Self-Rewarding Language Models
Paper
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2401.10020
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Published
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138
Synthetic Data and Self-Improvement
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Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 107 -
OS-Copilot: Towards Generalist Computer Agents with Self-Improvement
Paper • 2402.07456 • Published • 40 -
Learning From Mistakes Makes LLM Better Reasoner
Paper • 2310.20689 • Published • 27 -
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 25 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 58 -
ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline
Paper • 2404.02893 • Published • 19 -
Voyager: An Open-Ended Embodied Agent with Large Language Models
Paper • 2305.16291 • Published • 9 -
Reflexion: Language Agents with Verbal Reinforcement Learning
Paper • 2303.11366 • Published • 3 -
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
Paper • 2404.18796 • Published • 67 -
Extending Llama-3's Context Ten-Fold Overnight
Paper • 2404.19553 • Published • 30 -
Diffusion for World Modeling: Visual Details Matter in Atari
Paper • 2405.12399 • Published • 25 -
Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models
Paper • 2405.20541 • Published • 19 -
ShareGPT4Video: Improving Video Understanding and Generation with Better Captions
Paper • 2406.04325 • Published • 69 -
Depth Anything V2
Paper • 2406.09414 • Published • 88 -
Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Paper • 2406.08464 • Published • 49 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 84