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data/retrieval_battle-b9229914-47bc-4da8-a21b-89329fff8207.jsonl

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 {"tstamp": 1722310835.8058, "task_type": "retrieval", "type": "bothbadvote", "models": ["", ""], "ip": "", "0_conv_id": "51662d2391894809a37610cb3c419e8a", "0_model_name": "intfloat/multilingual-e5-large-instruct", "0_prompt": "what is the difference between field and sigma field?", "0_output": [["what is the difference between field and sigma field?", "Math Stackexchange\n\nQ: $\\sigma$-algebra vs. $\\sigma$-field: is there any difference? The subject says it all: is there any difference between the two concepts of $\\sigma$-algebra and $\\sigma$-field? In probability theory, they seem to be used more or less interchangeably. If there is no difference, is there any historical reason why some people/schools use the term $\\sigma$-algebra, while others use the term $\\sigma-$field?\n\nA: If you want to be completely sure you can see Taylor´s Introduction to Measure and Integration where he states that both concepts refer to the same thing.\n"]], "0_corpus": "stackexchange", "1_conv_id": "c60e866a11304ec09c51a718d9b9bbb8", "1_model_name": "mixedbread-ai/mxbai-embed-large-v1", "1_prompt": "what is the difference between field and sigma field?", "1_output": [["what is the difference between field and sigma field?", "Math Stackexchange\n\nQ: $\\sigma$-algebra vs. $\\sigma$-field: is there any difference? The subject says it all: is there any difference between the two concepts of $\\sigma$-algebra and $\\sigma$-field? In probability theory, they seem to be used more or less interchangeably. If there is no difference, is there any historical reason why some people/schools use the term $\\sigma$-algebra, while others use the term $\\sigma-$field?\n\nA: If you want to be completely sure you can see Taylor´s Introduction to Measure and Integration where he states that both concepts refer to the same thing.\n"]], "1_corpus": "stackexchange"}
 {"tstamp": 1722310863.6196, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "4f330aeb5b2b442d8190b75b12ed1f29", "0_model_name": "nomic-ai/nomic-embed-text-v1.5", "0_prompt": "New search algorithm inspired by AlphaZero for better theorem proving results", "0_output": [["New search algorithm inspired by AlphaZero for better theorem proving results", "Title: On the propagation of semiclassical Wigner functions\n\nAbstract: We establish the difference between the propagation of semiclassical Wigner functions and classical Liouville propagation. First we re-discuss the semiclassical limit for the propagator of Wigner functions, which on its own leads to their classical propagation. Then, via stationary phase evaluation of the full integral evolution equation, using the semiclassical expressions of Wigner functions, we provide the correct geometrical prescription for their semiclassical propagation. This is determined by the classical trajectories of the tips of the chords defined by the initial semiclassical Wigner function and centered on their arguments, in contrast to the Liouville propagation which is determined by the classical trajectories of the arguments themselves."]], "0_corpus": "arxiv", "1_conv_id": "86fc44429afe4954a77719d25bf4ef90", "1_model_name": "GritLM/GritLM-7B", "1_prompt": "New search algorithm inspired by AlphaZero for better theorem proving results", "1_output": [["New search algorithm inspired by AlphaZero for better theorem proving results", "Title: HyperTree Proof Search for Neural Theorem Proving\n\nAbstract: We propose an online training procedure for a transformer-based automated theorem prover. Our approach leverages a new search algorithm, HyperTree Proof Search (HTPS), inspired by the recent success of AlphaZero. Our model learns from previous proof searches through online training, allowing it to generalize to domains far from the training distribution. We report detailed ablations of our pipeline's main components by studying performance on three environments of increasing complexity. In particular, we show that with HTPS alone, a model trained on annotated proofs manages to prove 65.4% of a held-out set of Metamath theorems, significantly outperforming the previous state of the art of 56.5% by GPT-f. Online training on these unproved theorems increases accuracy to 82.6%. With a similar computational budget, we improve the state of the art on the Lean-based miniF2F-curriculum dataset from 31% to 42% proving accuracy."]], "1_corpus": "arxiv"}
 {"tstamp": 1722310892.1304, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "c998ef114db443b0a8ea43dcaa79997c", "0_model_name": "GritLM/GritLM-7B", "0_prompt": "can I put metal plate in a microwave", "0_output": [["can I put metal plate in a microwave", "Microwave oven\n\nMetal objects Contrary to popular assumptions, metal objects can be safely used in a microwave oven, but with some restrictions. Any metal or conductive object placed into the microwave oven acts as an antenna to some degree, resulting in an electric current. This causes the object to act as a heating element. This effect varies with the object's shape and composition, and is sometimes utilized for cooking.\nAny object containing pointed metal can create an electric arc (sparks) when microwaved. This includes cutlery, crumpled aluminium foil (though some foil used in microwave ovens is safe, see below), twist-ties containing metal wire, the metal wire carry-handles in oyster pails, or almost any metal formed into a poorly conductive foil or thin wire, or into a pointed shape. Forks are a good example: the tines of the fork respond to the electric field by producing high concentrations of electric charge at the tips. This has the effect of exceeding the dielectric breakdown of air, about 3 megavolts per meter (3×106 V/m). The air forms a conductive plasma, which is visible as a spark. The plasma and the tines may then form a conductive loop, which may be a more effective antenna, resulting in a longer lived spark. When dielectric breakdown occurs in air, some ozone and nitrogen oxides are formed, both of which are unhealthy in large quantities."]], "0_corpus": "wikipedia", "1_conv_id": "088ae8addacd4fa3a40cb59053e8abe6", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "can I put metal plate in a microwave", "1_output": [["can I put metal plate in a microwave", "Microwave oven\n\nMetal objects Contrary to popular assumptions, metal objects can be safely used in a microwave oven, but with some restrictions. Any metal or conductive object placed into the microwave oven acts as an antenna to some degree, resulting in an electric current. This causes the object to act as a heating element. This effect varies with the object's shape and composition, and is sometimes utilized for cooking.\nAny object containing pointed metal can create an electric arc (sparks) when microwaved. This includes cutlery, crumpled aluminium foil (though some foil used in microwave ovens is safe, see below), twist-ties containing metal wire, the metal wire carry-handles in oyster pails, or almost any metal formed into a poorly conductive foil or thin wire, or into a pointed shape. Forks are a good example: the tines of the fork respond to the electric field by producing high concentrations of electric charge at the tips. This has the effect of exceeding the dielectric breakdown of air, about 3 megavolts per meter (3×106 V/m). The air forms a conductive plasma, which is visible as a spark. The plasma and the tines may then form a conductive loop, which may be a more effective antenna, resulting in a longer lived spark. When dielectric breakdown occurs in air, some ozone and nitrogen oxides are formed, both of which are unhealthy in large quantities."]], "1_corpus": "wikipedia"}
