Self-Rewarding Language Models
Paper
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2401.10020
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Published
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145
Synthetic Data and Self-Improvement
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Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 114 -
OS-Copilot: Towards Generalist Computer Agents with Self-Improvement
Paper • 2402.07456 • Published • 42 -
Learning From Mistakes Makes LLM Better Reasoner
Paper • 2310.20689 • Published • 28 -
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 29 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 60 -
ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline
Paper • 2404.02893 • Published • 20 -
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 • 4 -
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
Paper • 2404.18796 • Published • 68 -
Extending Llama-3's Context Ten-Fold Overnight
Paper • 2404.19553 • Published • 33 -
Diffusion for World Modeling: Visual Details Matter in Atari
Paper • 2405.12399 • Published • 28 -
Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models
Paper • 2405.20541 • Published • 22 -
ShareGPT4Video: Improving Video Understanding and Generation with Better Captions
Paper • 2406.04325 • Published • 73 -
Depth Anything V2
Paper • 2406.09414 • Published • 95 -
Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Paper • 2406.08464 • Published • 66 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 97 -
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning
Paper • 2407.20798 • Published • 24 -
Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers
Paper • 2408.06195 • Published • 64 -
Data curation via joint example selection further accelerates multimodal learning
Paper • 2406.17711 • Published • 3 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 136 -
Thinking LLMs: General Instruction Following with Thought Generation
Paper • 2410.10630 • Published • 18 -
How to Synthesize Text Data without Model Collapse?
Paper • 2412.14689 • Published • 48 -
Euclid: Supercharging Multimodal LLMs with Synthetic High-Fidelity Visual Descriptions
Paper • 2412.08737 • Published • 52 -
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis
Paper • 2412.19723 • Published • 70 -
ProgCo: Program Helps Self-Correction of Large Language Models
Paper • 2501.01264 • Published • 23 -
Training Software Engineering Agents and Verifiers with SWE-Gym
Paper • 2412.21139 • Published • 16 -
RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response
Paper • 2412.14922 • Published • 84 -
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
Paper • 2412.17256 • Published • 44 -
Diving into Self-Evolving Training for Multimodal Reasoning
Paper • 2412.17451 • Published • 41 -
OpenAI o1 System Card
Paper • 2412.16720 • Published • 29 -
ResearchTown: Simulator of Human Research Community
Paper • 2412.17767 • Published • 12 -
SPaR: Self-Play with Tree-Search Refinement to Improve Instruction-Following in Large Language Models
Paper • 2412.11605 • Published • 16 -
AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials
Paper • 2412.09605 • Published • 26 -
Evaluating Language Models as Synthetic Data Generators
Paper • 2412.03679 • Published • 46 -
SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation
Paper • 2411.11053 • Published • 3 -
CodeDPO: Aligning Code Models with Self Generated and Verified Source Code
Paper • 2410.05605 • Published • 1 -
Enhancing LLM Reasoning via Critique Models with Test-Time and Training-Time Supervision
Paper • 2411.16579 • Published • 2 -
Vision-Language Models Can Self-Improve Reasoning via Reflection
Paper • 2411.00855 • Published • 5 -
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Paper • 2411.04282 • Published • 32 -
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
Paper • 2411.14432 • Published • 22 -
Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning
Paper • 2411.18203 • Published • 33 -
From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge
Paper • 2411.16594 • Published • 37 -
LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning
Paper • 2410.02884 • Published • 53 -
Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents
Paper • 2411.06559 • Published • 12 -
Generative World Explorer
Paper • 2411.11844 • Published • 75 -
Large Language Models Can Self-Improve in Long-context Reasoning
Paper • 2411.08147 • Published • 63 -
Stronger Models are NOT Stronger Teachers for Instruction Tuning
Paper • 2411.07133 • Published • 35 -
BLIP3-KALE: Knowledge Augmented Large-Scale Dense Captions
Paper • 2411.07461 • Published • 22 -
Self-Consistency Preference Optimization
Paper • 2411.04109 • Published • 17