Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs
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2503.01307
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30
Active Reasoning
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Asap7772
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CohenQu
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aviralku
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Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models
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2310.10639
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3
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Unfamiliar Finetuning Examples Control How Language Models Hallucinate
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3
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
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1
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold
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3
Generative Verifiers: Reward Modeling as Next-Token Prediction
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Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning
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Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance
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2
Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data
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Published
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
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Value-Based Deep RL Scales Predictably
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6
Asap7772
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CohenQu
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