+{"tstamp": 1722310932.6557, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "cbdc637378324499be0368c4cf0b44de", "0_model_name": "embed-english-v3.0", "0_prompt": "when was the abacus invented in ancient china", "0_output": [["when was the abacus invented in ancient china", "Abacus\n\nEgypt Greek historian Herodotus mentioned the abacus in Ancient Egypt. He wrote that the Egyptians manipulated the pebbles from right to left, opposite in direction to the Greek left-to-right method. Archaeologists have found ancient disks of various sizes that are thought to have been used as counters. However, wall depictions of this instrument are yet to be discovered.\nPersia\nAt around 600 BC, Persians first began to use the abacus, during the Achaemenid Empire. Under the Parthian, Sassanian, and Iranian empires, scholars concentrated on exchanging knowledge and inventions with the countries around them – India, China, and the Roman Empire- which is how the abacus may have been exported to other countries.\nGreece\nThe earliest archaeological evidence for the use of the Greek abacus dates to the 5th century BC. Demosthenes (384 BC–322 BC) complained that the need to use pebbles for calculations was too difficult. A play by Alexis from the 4th century BC mentions an abacus and pebbles for accounting, and both Diogenes and Polybius use the abacus as a metaphor for human behavior, stating \"that men that sometimes stood for more and sometimes for less\" like the pebbles on an abacus. The Greek abacus was a table of wood or marble, pre-set with small counters in wood or metal for mathematical calculations. This Greek abacus was used in Achaemenid Persia, the Etruscan civilization, Ancient Rome, and the Western Christian world until the French Revolution."]], "0_corpus": "wikipedia", "1_conv_id": "f78b452ffa04499e97fec3be70a373c3", "1_model_name": "jinaai/jina-embeddings-v2-base-en", "1_prompt": "when was the abacus invented in ancient china", "1_output": [["when was the abacus invented in ancient china", "Abacus\n\nEach rod typically represents one digit of a multi-digit number laid out using a positional numeral system such as base ten (though some cultures used different numerical bases). Roman and East Asian abacuses use a system resembling bi-quinary coded decimal, with a top deck (containing one or two beads) representing fives and a bottom deck (containing four or five beads) representing ones. Natural numbers are normally used, but some allow simple fractional components (e.g. , , and  in Roman abacus), and a decimal point can be imagined for fixed-point arithmetic.\nAny particular abacus design supports multiple methods to perform calculations, including addition, subtraction, multiplication, division, and square and cube roots. The beads are first arranged to represent a number, then are manipulated to perform a mathematical operation with another number, and their final position can be read as the result (or can be used as the starting number for subsequent operations).\nIn the ancient world, abacuses were a practical calculating tool. Although calculators and computers are commonly used today instead of abacuses, abacuses remain in everyday use in some countries. The abacus has an advantage of not requiring a writing implement and paper (needed for algorism) or an electric power source. Merchants, traders, and clerks in some parts of Eastern Europe, Russia, China, and Africa use abacuses. The abacus remains in common use as a scoring system in non-electronic table games. Others may use an abacus due to visual impairment that prevents the use of a calculator. The abacus is still used to teach the fundamentals of mathematics to children in most countries."]], "1_corpus": "wikipedia"}
+{"tstamp": 1722310979.3311, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "b6d7ab0bc1bb42cb8e93438eef835621", "0_model_name": "GritLM/GritLM-7B", "0_prompt": "where does the spinal cord become cauda equina", "0_output": [["where does the spinal cord become cauda equina", "Cauda equina\n\nDevelopment In humans, the spinal cord stops growing in infancy.  At birth the end of the spinal cord is about the level of the third lumbar vertebra, or L3. Because the bones of the vertebral column continue to grow, by about 12 months of age the end of the cord reaches its permanent position. Typically this is at the level of L1 or L2 (closer to the head), ranging due to normal anatomical variations anywhere from the twelfth thoracic vertebra (T12) to L3. Individual spinal nerve roots arise from the cord as they get closer to the head, but as the differential growth occurs, the top end of the nerve stays attached to the spinal cord while the lower end of the nerve exits the spinal column at its proper level. This results in a \"bundle\"-like structure of nerve fibers that extends caudally, within the spinal column, from the end of the spinal cord, gradually declining in number further down as individual pairs leave the spinal column.\nClinical significance\nNeedle insertion\nThe cauda equina exists within the lumbar cistern, a gap between the arachnoid membrane and the pia mater of the spinal cord, called the subarachnoid space. Cerebrospinal fluid also exists within this space. Because the spinal cord terminates at level L1/L2, lumbar puncture (or colloquially, \"spinal tap\") is performed from the lumbar cistern between two vertebrae at level L3/L4, or L4/L5, where there is no risk of accidental injury to the spinal cord, when a sample of CSF is needed for clinical purposes."]], "0_corpus": "wikipedia", "1_conv_id": "8dd7868f665946e3bc2d5ff340ff7f95", "1_model_name": "text-embedding-004", "1_prompt": "where does the spinal cord become cauda equina", "1_output": [["where does the spinal cord become cauda equina", "Cauda equina\n\nDevelopment In humans, the spinal cord stops growing in infancy.  At birth the end of the spinal cord is about the level of the third lumbar vertebra, or L3. Because the bones of the vertebral column continue to grow, by about 12 months of age the end of the cord reaches its permanent position. Typically this is at the level of L1 or L2 (closer to the head), ranging due to normal anatomical variations anywhere from the twelfth thoracic vertebra (T12) to L3. Individual spinal nerve roots arise from the cord as they get closer to the head, but as the differential growth occurs, the top end of the nerve stays attached to the spinal cord while the lower end of the nerve exits the spinal column at its proper level. This results in a \"bundle\"-like structure of nerve fibers that extends caudally, within the spinal column, from the end of the spinal cord, gradually declining in number further down as individual pairs leave the spinal column.\nClinical significance\nNeedle insertion\nThe cauda equina exists within the lumbar cistern, a gap between the arachnoid membrane and the pia mater of the spinal cord, called the subarachnoid space. Cerebrospinal fluid also exists within this space. Because the spinal cord terminates at level L1/L2, lumbar puncture (or colloquially, \"spinal tap\") is performed from the lumbar cistern between two vertebrae at level L3/L4, or L4/L5, where there is no risk of accidental injury to the spinal cord, when a sample of CSF is needed for clinical purposes."]], "1_corpus": "wikipedia"}
+{"tstamp": 1722311003.1834, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "14396d4a28ae4f839eb1d20af5252e72", "0_model_name": "text-embedding-3-large", "0_prompt": "Transformer-based model designed specifically for Arabic language understanding", "0_output": [["Transformer-based model designed specifically for Arabic language understanding", "Title: Interpreting Arabic Transformer Models\n\nAbstract: Arabic is a Semitic language which is widely spoken with many dialects. Given the success of pre-trained language models, many transformer models trained on Arabic and its dialects have surfaced. While these models have been compared with respect to downstream NLP tasks, no evaluation has been carried out to directly compare the internal representations. We probe how linguistic information is encoded in Arabic pretrained models, trained on different varieties of Arabic language. We perform a layer and neuron analysis on the models using three intrinsic tasks: two morphological tagging tasks based on MSA (modern standard Arabic) and dialectal POS-tagging and a dialectal identification task. Our analysis enlightens interesting findings such as: i) word morphology is learned at the lower and middle layers ii) dialectal identification necessitate more knowledge and hence preserved even in the final layers, iii) despite a large overlap in their vocabulary, the MSA-based models fail to capture the nuances of Arabic dialects, iv) we found that neurons in embedding layers are polysemous in nature, while the neurons in middle layers are exclusive to specific properties."]], "0_corpus": "arxiv", "1_conv_id": "f9f953034cbb4a10a1b425e550d64406", "1_model_name": "voyage-multilingual-2", "1_prompt": "Transformer-based model designed specifically for Arabic language understanding", "1_output": [["Transformer-based model designed specifically for Arabic language understanding", "Title: AraBERT: Transformer-based Model for Arabic Language Understanding\n\nAbstract: The Arabic language is a morphologically rich language with relatively few resources and a less explored syntax compared to English. Given these limitations, Arabic Natural Language Processing (NLP) tasks like Sentiment Analysis (SA), Named Entity Recognition (NER), and Question Answering (QA), have proven to be very challenging to tackle. Recently, with the surge of transformers based models, language-specific BERT based models have proven to be very efficient at language understanding, provided they are pre-trained on a very large corpus. Such models were able to set new standards and achieve state-of-the-art results for most NLP tasks. In this paper, we pre-trained BERT specifically for the Arabic language in the pursuit of achieving the same success that BERT did for the English language. The performance of AraBERT is compared to multilingual BERT from Google and other state-of-the-art approaches. The results showed that the newly developed AraBERT achieved state-of-the-art performance on most tested Arabic NLP tasks. The pretrained araBERT models are publicly available on https://github.com/aub-mind/arabert hoping to encourage research and applications for Arabic NLP."]], "1_corpus": "arxiv"}
