RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction | Paper Citation Record

Observation b12cabb1-843c-474d-a18d-35c787b36ab9 · outbound

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

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Advances in Neural Information Processing Systems , volume=

Reference 1

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This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 2

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This paper cites Unified Reward Model for Multimodal Understanding and Generation.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Unified Reward Model for Multimodal Understanding and Generation

Reference 3

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

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Advances in neural information processing systems , volume=

Reference 4

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This paper cites Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 5

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This paper cites WorldPM: Scaling Human Preference Modeling.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction WorldPM: Scaling Human Preference Modeling

Reference 6

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This paper cites Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 7

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This paper cites Reward is enough: Llms are in-context reinforcement learners , volume =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Reward is enough: Llms are in-context reinforcement learners , volume =

Reference 8

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Unresolved cited work

Reference 9

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This paper cites Scaling laws for neural language models , volume =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Scaling laws for neural language models , volume =

Reference 10

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This paper cites Large language models are not fair evaluators , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Large language models are not fair evaluators , year =

Reference 11

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This paper cites Theoretical and empirical evaluation of data reduction for exact Kemeny rank aggregation , volume =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Theoretical and empirical evaluation of data reduction for exact Kemeny rank aggregation , volume =

Reference 12

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

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Advances in Neural Information Processing Systems , volume=

Reference 13

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Improved parameterized algorithms for the Kemeny aggregation problem , year =

Reference 14

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Are we done with mmlu? , year =

Reference 15

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This paper cites Length-controlled alpacaeval: A simple debiasing of automatic evaluators , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Length-controlled alpacaeval: A simple debiasing of automatic evaluators , year =

Reference 16

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This paper cites Let's Verify Step by Step , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Let's Verify Step by Step , year =

Reference 17

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This paper cites Gpqa: A graduate-level google-proof q&a benchmark , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Gpqa: A graduate-level google-proof q&a benchmark , year =

Reference 18

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This paper cites From crowdsourced data to high-quality benchmarks: Arena-hard and benchbuilder pipeline , volume =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction From crowdsourced data to high-quality benchmarks: Arena-hard and benchbuilder pipeline , volume =

Reference 19

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This paper cites Wildbench: Benchmarking llms with challenging tasks from real users in the wild , volume =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Wildbench: Benchmarking llms with challenging tasks from real users in the wild , volume =

Reference 20

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This paper cites Hashimoto , howpublished =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Hashimoto , howpublished =

Reference 21

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This paper cites SimPO: Simple Preference Optimization with a Reference-Free Reward , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction SimPO: Simple Preference Optimization with a Reference-Free Reward , year =

Reference 22

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This paper cites HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages , volume =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages , volume =

Reference 23

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This paper cites Qwen2 technical report , volume =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Qwen2 technical report , volume =

Reference 24

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction The llama 3 herd of models , volume =

Reference 25

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This paper cites Rrhf: Rank responses to align language models with human feedback without tears , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Rrhf: Rank responses to align language models with human feedback without tears , year =

Reference 26

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction A computational study of the Kemeny rule for preference aggregation , year =

Reference 27

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Judgebench: A benchmark for evaluating llm-based judges , year =

Reference 28

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Rm-bench: Benchmarking reward models of language models with subtlety and style , year =

Reference 29

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Proximal policy optimization algorithms , year =

Reference 30

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Rank analysis of incomplete block designs: I

Reference 31

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Reinforcement Learning with Verifiable Rewards: GRPO's Effective Loss, Dynamics, and Success Amplification , year =

Reference 32

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Language models that think, chat better , year =

Reference 33

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Dissecting Long Reasoning Models: An Empirical Study , year =

Reference 34

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Reinforcement learning with verifiable rewards implicitly incentivizes correct reasoning in base llms , year =

Reference 35

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Reference 36

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Pre-Trained Policy Discriminators are General Reward Models , year =

Reference 37

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This paper cites Dynamic Reward Adjustment in Multi-Reward Reinforcement Learning for Counselor Reflection Generation , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Dynamic Reward Adjustment in Multi-Reward Reinforcement Learning for Counselor Reflection Generation , year =

Reference 38

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This paper cites Contrastive Preference Optimization: Pushing the Boundaries of.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Contrastive Preference Optimization: Pushing the Boundaries of

Reference 39

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction From system 1 to system 2: A survey of reasoning large language models , year =

Reference 40

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Unresolved cited work

Reference 41

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Prior constraints-based reward model training for aligning large language models , year =

Reference 42

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Improving In-Context Learning via Sequentially Selection and Preference Alignment for Few-Shot Aspect-Based Sentiment Analysis , year =

