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Collections including paper arxiv:2406.17557

Papers I want to read

Papers in my to-read list

RLHF Workflow: From Reward Modeling to Online RLHF

Paper • 2405.07863 • Published May 13 • 67
Chameleon: Mixed-Modal Early-Fusion Foundation Models

Paper • 2405.09818 • Published May 16 • 126
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24 • 53
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 85

PDFTriage: Question Answering over Long, Structured Documents

Paper • 2309.08872 • Published Sep 16, 2023 • 53
Adapting Large Language Models via Reading Comprehension

Paper • 2309.09530 • Published Sep 18, 2023 • 77
Table-GPT: Table-tuned GPT for Diverse Table Tasks

Paper • 2310.09263 • Published Oct 13, 2023 • 39
Context-Aware Meta-Learning

Paper • 2310.10971 • Published Oct 17, 2023 • 16

The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Paper • 2406.17557 • Published Jun 25 • 86
LiveBench: A Challenging, Contamination-Free LLM Benchmark

Paper • 2406.19314 • Published Jun 27 • 19

The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Paper • 2406.17557 • Published Jun 25 • 86
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Paper • 2406.16860 • Published Jun 24 • 57
Arboretum: A Large Multimodal Dataset Enabling AI for Biodiversity

Paper • 2406.17720 • Published Jun 25 • 7
Scaling Synthetic Data Creation with 1,000,000,000 Personas

Paper • 2406.20094 • Published Jun 28 • 94

OMG-LLaVA: Bridging Image-level, Object-level, Pixel-level Reasoning and Understanding

Paper • 2406.19389 • Published Jun 27 • 51
The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Paper • 2406.17557 • Published Jun 25 • 86
RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs

Paper • 2407.02485 • Published Jul 2 • 5
Summary of a Haystack: A Challenge to Long-Context LLMs and RAG Systems

Paper • 2407.01370 • Published Jul 1 • 85

The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Paper • 2406.17557 • Published Jun 25 • 86

DS' Daily paper

Instruction Pre-Training: Language Models are Supervised Multitask Learners

Paper • 2406.14491 • Published Jun 20 • 85
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Paper • 2405.21060 • Published May 31 • 63
Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models

Paper • 2405.20541 • Published May 30 • 20
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Paper • 2406.01574 • Published Jun 3 • 42

Large Language Model Unlearning via Embedding-Corrupted Prompts

Paper • 2406.07933 • Published Jun 12 • 7
Block Transformer: Global-to-Local Language Modeling for Fast Inference

Paper • 2406.02657 • Published Jun 4 • 36
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning

Paper • 2406.12050 • Published Jun 17 • 18
How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Paper • 2406.11813 • Published Jun 17 • 30

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Paper • 2405.04434 • Published May 7 • 13
The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Paper • 2406.17557 • Published Jun 25 • 86
DataComp-LM: In search of the next generation of training sets for language models

Paper • 2406.11794 • Published Jun 17 • 48
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Paper • 2402.14905 • Published Feb 22 • 126

WildChat: 1M ChatGPT Interaction Logs in the Wild

Paper • 2405.01470 • Published May 2 • 59
The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Paper • 2406.17557 • Published Jun 25 • 86

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