+{"tstamp": 1722311101.6953, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "42b61a56dbda4f8fb93f621e039f5ce4", "0_model_name": "intfloat/multilingual-e5-large-instruct", "0_prompt": "do switches use ip or mac?", "0_output": [["do switches use ip or mac?", "Superuser Stackexchange\n\nQ: IP Address vs MAC addresses why do we need ip addresses if mac address is enough to identify the machine???\n\nA: There are many reasons. For example: MAC address is bound to hardware. It means you can't or rather are not supposed to have the same MAC on different hardware. Imagine that google has to change DNS binding of \"google.com\" to \"MAC\" address each time they change some network card on front-end server.\nAnother reason is that MAC addresses are assigned by producers while IP addresses are assigned by network admins. This allows building hierarchy of addresses that is root of packets routing. This is because way from IP A1.A2.A3.A4 to B1.B2.B3.B4 is easily predictable and way from MAC#1 to MAC#2 isn't.\nNext reason is that MAC is Ethernet-related stuff and there are other network technologies that might not use MAC at all.\n"]], "0_corpus": "stackexchange", "1_conv_id": "ae5bb24c1351491fa7a7bb739099f035", "1_model_name": "BM25", "1_prompt": "do switches use ip or mac?", "1_output": [["do switches use ip or mac?", "Serverfault Stackexchange\n\nQ: Deny Static IP Assignments I am currently using a SonicWall Pro 2040 with DHCP enabled, but only with static IPs mapped to specific MAC addresses. There is no dynamic IP scope being used. Currently, no DHCP request will resolve an IP, as desired.\nHowever, if a server or workstation network interface is still configured with a user-defined, static IP address, it works fine. I would like potential users who assign their machines with static IPs to not work.\nIs there a way to deny these types of connections whose MAC address is not approved? \n\nA: There is no way to configure a DHCP server to deny static IP addresses. If you think about it, there is a direct path between hosts on the network that simply does not go through the SonicWall:\n            SonicWall\n            LAN Port\n                ^\n                |\n                v\nHostA <----> Switch <----> HostB\n\nSo if you want to filter on MAC address to stop HostA from advertising an IP address on the network, you need to do so at the switch. As an example, if your switch is a Cisco, the command to use is switchport port-security.\n"]], "1_corpus": "stackexchange"}
+{"tstamp": 1722311103.6017, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "dd1cd051afc647eabf636fc6055dea05", "0_model_name": "intfloat/multilingual-e5-large-instruct", "0_prompt": "How can retrieval-based methods be optimized to balance the trade-off between retrieval precision and computational efficiency in large-scale neural information retrieval systems?", "0_output": [["How can retrieval-based methods be optimized to balance the trade-off between retrieval precision and computational efficiency in large-scale neural information retrieval systems?", "Evaluation measures (information retrieval)\n\nSome authors choose to interpolate the  function to reduce the impact of \"wiggles\" in the curve. For example, the PASCAL Visual Object Classes challenge (a benchmark for computer vision object detection) until 2010 computed the average precision by averaging the precision over a set of evenly spaced recall levels {0, 0.1, 0.2, ... 1.0}:\nwhere  is an interpolated precision that takes the maximum precision over all recalls greater than :\n.\nAn alternative is to derive an analytical  function by assuming a particular parametric distribution for the underlying decision values. For example, a binormal precision-recall curve can be obtained by assuming decision values in both classes to follow a Gaussian distribution.\nThe minimum achievable AveP for a given classification task is given by:\nPrecision at k\nFor modern (web-scale) information retrieval, recall is no longer a meaningful metric, as many queries have thousands of relevant documents, and few users will be interested in reading all of them. Precision at k documents (P@k) is still a useful metric (e.g., P@10 or \"Precision at 10\" corresponds to the number of relevant results among the top 10 retrieved documents), but fails to take into account the positions of the relevant documents among the top k.  Another shortcoming is that on a query with fewer relevant results than k, even a perfect system will have a score less than 1.  It is easier to score manually since only the top k results need to be examined to determine if they are relevant or not."]], "0_corpus": "wikipedia", "1_conv_id": "181c322773ac4bf5a3d0c6321237b30a", "1_model_name": "Salesforce/SFR-Embedding-2_R", "1_prompt": "How can retrieval-based methods be optimized to balance the trade-off between retrieval precision and computational efficiency in large-scale neural information retrieval systems?", "1_output": [["How can retrieval-based methods be optimized to balance the trade-off between retrieval precision and computational efficiency in large-scale neural information retrieval systems?", "Information retrieval\n\nInformation retrieval (IR) in computing and information science is the task of identifying and retrieving information system resources that are relevant to an information need.  The information need can be specified in the form of a search query. In the case of document retrieval, queries can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.\nAutomated information retrieval systems are used to reduce what has been called information overload. An IR system is a software system that provides access to books, journals and other documents; it also stores and manages those documents. Web search engines are the most visible IR applications."]], "1_corpus": "wikipedia"}
+{"tstamp": 1722311155.3291, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "af5d587baf874dcaa68ca13be655b9ec", "0_model_name": "mixedbread-ai/mxbai-embed-large-v1", "0_prompt": "Impact of AI chatbots on academic integrity and plagiarism", "0_output": [["Impact of AI chatbots on academic integrity and plagiarism", "Title: Will ChatGPT get you caught? Rethinking of Plagiarism Detection\n\nAbstract: The rise of Artificial Intelligence (AI) technology and its impact on education has been a topic of growing concern in recent years. The new generation AI systems such as chatbots have become more accessible on the Internet and stronger in terms of capabilities. The use of chatbots, particularly ChatGPT, for generating academic essays at schools and colleges has sparked fears among scholars. This study aims to explore the originality of contents produced by one of the most popular AI chatbots, ChatGPT. To this end, two popular plagiarism detection tools were used to evaluate the originality of 50 essays generated by ChatGPT on various topics. Our results manifest that ChatGPT has a great potential to generate sophisticated text outputs without being well caught by the plagiarism check software. In other words, ChatGPT can create content on many topics with high originality as if they were written by someone. These findings align with the recent concerns about students using chatbots