Collections
Discover the best community collections!
Collections including paper arxiv:2601.08584
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 153 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 60 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 53 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
-
LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 60 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 53 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 153 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25