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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 83 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 147 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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Collections including paper arxiv:2408.11796
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 147 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 13 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 56 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 47
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DocGraphLM: Documental Graph Language Model for Information Extraction
Paper • 2401.02823 • Published • 36 -
Understanding LLMs: A Comprehensive Overview from Training to Inference
Paper • 2401.02038 • Published • 64 -
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 180 -
Attention Where It Matters: Rethinking Visual Document Understanding with Selective Region Concentration
Paper • 2309.01131 • Published • 1
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Chain-of-Verification Reduces Hallucination in Large Language Models
Paper • 2309.11495 • Published • 38 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77 -
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
Paper • 2309.09400 • Published • 85 -
Language Modeling Is Compression
Paper • 2309.10668 • Published • 83