CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
Paper
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2309.09400
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Published
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77
LLMs
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PDFTriage: Question Answering over Long, Structured Documents
Paper • 2309.08872 • Published • 51 -
Chain-of-Verification Reduces Hallucination in Large Language Models
Paper • 2309.11495 • Published • 37 -
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Paper • 2309.12307 • Published • 82 -
SCREWS: A Modular Framework for Reasoning with Revisions
Paper • 2309.13075 • Published • 15 -
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models
Paper • 2309.14509 • Published • 16 -
Qwen Technical Report
Paper • 2309.16609 • Published • 30 -
From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
Paper • 2309.04269 • Published • 28 -
In-Context Pretraining: Language Modeling Beyond Document Boundaries
Paper • 2310.10638 • Published • 26 -
Can LLMs Follow Simple Rules?
Paper • 2311.04235 • Published • 9 -
Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs
Paper • 2311.05657 • Published • 26 -
Lost in the Middle: How Language Models Use Long Contexts
Paper • 2307.03172 • Published • 31 -
Challenges and Applications of Large Language Models
Paper • 2307.10169 • Published • 46 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 37 -
GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 170 -
SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention
Paper • 2312.07987 • Published • 39 -
Mixtral of Experts
Paper • 2401.04088 • Published • 152 -
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
Paper • 2401.16380 • Published • 45 -
Generative Representational Instruction Tuning
Paper • 2402.09906 • Published • 50 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 58 -
Can large language models explore in-context?
Paper • 2403.15371 • Published • 30 -
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
Paper • 2404.07143 • Published • 90 -
Rho-1: Not All Tokens Are What You Need
Paper • 2404.07965 • Published • 78