for an easy shortcut to success with minimal or no effort. Moreover, ChatGPT was asked to verify if the essays were generated by itself, as an additional measure of plagiarism check, and it showed superior performance compared to the traditional plagiarism-detection tools. The paper discusses the need for institutions to consider appropriate measures to mitigate potential plagiarism issues and advise on the ongoing debate surrounding the impact of AI technology on education. Further implications are discussed in the paper."]], "0_corpus": "arxiv", "1_conv_id": "6912b24d5d0444babee7fd61715355bc", "1_model_name": "text-embedding-004", "1_prompt": "Impact of AI chatbots on academic integrity and plagiarism", "1_output": [["Impact of AI chatbots on academic integrity and plagiarism", "Title: Will ChatGPT get you caught? Rethinking of Plagiarism Detection\n\nAbstract: The rise of Artificial Intelligence (AI) technology and its impact on education has been a topic of growing concern in recent years. The new generation AI systems such as chatbots have become more accessible on the Internet and stronger in terms of capabilities. The use of chatbots, particularly ChatGPT, for generating academic essays at schools and colleges has sparked fears among scholars. This study aims to explore the originality of contents produced by one of the most popular AI chatbots, ChatGPT. To this end, two popular plagiarism detection tools were used to evaluate the originality of 50 essays generated by ChatGPT on various topics. Our results manifest that ChatGPT has a great potential to generate sophisticated text outputs without being well caught by the plagiarism check software. In other words, ChatGPT can create content on many topics with high originality as if they were written by someone. These findings align with the recent concerns about students using chatbots for an easy shortcut to success with minimal or no effort. Moreover, ChatGPT was asked to verify if the essays were generated by itself, as an additional measure of plagiarism check, and it showed superior performance compared to the traditional plagiarism-detection tools. The paper discusses the need for institutions to consider appropriate measures to mitigate potential plagiarism issues and advise on the ongoing debate surrounding the impact of AI technology on education. Further implications are discussed in the paper."]], "1_corpus": "arxiv"}
+{"tstamp": 1722311155.3294, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "c96bbb99cf3546ba97838b73048bd5fa", "0_model_name": "BM25", "0_prompt": "What are the main causes and effects of the Industrial Revolution?", "0_output": [["What are the main causes and effects of the Industrial Revolution?", "Industrial Revolution\n\nPrimitivism Primitivism argues that the Industrial Revolution have created an un-natural frame of society and the world in which humans need to adapt to an un-natural urban landscape in which humans are perpetual cogs without personal autonomy.\nCertain primitivists argue for a return to pre-industrial society, while others argue that technology such as modern medicine, and agriculture are all positive for humanity assuming they are controlled by and serve humanity and have no effect on the natural environment.\nPollution and ecological collapse\nThe Industrial Revolution has been criticised for leading to immense ecological and habitat destruction. It has led to immense decrease in the biodiversity of life on Earth. The Industrial revolution has been said to be inherently unsustainable and will lead to eventual collapse of society, mass hunger, starvation, and resource scarcity.\nThe Anthropocene\nThe Anthropocene is a proposed epoch or mass extinction coming from humanity (anthropo- is the Greek root for humanity). Since the start of the Industrial revolution humanity has permanently changed the Earth, such as immense decrease in biodiversity, and mass extinction caused by the Industrial revolution. The effects include permanent changes to the Earth's atmosphere and soil, forests, the mass destruction of the Industrial revolution has led to catastrophic impacts on the Earth. Most organisms are unable to adapt leading to mass extinction with the remaining undergoing evolutionary rescue, as a result of the Industrial revolution."]], "0_corpus": "wikipedia", "1_conv_id": "babef639f1a24f2a9ac89cb3279d6177", "1_model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "1_prompt": "What are the main causes and effects of the Industrial Revolution?", "1_output": [["What are the main causes and effects of the Industrial Revolution?", "De-industrialisation of India\n\nThe fall in the hegemony of Mughals reduced the overall productivity of agriculture and reduced the supply of grains. The grain was the primary consumption good for the Indian workers and was non-tradeable. The reduction in the supply of grain resulted in the rise of its prices. This rise in prices and negative supply shock led to a rise in the nominal wages in the cotton and weaving industry. The increased competition from British cotton and rising nominal wages reduced the profitability of the cotton industry of India. Thus, the negative supply shock in agricultural production is also an important reason behind the de-industrialisation of cotton–industries.\nThe short run as well as long run impact on living standards and growth rate of GDP providing agriculture sector competitive advantage with strengthening of the productivity advance on the land at home or increasing openness to world in turn increases GDP in the short run. The causes of de-industrialisation are region or country specific as in the case of India in the 19th and 20th century. The colonial rule under the British led to the decline of textile and handicrafts industries through their policies and introduction of machine made goods in to the Indian market. Some of the causes of de-industrialisation in India during that period were:\nIntroduction of machine made goods in the Indian subcontinent at a cheaper rate, which led to the decline of the traditional textile industry of India."]], "1_corpus": "wikipedia"}

data/retrieval_individual-b9229914-47bc-4da8-a21b-89329fff8207.jsonl

@@ -73,3 +73,17 @@
 {"tstamp": 1722310874.1706, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1722310873.894, "finish": 1722310874.1706, "ip": "", "conv_id": "f78b452ffa04499e97fec3be70a373c3", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "when was the abacus invented in ancient china", "output": [["when was the abacus invented in ancient china", "Abacus\n\nEach rod typically represents one digit of a multi-digit number laid out using a positional numeral system such as base ten (though some cultures used different numerical bases). Roman and East Asian abacuses use a system resembling bi-quinary coded decimal, with a top deck (containing one or two beads) representing fives and a bottom deck (containing four or five beads) representing ones. Natural numbers are normally used, but some allow simple fractional components (e.g. , , and  in Roman abacus), and a decimal point can be imagined for fixed-point arithmetic.\nAny particular abacus design supports multiple methods to perform calculations, including addition, subtraction, multiplication, division, and square and cube roots. The beads are first arranged to represent a number, then are manipulated to perform a mathematical operation with another number, and their final position can be read as the result (or can be used as the starting number for subsequent operations).\nIn the ancient world, abacuses were a practical calculating tool. Although calculators and computers are commonly used today instead of abacuses, abacuses remain in everyday use in some countries. The abacus has an advantage of not requiring a writing implement and paper (needed for algorism) or an electric power source. Merchants, traders, and clerks in some parts of Eastern Europe, Russia, China, and Africa use abacuses. The abacus remains in common use as a scoring system in non-electronic table games. Others may use an abacus due to visual impairment that prevents the use of a calculator. The abacus is still used to teach the fundamentals of mathematics to children in most countries."]], "corpus": "wikipedia"}
