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

Observation b44c3712-e4fb-4d25-b042-b058b40d0c96 · outbound

This paper cites Approximating.

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

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.692427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d978763-eb09-4404-ac3a-ea6d751c60d3 · outbound

This paper cites Thinking Machines Lab: Connectionism , year=.

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

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.697244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bc3d340-d0ad-46f6-886e-05ad422f23b4 · outbound

This paper cites GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization.

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

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.701026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f930e07-0f31-4a88-86bd-77b11984480b · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

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

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.705018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60b9bebc-e6c2-4376-a935-351d30f38d02 · outbound

This paper cites 2017 , eprint=.

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

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.708487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4b0f2f6-ed7b-432d-b120-1e6766403ba6 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

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

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.711697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be70df40-b56d-4ea7-a077-17a1b2023331 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

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

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.715648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0787fa9-408b-4eb8-9531-1affac13a384 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

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

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.719267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a31bca12-0bbb-4470-bd94-c9265e587d90 · outbound

This paper cites NIPS Deep Learning and Representation Learning Workshop , year=.

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

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.722363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c332071-41cd-4d27-a618-1b40ac4a1c61 · outbound

This paper cites International Conference on Learning Representations (ICLR) , year=.

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

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.725125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66007b7a-c580-4046-af05-70c4019a05ec · outbound

This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=.

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

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.728125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e772e42-ca45-4703-972f-f65ccf585771 · outbound

This paper cites an unresolved cited work.

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

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.731053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58fb0731-3699-499a-973e-7019f2ddc652 · outbound

This paper cites Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages=.

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=

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.734494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 301e8b44-978d-47bb-8ef6-e89e0d9de9b6 · outbound

This paper cites an unresolved cited work.

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

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.737879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea2d3af1-68aa-4862-81bf-184310a1320e · outbound

This paper cites 2026 , eprint=.

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

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.740548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bffd4d0-e002-4b5a-8291-bc548fcdbf54 · outbound

This paper cites MOPD: Multi-Teacher On-Policy Distillation for Capability Integration in LLM Post-Training.

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

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.744202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e160db9-9907-4243-9747-5cd4c6284f54 · outbound

This paper cites an unresolved cited work.

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

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.748401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9981f875-77c8-4e0f-a65f-c41b1036962d · outbound

This paper cites Language Models are Super.

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

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.751873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8609371-1e60-447a-afec-bf88a774d8f6 · outbound

This paper cites International Conference on Learning Representations (ICLR) , year=.

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

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.755666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1c3a387-c06f-4e35-98e1-48f32b788dae · outbound

This paper cites Proceedings of the 39th International Conference on Machine Learning (ICML) , year=.

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

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.759548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bb26a02-3136-4743-be38-7b335f5a47f4 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

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

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.762569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e55ff134-a8c9-4fef-be53-5822847b22cf · outbound

This paper cites an unresolved cited work.

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

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.765987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f469fe5c-7c2f-4362-a77f-f9cb0ec5a8f0 · outbound

This paper cites 2022 , eprint=.

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

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.769326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a04f551-0c78-48aa-bcd0-2e3b1650c66a · outbound

This paper cites Hashimoto , year=.

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

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.772522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a5ba99a-6b97-4694-a945-a9535aee84ac · outbound

This paper cites Arithmetic Control of.

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

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.775564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c6e0cdb-3ef0-409f-b06d-7d3837124cd8 · outbound

This paper cites Rewarded soups: towards.

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

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.779097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5911d5ed-af19-4c20-99d2-f54f52ae8c3a · outbound

This paper cites an unresolved cited work.

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

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.782265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55315f55-352e-45fb-92d4-c8072d293dd1 · outbound

This paper cites Back to Basics: Revisiting.

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

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.785597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e845bf90-36b6-4458-8001-5b3997453d2c · outbound

This paper cites 2025 , eprint=.

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

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.788532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f21dcfbf-6f20-4b6c-b3b0-a49a4d561e47 · outbound

This paper cites 2606.16771 , archivePrefix=.

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

Reference 30

Resolution: verified exact; raw_fallback, observed 2026-08-15T14:57:54.687922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a56a4a33-f71d-4464-8afd-e78f8f8071ad · outbound

This paper cites DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning.

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

Reference 31

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T14:57:54.634427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 947a9e8c-6c31-4e97-b98e-94b3b52ea8b0 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

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

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.799215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56257440-42c7-4d8e-8768-c59fd0c926f5 · outbound

This paper cites 2024 , eprint=.

