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- ---
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- dataset_info:
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- features:
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- - name: label
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- dtype: string
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- - name: prompts
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- list:
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- - name: text
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- dtype: string
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- - name: prompt_templates
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- sequence: string
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- - name: id
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- dtype: string
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- - name: metadata
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- struct:
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- - name: language
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- dtype: string
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- splits:
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- - name: id
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- num_bytes: 728212
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- num_examples: 1000
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- - name: id_fewshot
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- num_bytes: 780
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- num_examples: 5
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- - name: th
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- num_bytes: 1356637
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- num_examples: 1000
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- - name: th_fewshot
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- num_bytes: 983
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- num_examples: 5
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- - name: vi
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- num_bytes: 699612
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- num_examples: 1000
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- - name: vi_fewshot
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- num_bytes: 584
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- num_examples: 5
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- download_size: 283080
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- dataset_size: 2786808
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- configs:
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- - config_name: default
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- data_files:
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- - split: id
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- path: data/id-*
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- - split: id_fewshot
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- path: data/id_fewshot-*
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- - split: th
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- path: data/th-*
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- - split: th_fewshot
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- path: data/th_fewshot-*
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- - split: vi
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- path: data/vi-*
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- - split: vi_fewshot
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- path: data/vi_fewshot-*
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ pretty_name: SEA Toxicity Detection
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+ license:
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+ - cc-by-nc-sa-4.0
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+ - cc-by-nc-3.0
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+ - cc-by-nc-4.0
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+ task_categories:
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+ - text-generation
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+ - text-classification
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+ language:
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+ - id
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+ - th
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+ - vi
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+ dataset_info:
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+ features:
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+ - name: label
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+ dtype: string
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+ - name: prompts
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+ list:
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+ - name: text
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+ dtype: string
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+ - name: prompt_templates
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+ sequence: string
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+ - name: id
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+ dtype: string
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+ - name: metadata
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+ struct:
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+ - name: language
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+ dtype: string
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+ splits:
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+ - name: id
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+ num_bytes: 728212
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+ num_examples: 1000
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+ num_tokens_gpt_4o: 34416
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+ num_tokens_gemma_2: 34238
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+ num_tokens_llama_3: 40537
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+ - name: id_fewshot
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+ num_bytes: 780
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+ num_examples: 5
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+ num_tokens_gpt_4o: 183
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+ num_tokens_gemma_2: 174
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+ num_tokens_llama_3: 216
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+ - name: th
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+ num_bytes: 1356637
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+ num_examples: 1000
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+ num_tokens_gpt_4o: 38189
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+ num_tokens_gemma_2: 35980
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+ num_tokens_llama_3: 42901
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+ - name: th_fewshot
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+ num_bytes: 983
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+ num_examples: 5
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+ num_tokens_gpt_4o: 130
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+ num_tokens_gemma_2: 121
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+ num_tokens_llama_3: 150
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+ - name: vi
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+ num_bytes: 699612
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+ num_examples: 1000
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+ num_tokens_gpt_4o: 17540
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+ num_tokens_gemma_2: 16904
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+ num_tokens_llama_3: 18287
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+ - name: vi_fewshot
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+ num_bytes: 584
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+ num_examples: 5
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+ num_tokens_gpt_4o: 104
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+ num_tokens_gemma_2: 97
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+ num_tokens_llama_3: 104
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+ download_size: 283080
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+ dataset_size: 2786808
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+ total_tokens_gpt_4o: 90562
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+ total_tokens_gemma_2: 87514
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+ total_tokens_llama_3: 102195
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: id
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+ path: data/id-*
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+ - split: id_fewshot
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+ path: data/id_fewshot-*
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+ - split: th
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+ path: data/th-*
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+ - split: th_fewshot
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+ path: data/th_fewshot-*
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+ - split: vi
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+ path: data/vi-*
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+ - split: vi_fewshot
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+ path: data/vi_fewshot-*
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+ size_categories:
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+ - 1K<n<10K
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+ ---
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+
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+ # SEA Toxicity Detection
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+ SEA Toxicity Detection evaluates a model's ability to identify toxic content such as hate speech and abusive language in text. It is sampled from [MLHSD](https://aclanthology.org/W19-3506/) for Indonesian, [TTD](http://lrec-conf.org/workshops/lrec2018/W32/pdf/1_W32.pdf) for Thai, and [ViHSD](https://link.springer.com/chapter/10.1007/978-3-030-79457-6_35) for Vietnamese.