 {"tstamp": 1722310885.7903, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722310883.6154, "finish": 1722310885.7903, "ip": "", "conv_id": "c998ef114db443b0a8ea43dcaa79997c", "model_name": "GritLM/GritLM-7B", "prompt": "can I put metal plate in a microwave", "output": [["can I put metal plate in a microwave", "Microwave oven\n\nMetal objects Contrary to popular assumptions, metal objects can be safely used in a microwave oven, but with some restrictions. Any metal or conductive object placed into the microwave oven acts as an antenna to some degree, resulting in an electric current. This causes the object to act as a heating element. This effect varies with the object's shape and composition, and is sometimes utilized for cooking.\nAny object containing pointed metal can create an electric arc (sparks) when microwaved. This includes cutlery, crumpled aluminium foil (though some foil used in microwave ovens is safe, see below), twist-ties containing metal wire, the metal wire carry-handles in oyster pails, or almost any metal formed into a poorly conductive foil or thin wire, or into a pointed shape. Forks are a good example: the tines of the fork respond to the electric field by producing high concentrations of electric charge at the tips. This has the effect of exceeding the dielectric breakdown of air, about 3 megavolts per meter (3×106 V/m). The air forms a conductive plasma, which is visible as a spark. The plasma and the tines may then form a conductive loop, which may be a more effective antenna, resulting in a longer lived spark. When dielectric breakdown occurs in air, some ozone and nitrogen oxides are formed, both of which are unhealthy in large quantities."]], "corpus": "wikipedia"}
 {"tstamp": 1722310885.7903, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722310883.6154, "finish": 1722310885.7903, "ip": "", "conv_id": "088ae8addacd4fa3a40cb59053e8abe6", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "can I put metal plate in a microwave", "output": [["can I put metal plate in a microwave", "Microwave oven\n\nMetal objects Contrary to popular assumptions, metal objects can be safely used in a microwave oven, but with some restrictions. Any metal or conductive object placed into the microwave oven acts as an antenna to some degree, resulting in an electric current. This causes the object to act as a heating element. This effect varies with the object's shape and composition, and is sometimes utilized for cooking.\nAny object containing pointed metal can create an electric arc (sparks) when microwaved. This includes cutlery, crumpled aluminium foil (though some foil used in microwave ovens is safe, see below), twist-ties containing metal wire, the metal wire carry-handles in oyster pails, or almost any metal formed into a poorly conductive foil or thin wire, or into a pointed shape. Forks are a good example: the tines of the fork respond to the electric field by producing high concentrations of electric charge at the tips. This has the effect of exceeding the dielectric breakdown of air, about 3 megavolts per meter (3×106 V/m). The air forms a conductive plasma, which is visible as a spark. The plasma and the tines may then form a conductive loop, which may be a more effective antenna, resulting in a longer lived spark. When dielectric breakdown occurs in air, some ozone and nitrogen oxides are formed, both of which are unhealthy in large quantities."]], "corpus": "wikipedia"}
+{"tstamp": 1722310958.2128, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722310957.4932, "finish": 1722310958.2128, "ip": "", "conv_id": "b6d7ab0bc1bb42cb8e93438eef835621", "model_name": "GritLM/GritLM-7B", "prompt": "where does the spinal cord become cauda equina", "output": [["where does the spinal cord become cauda equina", "Cauda equina\n\nDevelopment In humans, the spinal cord stops growing in infancy.  At birth the end of the spinal cord is about the level of the third lumbar vertebra, or L3. Because the bones of the vertebral column continue to grow, by about 12 months of age the end of the cord reaches its permanent position. Typically this is at the level of L1 or L2 (closer to the head), ranging due to normal anatomical variations anywhere from the twelfth thoracic vertebra (T12) to L3. Individual spinal nerve roots arise from the cord as they get closer to the head, but as the differential growth occurs, the top end of the nerve stays attached to the spinal cord while the lower end of the nerve exits the spinal column at its proper level. This results in a \"bundle\"-like structure of nerve fibers that extends caudally, within the spinal column, from the end of the spinal cord, gradually declining in number further down as individual pairs leave the spinal column.\nClinical significance\nNeedle insertion\nThe cauda equina exists within the lumbar cistern, a gap between the arachnoid membrane and the pia mater of the spinal cord, called the subarachnoid space. Cerebrospinal fluid also exists within this space. Because the spinal cord terminates at level L1/L2, lumbar puncture (or colloquially, \"spinal tap\") is performed from the lumbar cistern between two vertebrae at level L3/L4, or L4/L5, where there is no risk of accidental injury to the spinal cord, when a sample of CSF is needed for clinical purposes."]], "corpus": "wikipedia"}
+{"tstamp": 1722310958.2128, "task_type": "retrieval", "type": "chat", "model": "text-embedding-004", "gen_params": {}, "start": 1722310957.4932, "finish": 1722310958.2128, "ip": "", "conv_id": "8dd7868f665946e3bc2d5ff340ff7f95", "model_name": "text-embedding-004", "prompt": "where does the spinal cord become cauda equina", "output": [["where does the spinal cord become cauda equina", "Cauda equina\n\nDevelopment In humans, the spinal cord stops growing in infancy.  At birth the end of the spinal cord is about the level of the third lumbar vertebra, or L3. Because the bones of the vertebral column continue to grow, by about 12 months of age the end of the cord reaches its permanent position. Typically this is at the level of L1 or L2 (closer to the head), ranging due to normal anatomical variations anywhere from the twelfth thoracic vertebra (T12) to L3. Individual spinal nerve roots arise from the cord as they get closer to the head, but as the differential growth occurs, the top end of the nerve stays attached to the spinal cord while the lower end of the nerve exits the spinal column at its proper level. This results in a \"bundle\"-like structure of nerve fibers that extends caudally, within the spinal column, from the end of the spinal cord, gradually declining in number further down as individual pairs leave the spinal column.\nClinical significance\nNeedle insertion\nThe cauda equina exists within the lumbar cistern, a gap between the arachnoid membrane and the pia mater of the spinal cord, called the subarachnoid space. Cerebrospinal fluid also exists within this space. Because the spinal cord terminates at level L1/L2, lumbar puncture (or colloquially, \"spinal tap\") is performed from the lumbar cistern between two vertebrae at level L3/L4, or L4/L5, where there is no risk of accidental injury to the spinal cord, when a sample of CSF is needed for clinical purposes."]], "corpus": "wikipedia"}
+{"tstamp": 1722310988.5027, "task_type": "retrieval", "type": "chat", "model": "text-embedding-3-large", "gen_params": {}, "start": 1722310987.9544, "finish": 1722310988.5027, "ip": "", "conv_id": "14396d4a28ae4f839eb1d20af5252e72", "model_name": "text-embedding-3-large", "prompt": "Transformer-based model designed specifically for Arabic language understanding", "output": [["Transformer-based model designed specifically for Arabic language understanding", "Title: Interpreting Arabic Transformer Models\n\nAbstract: Arabic is a Semitic language which is widely spoken with many dialects. Given the success of pre-trained language models, many transformer models trained on Arabic and its dialects have surfaced. While these models have been compared with respect to downstream NLP tasks, no evaluation has been carried out to directly compare the internal representations. We probe how linguistic information is encoded in Arabic pretrained models, trained on different varieties of Arabic language. We perform a layer and neuron analysis on the models using three intrinsic tasks: two morphological tagging tasks based on MSA (modern standard Arabic) and dialectal POS-tagging and a dialectal identification task. Our analysis enlightens interesting findings such as: i) word morphology is learned at the lower and middle layers ii) dialectal identification necessitate more knowledge and hence preserved even in the final layers, iii) despite a large overlap in their vocabulary, the MSA-based models fail to capture the nuances of Arabic dialects, iv) we found that neurons in embedding layers are polysemous in nature, while the neurons in middle layers are exclusive to specific properties."]], "corpus": "arxiv"}
+{"tstamp": 1722310988.5027, "task_type": "retrieval", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1722310987.9544, "finish": 1722310988.5027, "ip": "", "conv_id": "f9f953034cbb4a10a1b425e550d64406", "model_name": "voyage-multilingual-2", "prompt": "Transformer-based model designed specifically for Arabic language understanding", "output": [["Transformer-based model designed specifically for Arabic language understanding", "Title: AraBERT: Transformer-based Model for Arabic Language Understanding\n\nAbstract: The Arabic language is a morphologically rich language with relatively few resources and a less explored syntax compared to English. Given these limitations, Arabic Natural Language Processing (NLP) tasks like Sentiment Analysis (SA), Named Entity Recognition (NER), and Question Answering (QA), have proven to be very challenging to tackle. Recently, with the surge of transformers based models, language-specific BERT based models have proven to be very efficient at language understanding, provided they are pre-trained on a very large corpus. Such models were able to set new standards and achieve state-of-the-art results for most NLP tasks. In this paper, we pre-trained BERT specifically for the Arabic language in the pursuit of achieving the same success that BERT did for the English language. The performance of AraBERT is compared to multilingual BERT from Google and other state-of-the-art approaches. The results showed that the newly developed AraBERT achieved state-of-the-art performance on most tested Arabic NLP tasks. The pretrained araBERT models are publicly available on https://github.com/aub-mind/arabert hoping to encourage research and applications for Arabic NLP."]], "corpus": "arxiv"}
+{"tstamp": 1722311017.1892, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1722311016.9641, "finish": 1722311017.1892, "ip": "", "conv_id": "42b61a56dbda4f8fb93f621e039f5ce4", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "do switches use ip or mac?", "output": [["do switches use ip or mac?", "Superuser Stackexchange\n\nQ: IP Address vs MAC addresses why do we need ip addresses if mac address is enough to identify the machine???\n\nA: There are many reasons. For example: MAC address is bound to hardware. It means you can't or rather are not supposed to have the same MAC on different hardware. Imagine that google has to change DNS binding of \"google.com\" to \"MAC\" address each time they change some network card on front-end server.\nAnother reason is that MAC addresses are assigned by producers while IP addresses are assigned by network admins. This allows building hierarchy of addresses that is root of packets routing. This is because way from IP A1.A2.A3.A4 to B1.B2.B3.B4 is easily predictable and way from MAC#1 to MAC#2 isn't.\nNext reason is that MAC is Ethernet-related stuff and there are other network technologies that might not use MAC at all.\n"]], "corpus": "stackexchange"}
+{"tstamp": 1722311017.1892, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1722311016.9641, "finish": 1722311017.1892, "ip": "", "conv_id": "ae5bb24c1351491fa7a7bb739099f035", "model_name": "BM25", "prompt": "do switches use ip or mac?", "output": [["do switches use ip or mac?", "Serverfault Stackexchange\n\nQ: Deny Static IP Assignments I am currently using a SonicWall Pro 2040 with DHCP enabled, but only with static IPs mapped to specific MAC addresses. There is no dynamic IP scope being used. Currently, no DHCP request will resolve an IP, as desired.\nHowever, if a server or workstation network interface is still configured with a user-defined, static IP address, it works fine. I would like potential users who assign their machines with static IPs to not work.\nIs there a way to deny these types of connections whose MAC address is not approved? \n\nA: There is no way to configure a DHCP server to deny static IP addresses. If you think about it, there is a direct path between hosts on the network that simply does not go through the SonicWall:\n            SonicWall\n            LAN Port\n                ^\n                |\n                v\nHostA <----> Switch <----> HostB\n\nSo if you want to filter on MAC address to stop HostA from advertising an IP address on the network, you need to do so at the switch. As an example, if your switch is a Cisco, the command to use is switchport port-security.\n"]], "corpus": "stackexchange"}
+{"tstamp": 1722311040.472, "task_type": "retrieval", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1722311039.6792, "finish": 1722311040.472, "ip": "", "conv_id": "8472d85456e841798101c9a3e9d1d29a", "model_name": "voyage-multilingual-2", "prompt": "can I do multithreading with fastapi", "output": [["can I do multithreading with fastapi", "FastAPI\n\nFastAPI is a modern web framework first released in 2018 for building HTTP-based service APIs in Python. It is used for building APIs with Python 3.8+ based on standard Python-type hints.\nFastAPI is based on Pydantic and uses type hints to validate, serialize and deserialize data. It also automatically generates OpenAPI documentation for APIs built with it.\nComponents\nPydantic\nPydantic is a data validation library for Python. While writing code in an IDE, Pydantic provides type hints for schema validation and serialization through type annotations.\nStarlette\nStarlette is a lightweight ASGI framework/toolkit, to support async functionality in Python.\nUvicorn\nUvicorn is a minimal low-level server/application web server for async frameworks, following the ASGI specification. Technically, it implements a multi-process model with one main process, which is responsible for managing a pool of worker processes and distributing incoming HTTP requests to them. The number of worker processes is pre-configured, but can also be adjusted up or down at runtime.\nExample\nThe following code shows a simple web application that displays \"Hello World!\" when visited:\nfrom fastapi import FastAPI\napp = FastAPI()\n@app.get(\"/\")\ndef read_root():"]], "corpus": "wikipedia"}
+{"tstamp": 1722311040.472, "task_type": "retrieval", "type": "chat", "model": "text-embedding-004", "gen_params": {}, "start": 1722311039.6792, "finish": 1722311040.472, "ip": "", "conv_id": "b987e3526f4e4c9fbea6f0eae988d918", "model_name": "text-embedding-004", "prompt": "can I do multithreading with fastapi", "output": [["can I do multithreading with fastapi", "FastAPI\n\nFastAPI is a modern web framework first released in 2018 for building HTTP-based service APIs in Python. It is used for building APIs with Python 3.8+ based on standard Python-type hints.\nFastAPI is based on Pydantic and uses type hints to validate, serialize and deserialize data. It also automatically generates OpenAPI documentation for APIs built with it.\nComponents\nPydantic\nPydantic is a data validation library for Python. While writing code in an IDE, Pydantic provides type hints for schema validation and serialization through type annotations.\nStarlette\nStarlette is a lightweight ASGI framework/toolkit, to support async functionality in Python.\nUvicorn\nUvicorn is a minimal low-level server/application web server for async frameworks, following the ASGI specification. Technically, it implements a multi-process model with one main process, which is responsible for managing a pool of worker processes and distributing incoming HTTP requests to them. The number of worker processes is pre-configured, but can also be adjusted up or down at runtime.\nExample\nThe following code shows a simple web application that displays \"Hello World!\" when visited:\nfrom fastapi import FastAPI\napp = FastAPI()\n@app.get(\"/\")\ndef read_root():"]], "corpus": "wikipedia"}
+{"tstamp": 1722311095.9576, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1722311095.6351, "finish": 1722311095.9576, "ip": "", "conv_id": "dd1cd051afc647eabf636fc6055dea05", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "How can retrieval-based methods be optimized to balance the trade-off between retrieval precision and computational efficiency in large-scale neural information retrieval systems?", "output": [["How can retrieval-based methods be optimized to balance the trade-off between retrieval precision and computational efficiency in large-scale neural information retrieval systems?", "Evaluation measures (information retrieval)\n\nSome authors choose to interpolate the  function to reduce the impact of \"wiggles\" in the curve. For example, the PASCAL Visual Object Classes challenge (a benchmark for computer vision object detection) until 2010 computed the average precision by averaging the precision over a set of evenly spaced recall levels {0, 0.1, 0.2, ... 1.0}:\nwhere  is an interpolated precision that takes the maximum precision over all recalls greater than :\n.\nAn alternative is to derive an analytical  function by assuming a particular parametric distribution for the underlying decision values. For example, a binormal precision-recall curve can be obtained by assuming decision values in both classes to follow a Gaussian distribution.\nThe minimum achievable AveP for a given classification task is given by:\nPrecision at k\nFor modern (web-scale) information retrieval, recall is no longer a meaningful metric, as many queries have thousands of relevant documents, and few users will be interested in reading all of them. Precision at k documents (P@k) is still a useful metric (e.g., P@10 or \"Precision at 10\" corresponds to the number of relevant results among the top 10 retrieved documents), but fails to take into account the positions of the relevant documents among the top k.  Another shortcoming is that on a query with fewer relevant results than k, even a perfect system will have a score less than 1.  It is easier to score manually since only the top k results need to be examined to determine if they are relevant or not."]], "corpus": "wikipedia"}
+{"tstamp": 1722311095.9576, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722311095.6351, "finish": 1722311095.9576, "ip": "", "conv_id": "181c322773ac4bf5a3d0c6321237b30a", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "How can retrieval-based methods be optimized to balance the trade-off between retrieval precision and computational efficiency in large-scale neural information retrieval systems?", "output": [["How can retrieval-based methods be optimized to balance the trade-off between retrieval precision and computational efficiency in large-scale neural information retrieval systems?", "Information retrieval\n\nInformation retrieval (IR) in computing and information science is the task of identifying and retrieving information system resources that are relevant to an information need.  The information need can be specified in the form of a search query. In the case of document retrieval, queries can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.\nAutomated information retrieval systems are used to reduce what has been called information overload. An IR system is a software system that provides access to books, journals and other documents; it also stores and manages those documents. Web search engines are the most visible IR applications."]], "corpus": "wikipedia"}
+{"tstamp": 1722311121.1601, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1722311119.0323, "finish": 1722311121.1601, "ip": "", "conv_id": "af5d587baf874dcaa68ca13be655b9ec", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "Impact of AI chatbots on academic integrity and plagiarism", "output": [["Impact of AI chatbots on academic integrity and plagiarism", "Title: Will ChatGPT get you caught? Rethinking of Plagiarism Detection\n\nAbstract: The rise of Artificial Intelligence (AI) technology and its impact on education has been a topic of growing concern in recent years. The new generation AI systems such as chatbots have become more accessible on the Internet and stronger in terms of capabilities. The use of chatbots, particularly ChatGPT, for generating academic essays at schools and colleges has sparked fears among scholars. This study aims to explore the originality of contents produced by one of the most popular AI chatbots, ChatGPT. To this end, two popular plagiarism detection tools were used to evaluate the originality of 50 essays generated by ChatGPT on various topics. Our results manifest that ChatGPT has a great potential to generate sophisticated text outputs without being well caught by the plagiarism check software. In other words, ChatGPT can create content on many topics with high originality as if they were written by someone. These findings align with the recent concerns about students using chatbots for an easy shortcut to success with minimal or no effort. Moreover, ChatGPT was asked to verify if the essays were generated by itself, as an additional measure of plagiarism check, and it showed superior performance compared to the traditional plagiarism-detection tools. The paper discusses the need for institutions to consider appropriate measures to mitigate potential plagiarism issues and advise on the ongoing debate surrounding the impact of AI technology on education. Further implications are discussed in the paper."]], "corpus": "arxiv"}
+{"tstamp": 1722311121.1601, "task_type": "retrieval", "type": "chat", "model": "text-embedding-004", "gen_params": {}, "start": 1722311119.0323, "finish": 1722311121.1601, "ip": "", "conv_id": "6912b24d5d0444babee7fd61715355bc", "model_name": "text-embedding-004", "prompt": "Impact of AI chatbots on academic integrity and plagiarism", "output": [["Impact of AI chatbots on academic integrity and plagiarism", "Title: Will ChatGPT get you caught? Rethinking of Plagiarism Detection\n\nAbstract: The rise of Artificial Intelligence (AI) technology and its impact on education has been a topic of growing concern in recent years. The new generation AI systems such as chatbots have become more accessible on the Internet and stronger in terms of capabilities. The use of chatbots, particularly ChatGPT, for generating academic essays at schools and colleges has sparked fears among scholars. This study aims to explore the originality of contents produced by one of the most popular AI chatbots, ChatGPT. To this end, two popular plagiarism detection tools were used to evaluate the originality of 50 essays generated by ChatGPT on various topics. Our results manifest that ChatGPT has a great potential to generate sophisticated text outputs without being well caught by the plagiarism check software. In other words, ChatGPT can create content on many topics with high originality as if they were written by someone. These findings align with the recent concerns about students using chatbots for an easy shortcut to success with minimal or no effort. Moreover, ChatGPT was asked to verify if the essays were generated by itself, as an additional measure of plagiarism check, and it showed superior performance compared to the traditional plagiarism-detection tools. The paper discusses the need for institutions to consider appropriate measures to mitigate potential plagiarism issues and advise on the ongoing debate surrounding the impact of AI technology on education. Further implications are discussed in the paper."]], "corpus": "arxiv"}
+{"tstamp": 1722311138.467, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1722311136.1656, "finish": 1722311138.467, "ip": "", "conv_id": "c96bbb99cf3546ba97838b73048bd5fa", "model_name": "BM25", "prompt": "What are the main causes and effects of the Industrial Revolution?", "output": [["What are the main causes and effects of the Industrial Revolution?", "Industrial Revolution\n\nPrimitivism Primitivism argues that the Industrial Revolution have created an un-natural frame of society and the world in which humans need to adapt to an un-natural urban landscape in which humans are perpetual cogs without personal autonomy.\nCertain primitivists argue for a return to pre-industrial society, while others argue that technology such as modern medicine, and agriculture are all positive for humanity assuming they are controlled by and serve humanity and have no effect on the natural environment.\nPollution and ecological collapse\nThe Industrial Revolution has been criticised for leading to immense ecological and habitat destruction. It has led to immense decrease in the biodiversity of life on Earth. The Industrial revolution has been said to be inherently unsustainable and will lead to eventual collapse of society, mass hunger, starvation, and resource scarcity.\nThe Anthropocene\nThe Anthropocene is a proposed epoch or mass extinction coming from humanity (anthropo- is the Greek root for humanity). Since the start of the Industrial revolution humanity has permanently changed the Earth, such as immense decrease in biodiversity, and mass extinction caused by the Industrial revolution. The effects include permanent changes to the Earth's atmosphere and soil, forests, the mass destruction of the Industrial revolution has led to catastrophic impacts on the Earth. Most organisms are unable to adapt leading to mass extinction with the remaining undergoing evolutionary rescue, as a result of the Industrial revolution."]], "corpus": "wikipedia"}
+{"tstamp": 1722311138.467, "task_type": "retrieval", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1722311136.1656, "finish": 1722311138.467, "ip": "", "conv_id": "babef639f1a24f2a9ac89cb3279d6177", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "prompt": "What are the main causes and effects of the Industrial Revolution?", "output": [["What are the main causes and effects of the Industrial Revolution?", "De-industrialisation of India\n\nThe fall in the hegemony of Mughals reduced the overall productivity of agriculture and reduced the supply of grains. The grain was the primary consumption good for the Indian workers and was non-tradeable. The reduction in the supply of grain resulted in the rise of its prices. This rise in prices and negative supply shock led to a rise in the nominal wages in the cotton and weaving industry. The increased competition from British cotton and rising nominal wages reduced the profitability of the cotton industry of India. Thus, the negative supply shock in agricultural production is also an important reason behind the de-industrialisation of cotton–industries.\nThe short run as well as long run impact on living standards and growth rate of GDP providing agriculture sector competitive advantage with strengthening of the productivity advance on the land at home or increasing openness to world in turn increases GDP in the short run. The causes of de-industrialisation are region or country specific as in the case of India in the 19th and 20th century. The colonial rule under the British led to the decline of textile and handicrafts industries through their policies and introduction of machine made goods in to the Indian market. Some of the causes of de-industrialisation in India during that period were:\nIntroduction of machine made goods in the Indian subcontinent at a cheaper rate, which led to the decline of the traditional textile industry of India."]], "corpus": "wikipedia"}

data/retrieval_side_by_side-b9229914-47bc-4da8-a21b-89329fff8207.jsonl

@@ -1 +1,2 @@
 {"tstamp": 1722307028.8576, "task_type": "retrieval", "type": "rightvote", "models": ["voyage-multilingual-2", "text-embedding-3-large"], "ip": "", "0_conv_id": "fdbaddd493b84cc89357c4480e2d727d", "0_model_name": "voyage-multilingual-2", "0_prompt": "The effect of Long pimple ", "0_output": [["The effect of Long pimple ", "Pimple\n\nA pimple or zit is a kind of comedo that results from excess sebum and dead skin cells getting trapped in the pores of the skin. In its aggravated state, it may evolve into a pustule or papule. Pimples can be treated by acne medications, antibiotics, and anti-inflammatories prescribed by a physician, or various over the counter remedies purchased at a pharmacy.\nCauses\nSebaceous glands inside the pore of the skin produce sebum. When the outer layers of skin shed (a natural and continuous process, normally), dead skin and oily sebum left behind may bond together and form a blockage of the sebaceous gland at the base of the skin. This is most common when the skin becomes thicker at puberty. The sebaceous gland continues to produce sebum, which builds up behind the blockage, allowing bacteria to grow in the area, including the species Staphylococcus aureus and Cutibacterium acnes, which causes inflammation and infection. Other causes of pimples include family history, stress, fluctuations in hormone levels, hair and skincare products, medication side effects, and un-diagnosed or underlying medical conditions. Pimples can be part of the presentation of rosacea."]], "0_corpus": "wikipedia", "1_conv_id": "86047e9633f3430da6d888564b950f65", "1_model_name": "text-embedding-3-large", "1_prompt": "The effect of Long pimple ", "1_output": [["The effect of Long pimple ", "Table tennis grips and playing styles\n\nShort pips hitter This penhold style utilizes a short pips out rubber, usually on only one side of the racket with no backside rubber. Short pips hitters play over the table, hitting the ball very flatly as soon as it bounces off the table with the pips being largely unaffected by (or even negating) the majority of the opponent's spin. The advantage of hitting the ball flatly is that all of the player's power is transferred into the linear velocity of the ball, without expending any energy on creating spin. This means that the shots are very fast, and typically hard to block for the inexperienced player. However, the lack of a topspin Magnus effect means that the shots are harder to place on the table since they don't follow a downward arc trajectory, and the lack of angular momentum on the ball means that shots are less consistent and more sensitive to small amounts of wind or air pressure, often giving a knuckle ball effect.\nNotable penhold short pips hitters include 1996 Olympic Champion Liu Guoliang, 1985 and 1987 World Champion Jiang Jialiang, three-time Olympian Toshio Tasaki, Yang Ying, Kwak Bang-bang, Seok Eun-mi, He Zhi Wen, Lee Eun-hee, Wang Zeng Yi and Rory Cargill.\nShakehand playing styles"]], "1_corpus": "wikipedia"}
+{"tstamp": 1722311047.6413, "task_type": "retrieval", "type": "tievote", "models": ["voyage-multilingual-2", "text-embedding-004"], "ip": "", "0_conv_id": "8472d85456e841798101c9a3e9d1d29a", "0_model_name": "voyage-multilingual-2", "0_prompt": "can I do multithreading with fastapi", "0_output": [["can I do multithreading with fastapi", "FastAPI\n\nFastAPI is a modern web framework first released in 2018 for building HTTP-based service APIs in Python. It is used for building APIs with Python 3.8+ based on standard Python-type hints.\nFastAPI is based on Pydantic and uses type hints to validate, serialize and deserialize data. It also automatically generates OpenAPI documentation for APIs built with it.\nComponents\nPydantic\nPydantic is a data validation library for Python. While writing code in an IDE, Pydantic provides type hints for schema validation and serialization through type annotations.\nStarlette\nStarlette is a lightweight ASGI framework/toolkit, to support async functionality in Python.\nUvicorn\nUvicorn is a minimal low-level server/application web server for async frameworks, following the ASGI specification. Technically, it implements a multi-process model with one main process, which is responsible for managing a pool of worker processes and distributing incoming HTTP requests to them. The number of worker processes is pre-configured, but can also be adjusted up or down at runtime.\nExample\nThe following code shows a simple web application that displays \"Hello World!\" when visited:\nfrom fastapi import FastAPI\napp = FastAPI()\n@app.get(\"/\")\ndef read_root():"]], "0_corpus": "wikipedia", "1_conv_id": "b987e3526f4e4c9fbea6f0eae988d918", "1_model_name": "text-embedding-004", "1_prompt": "can I do multithreading with fastapi", "1_output": [["can I do multithreading with fastapi", "FastAPI\n\nFastAPI is a modern web framework first released in 2018 for building HTTP-based service APIs in Python. It is used for building APIs with Python 3.8+ based on standard Python-type hints.\nFastAPI is based on Pydantic and uses type hints to validate, serialize and deserialize data. It also automatically generates OpenAPI documentation for APIs built with it.\nComponents\nPydantic\nPydantic is a data validation library for Python. While writing code in an IDE, Pydantic provides type hints for schema validation and serialization through type annotations.\nStarlette\nStarlette is a lightweight ASGI framework/toolkit, to support async functionality in Python.\nUvicorn\nUvicorn is a minimal low-level server/application web server for async frameworks, following the ASGI specification. Technically, it implements a multi-process model with one main process, which is responsible for managing a pool of worker processes and distributing incoming HTTP requests to them. The number of worker processes is pre-configured, but can also be adjusted up or down at runtime.\nExample\nThe following code shows a simple web application that displays \"Hello World!\" when visited:\nfrom fastapi import FastAPI\napp = FastAPI()\n@app.get(\"/\")\ndef read_root():"]], "1_corpus": "wikipedia"}