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

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.802430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60362f9e-c83b-4f2e-b4c4-f50e93c95758 · outbound

This paper cites 2024 , eprint=.

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

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.806791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1355564d-ac98-4810-a57f-0b906cb5eace · outbound

This paper cites Gonzalez and Hao Zhang and Ion Stoica , booktitle=.

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

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.809737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dab2f60-a705-448b-a87e-589b931b20b9 · outbound

This paper cites an unresolved cited work.

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

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.813058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3971191-ef85-4ff8-b1c6-f11cee07edff · outbound

This paper cites Patil and Tianjun Zhang and Xin Wang and Joseph E.

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

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.816389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb7f4ffe-1f1a-4a0c-9444-fbd9de0231a0 · outbound

This paper cites an unresolved cited work.

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

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.820297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d237aab3-d2f0-45e2-8d98-a83959f16682 · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2024 , pages=.

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

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.823262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9c73846-1a10-4f50-9319-e3fb17d0e450 · outbound

This paper cites SAW: Stage-Aware Dynamic Weighting for Multi-Objective Reinforcement Learning in Large Language Models.

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

Reference 40

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T14:57:54.619457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5f1707d8-0451-4278-be2d-ea5f5f65f148 · outbound

This paper cites The Perfect Blend: Redefining RLHF with Mixture of Judges.

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

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.831378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7100e852-0073-42bc-9aef-0a21d22ff9ef · outbound

This paper cites International Conference on Learning Representations (ICLR) , year=.

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

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.836395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 458571d0-4753-49b3-bc5e-b90ebef85fe3 · outbound

This paper cites WARP: On the Benefits of Weight Averaged Rewarded Policies.

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

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.839991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b74d5406-0524-46d2-8a75-34d0a3b1ce8c · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2024 , year=.

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

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.843008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52d38c34-105f-4271-84ec-e8728d765d87 · outbound

This paper cites Singh and DJ Strouse and Tuomas Sandholm and Ruslan Salakhutdinov and Anca D.

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

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.846073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a920b9b-be2f-48cc-8f55-8369bda27d7d · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

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

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.848979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42b17cf8-95dd-4af2-a4f0-cf5d12562fa7 · outbound

This paper cites 2025 , doi=.

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

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.851928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 910b124d-5a82-4792-b21f-92dba7479cf3 · outbound

This paper cites 2021 , eprint=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2021 , eprint=

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.855105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b66bf340-d024-4cef-9b55-5130159e6940 · outbound

This paper cites Measuring Mathematical Problem Solving With the.

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

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.858442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d649c44-756f-4c84-8759-1a43d032246e · outbound

This paper cites 2019 , eprint=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2019 , eprint=

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.861265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 739164c7-0b3f-434f-b1dd-9d7647fb01c4 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

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

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.864101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 933ed797-10b5-4678-bba9-08d2b4935b00 · outbound

This paper cites International Conference on Machine Learning , pages=.

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

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.867436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c6525fa-6a6e-43e7-b798-c2b3bd17038b · outbound

This paper cites Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics , pages=.

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=

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.871011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53692ec1-9980-46a6-ac36-d69d18c923d9 · outbound

This paper cites 2026 , eprint=.

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

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.875132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc3c0ad2-cb95-434c-b0b0-3abcff808756 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

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

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.878335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1506ac23-0a71-46b5-a02c-d10d8f928cfd · outbound

This paper cites an unresolved cited work.

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

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.882201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d606a231-f2ae-4509-8597-e32f247ea1ee · outbound

This paper cites Gonzalez and Ion Stoica , booktitle=.

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

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.885627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2370deaa-773b-479e-b087-935cb248bd00 · outbound

This paper cites Machine Learning , volume=.

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

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.889122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4003c66c-0810-457c-b427-a3be5aa1dc7d · outbound

This paper cites 2024 , eprint=.

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

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.892306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96673f63-9191-467a-80d1-a86c82d45f75 · outbound

This paper cites Findings of the association for computational linguistics: EMNLP 2024 , pages=.

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

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.895395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb436b5f-bffc-44f3-8219-b28e115e373f · outbound

This paper cites Everyone Deserves A Reward: Learning Customized Human Preferences.

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

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.898499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Kimi-VL Technical Report.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Kimi-VL Technical Report

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.902060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c547009-05c7-4ae9-8842-3864d34f42c6 · outbound

This paper cites Advances in neural information processing systems , volume=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Advances in neural information processing systems , volume=

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.905649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7d3048e-1d8c-4e85-be5b-7b2308f1e963 · outbound

This paper cites 2024 , eprint=.

