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 Advances in Neural Information Processing Systems , volume=

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

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

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

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Reference 62

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Reference 63

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Observation 09f95b76-65fa-442f-af2a-decc09c41a21 · outbound

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Reference 74

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Observation f904c68f-6879-4859-8ce7-4640b3670e3c · outbound

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment

Reference 75

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Observation 5ef0411b-074d-420d-b9bb-4b3e3314c8c2 · outbound

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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

Reference 76

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Observation 90036455-6a28-4aa9-8e78-d0208b1910d2 · outbound

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Observation dcdda4da-491a-432d-a3a1-4b8f546c4c3d · outbound

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Observation d8724f47-7509-4199-9099-2e2d18c147e5 · outbound

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Findings of the Association for Computational Linguistics: NAACL 2025 , pages=

Reference 79

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

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

Reference 80

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Observation 283518ca-0f74-43ac-9f73-68e4f8110187 · outbound

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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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Observation 81a4ea9b-7e5b-4972-8c5a-333a96a32c0f · outbound

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Reference 83

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Observation 8f68f78d-087d-498d-8e1d-b1b9609f78ce · outbound

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Reference 84

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Observation 2c52bc28-2c74-4fa0-9f45-d1f6cf46fb42 · outbound

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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

Reference 86

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Observation 8d7d7669-d088-4acb-b031-e45a426084a8 · outbound

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Reference 87

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Reference 88

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Reference 89

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Reference 90

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Observation c9157bab-d55e-46d8-972f-18644528a140 · outbound

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SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation The method of paired comparisons , author=

Reference 91

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Reference 92

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Reference 93

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Reference 94

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Reference 95

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

Reference 96

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Reference 97

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Reference 98

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Reference 99

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Reference 100

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Pith citing papers