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+
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+ ### Supported Tasks and Leaderboards
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+ SEA Toxicity Detection is designed for evaluating chat or instruction-tuned large language models (LLMs). It is part of the [SEA-HELM](https://leaderboard.sea-lion.ai/) leaderboard from [AI Singapore](https://aisingapore.org/).
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+
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+ ### Languages
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+ - Indonesian (id)
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+ - Thai (th)
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+ - Vietnamese (vi)
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+
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+ ### Dataset Details
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+ SEA Toxicity Detection is split by language, with additional splits containing fewshot examples. Below are the statistics for this dataset. The number of tokens only refer to the strings of text found within the `prompts` column.
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+
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+ | Split | # of examples | # of GPT-4o tokens | # of Gemma 2 tokens | # of Llama 3 tokens |
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+ |-|:-|:-|:-|:-|
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+ | id | 1000 | 34416 | 34238 | 40537
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+ | th | 1000 | 38189 | 35980 | 42901
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+ | vi | 1000 | 17540 | 16904 | 18287
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+ | id_fewshot | 5 | 183 | 174 | 216
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+ | th_fewshot | 5 | 130 | 121 | 150
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+ | vi_fewshot | 5 | 104 | 97 | 104
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+ | **total** | 3015 | 90562 | 87514 | 102195 |
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+
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+ ### Data Sources
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+
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+ | Data Source | License | Language/s | Split/s
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+ |-|:-|:-| :-|
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+ | [MLHSD](https://github.com/okkyibrohim/id-multi-label-hate-speech-and-abusive-language-detection) | [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) | Indonesian | id, id_fewshot
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+ | [TTD](https://huggingface.co/datasets/tmu-nlp/thai_toxicity_tweet) | [CC BY-NC 3.0](https://creativecommons.org/licenses/by-nc/3.0/) | Thai |th, th_fewshot
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+ | [ViHSD](https://github.com/sonlam1102/vihsd) | [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) | Vietnamese | vi, vi_fewshot
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+
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+ ### License
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+
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+ For the license/s of the dataset/s, please refer to the data sources table above.
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+
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+ We endeavor to ensure data used is permissible and have chosen datasets from creators who have processes to exclude copyrighted or disputed data.
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+
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+
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+ ### References
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+
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+ ```bibtex
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+ @inproceedings{ibrohim-budi-2019-multi,
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+ title = "Multi-label Hate Speech and Abusive Language Detection in {I}ndonesian {T}witter",
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+ author = "Ibrohim, Muhammad Okky and
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+ Budi, Indra",
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+ editor = "Roberts, Sarah T. and
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+ Tetreault, Joel and
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+ Prabhakaran, Vinodkumar and
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+ Waseem, Zeerak",
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+ booktitle = "Proceedings of the Third Workshop on Abusive Language Online",
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+ month = aug,
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+ year = "2019",
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+ address = "Florence, Italy",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/W19-3506",
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+ doi = "10.18653/v1/W19-3506",
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+ pages = "46--57",
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+ }
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+
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+ @inproceedings{sirihattasak2018annotation,
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+ title={Annotation and classification of toxicity for Thai Twitter},
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+ author={Sirihattasak, Sugan and Komachi, Mamoru and Ishikawa, Hiroshi},
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+ booktitle={TA-COS 2018: 2nd Workshop on Text Analytics for Cybersecurity and Online Safety},
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+ pages={1},
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+ year={2018}
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+ }
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+
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+ @InProceedings{10.1007/978-3-030-79457-6_35,
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+ author="Luu, Son T.
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+ and Nguyen, Kiet Van
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+ and Nguyen, Ngan Luu-Thuy",
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+ editor="Fujita, Hamido
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+ and Selamat, Ali
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+ and Lin, Jerry Chun-Wei
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+ and Ali, Moonis",
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+ title="A Large-Scale Dataset for Hate Speech Detection on Vietnamese Social Media Texts",
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+ booktitle="Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices",
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+ year="2021",
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+ publisher="Springer International Publishing",
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+ address="Cham",
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+ pages="415--426",
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+ isbn="978-3-030-79457-6"
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+ }
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+
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+ @misc{leong2023bhasaholisticsoutheastasian,
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+ title={BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models},
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+ author={Wei Qi Leong and Jian Gang Ngui and Yosephine Susanto and Hamsawardhini Rengarajan and Kengatharaiyer Sarveswaran and William Chandra Tjhi},
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+ year={2023},
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+ eprint={2309.06085},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2309.06085},
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+ }
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+ ```