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

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.909368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37c9e7be-5e37-4de4-a6ae-018e2e77da91 · outbound

This paper cites 2000 , eprint=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2000 , eprint=

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.912159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed62110f-f4e8-4f0a-8f43-9a5398d88936 · outbound

This paper cites 1997 , publisher=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 1997 , publisher=

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.916002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a830bc8-5b09-4916-afbd-fc7199199291 · outbound

This paper cites International conference on machine learning , pages=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation International conference on machine learning , pages=

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.919633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74fe22e8-2260-483f-be44-6ee4dc7feb15 · outbound

This paper cites International conference on machine learning , pages=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation International conference on machine learning , pages=

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.922992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff4ac2d3-d624-4216-bc39-52052533cbe1 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Representation Learning with Contrastive Predictive Coding

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.926780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8595768-a948-4f78-a4aa-69e7e79a006a · outbound

This paper cites 2019 , eprint=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2019 , eprint=

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.930464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b0a12de-5c06-49c9-b42c-d1066999ad54 · outbound

This paper cites International conference on machine learning , pages=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation International conference on machine learning , pages=

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.933734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efceb99c-e966-482d-88be-1bee64ba9100 · outbound

This paper cites Advances in neural information processing systems , volume=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Advances in neural information processing systems , volume=

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.937179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1911532-51fd-466a-9c76-2074d31e8c6b · outbound

This paper cites A Long Way to Go: Investigating Length Correlations in RLHF.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation A Long Way to Go: Investigating Length Correlations in RLHF

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.940237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Towards Understanding Sycophancy in Language Models.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Towards Understanding Sycophancy in Language Models

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.943369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment.

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

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.946749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Loose lips sink ships: Mitigating Length Bias in Reinforcement Learning from Human Feedback.

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

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.950455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Advances in Neural Information Processing Systems , volume=.

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

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.953858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites 2025 , eprint=.

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

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.957789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Findings of the Association for Computational Linguistics: NAACL 2025 , pages=.

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

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.961334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites an unresolved cited work.

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

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.964603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites GPT-4o System Card.

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

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.967415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6c8126d-f837-483d-947e-fbd78482a8dd · outbound

This paper cites 2022 , eprint=.

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

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.970403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites 2023 , eprint=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2023 , eprint=

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.973324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites 2024 , eprint=.

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

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.976058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd26a059-5d3c-4d27-828a-4c16ff5ba1a5 · outbound

This paper cites 2025 , eprint=.

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

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.979341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts.

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

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.982198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites 2024 , eprint=.

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

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.985088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d1257dc-eee2-430c-9915-3f920322fb5b · outbound

This paper cites 2021 , booktitle=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2021 , booktitle=

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.988450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98600c1f-5a41-4af8-ae8b-0c0c8d4267af · outbound

This paper cites 2019 , booktitle=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2019 , booktitle=

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.991165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaeff446-e299-471c-bef7-f32774ea6311 · outbound

This paper cites 2025 , eprint=.

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

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.994950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites The method of paired comparisons , author=.

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

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:53.998943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3671c0d6-78d4-49cf-9a2f-e02ec65f551a · outbound

This paper cites 2022 , eprint=.

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

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:54.001963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6db5d0e8-e58a-437c-85d2-fc3a6e5e6409 · outbound

This paper cites 2024 , eprint=.

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

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:54.005398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a3c386e-3536-4b72-9788-809f86b0f89b · outbound

This paper cites 2024 , eprint=.

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

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:54.008261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6661f9bc-b9bc-4d85-a316-01b58d24a03f · outbound

This paper cites 2024 , eprint=.

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

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:54.011160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7c4114e-0800-4c37-9b5e-fc611cca1038 · outbound

This paper cites Instruction Tuning with GPT-4.

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

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:54.014237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be4702e3-bdb3-4135-b817-af21f4a2d47a · outbound

This paper cites 2021 , eprint=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2021 , eprint=

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:54.017797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1884369b-ba39-47b9-86d7-cc2fd09e02fb · outbound

This paper cites 2017 , eprint=.

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

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:54.021547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a58c936d-b789-4294-8d0b-8761a1b6fc64 · outbound

This paper cites 2017 , eprint=.

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

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:54.024618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d8a1c50-2af2-488e-b1cd-26f9a98fee5a · outbound

This paper cites 2019 , eprint=.

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation 2019 , eprint=

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:54.027500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers