SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation | Paper Citation Record

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Approximating

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Thinking Machines Lab: Connectionism , year=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2017 , eprint=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Advances in Neural Information Processing Systems , volume=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Advances in Neural Information Processing Systems , volume=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Advances in Neural Information Processing Systems , volume=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation NIPS Deep Learning and Representation Learning Workshop , year=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation International Conference on Learning Representations (ICLR) , year=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Unresolved cited work

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Unresolved cited work

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2026 , eprint=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation MOPD: Multi-Teacher On-Policy Distillation for Capability Integration in LLM Post-Training

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Unresolved cited work

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Language Models are Super

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation International Conference on Learning Representations (ICLR) , year=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Proceedings of the 39th International Conference on Machine Learning (ICML) , year=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Constitutional AI: Harmlessness from AI Feedback

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Unresolved cited work

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2022 , eprint=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Hashimoto , year=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Arithmetic Control of

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Rewarded soups: towards

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Unresolved cited work

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Back to Basics: Revisiting

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2025 , eprint=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2606.16771 , archivePrefix=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Advances in Neural Information Processing Systems , volume=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2024 , eprint=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Gonzalez and Hao Zhang and Ion Stoica , booktitle=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Patil and Tianjun Zhang and Xin Wang and Joseph E

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Findings of the Association for Computational Linguistics: EMNLP 2024 , pages=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation SAW: Stage-Aware Dynamic Weighting for Multi-Objective Reinforcement Learning in Large Language Models

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation The Perfect Blend: Redefining RLHF with Mixture of Judges

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation International Conference on Learning Representations (ICLR) , year=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation WARP: On the Benefits of Weight Averaged Rewarded Policies

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Singh and DJ Strouse and Tuomas Sandholm and Ruslan Salakhutdinov and Anca D

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Advances in Neural Information Processing Systems , volume=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2025 , doi=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Measuring Mathematical Problem Solving With the

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Advances in Neural Information Processing Systems , volume=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation International Conference on Machine Learning , pages=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics , pages=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2026 , eprint=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2024 , eprint=

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Findings of the association for computational linguistics: EMNLP 2024 , pages=

Reference 60

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Everyone Deserves A Reward: Learning Customized Human Preferences

Reference 61

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Observation 17f84292-f9a6-42c0-938a-43315dd4d88a · outbound

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Reference 63

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Reference 75

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Loose lips sink ships: Mitigating Length Bias in Reinforcement Learning from Human Feedback

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Reference 79

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Observation 783e67f2-7ba2-4956-96bd-cd9d5f43d6f6 · outbound

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Reference 80

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation GPT-4o System Card

Reference 81

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Reference 82

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts

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Reference 88

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Reference 89

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Reference 91

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Reference 92

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Reference 93

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Reference 94

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Instruction Tuning with GPT-4

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Reference 100

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