Reference 43

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This paper cites Qwen-audio: Advancing universal audio understanding via unified large-scale audio-language models , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Qwen-audio: Advancing universal audio understanding via unified large-scale audio-language models , year =

Reference 44

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Observation 38c72927-3206-40a4-98de-0a66f7aa5a28 · outbound

This paper cites Manning and Stefano Ermon and Chelsea Finn , booktitle =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Manning and Stefano Ermon and Chelsea Finn , booktitle =

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:52.126244Z

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Observation 5f6a0495-ddc0-49fa-8cfd-e859a86ded4f · outbound

This paper cites Discriminative Reranking for Neural Machine Translation , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Discriminative Reranking for Neural Machine Translation , year =

Reference 46

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Observation e4bcb13c-a52a-4763-809d-d513742ce78b · outbound

This paper cites Dapo: An open-source llm reinforcement learning system at scale , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Dapo: An open-source llm reinforcement learning system at scale , year =

Reference 47

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This paper cites Deepseekmath: Pushing the limits of mathematical reasoning in open language models , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Deepseekmath: Pushing the limits of mathematical reasoning in open language models , year =

Reference 48

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This paper cites Generative reward modeling via synthetic criteria preference learning , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Generative reward modeling via synthetic criteria preference learning , year =

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:52.077498Z

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Unified multimodal chain-of-thought reward model through reinforcement fine-tuning , year =

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:52.062854Z

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Observation d03689ab-3acf-429a-b7ab-fc5322fbf02f · outbound

This paper cites Rm-r1: Reward modeling as reasoning , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Rm-r1: Reward modeling as reasoning , year =

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:52.048217Z

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This paper cites Reward reasoning model , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Reward reasoning model , year =

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:52.033753Z

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Observation 2b9f8ed9-f566-4459-9c84-dc3dbcae46fc · outbound

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction GRAM-R ^2 : Self-Training Generative Foundation Reward Models for Reward Reasoning , year =

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:52.019979Z

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Observation fe4d15e3-bc62-408c-851f-2489c4f00019 · outbound

This paper cites GRAM: A Generative Foundation Reward Model for Reward Generalization , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction GRAM: A Generative Foundation Reward Model for Reward Generalization , year =

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:52.003423Z

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This paper cites Inference-time scaling for generalist reward modeling , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Inference-time scaling for generalist reward modeling , year =

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.988506Z

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Observation 5a571064-f449-4e59-bd29-3d741065ed9a · outbound

This paper cites Reward Model Ensembles Help Mitigate Overoptimization , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Reward Model Ensembles Help Mitigate Overoptimization , year =

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.971964Z

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Observation 8b55f41c-0c8f-4224-a776-77118909d455 · outbound

This paper cites Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy , year =

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.956432Z

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Observation 0c1242af-9be7-489e-b125-e1785b84d53a · outbound

This paper cites Rovrm: A robust visual reward model optimized via auxiliary textual preference data , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Rovrm: A robust visual reward model optimized via auxiliary textual preference data , year =

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.942367Z

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Observation b1d32292-7cd2-4a90-bbde-433e37e585c5 · outbound

This paper cites Specialist or Generalist? Instruction Tuning for Specific.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Specialist or Generalist? Instruction Tuning for Specific

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.926107Z

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Observation ea9c6137-14cb-4ddb-8dad-99dcf3f0622d · outbound

This paper cites Unveiling the Generalization Power of Fine-Tuned Large Language Models , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Unveiling the Generalization Power of Fine-Tuned Large Language Models , year =

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.911106Z

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Observation aef914da-2aac-4694-baa9-bfca318d3932 · outbound

This paper cites Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning , year =

Reference 61

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Observation 823d99c6-f758-4b11-a3bd-c88f0f608d21 · outbound

This paper cites Chi and Quoc V.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Chi and Quoc V

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T05:49:50.354120Z

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Observation bf973903-1f16-46b4-ac31-9a8109a64c7e · outbound

This paper cites Scaling instruction-finetuned language models , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Scaling instruction-finetuned language models , year =

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.873938Z

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Observation 22f12c7c-1afd-4d0a-bd3a-4081930d89c9 · outbound

This paper cites ArXiv preprint , title =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction ArXiv preprint , title =

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.856887Z

Source-reported events for the cited work

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Observation bc442f6e-970a-4c0d-ac49-e85517058b0d · outbound

This paper cites Generative verifiers: Reward modeling as next-token prediction , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Generative verifiers: Reward modeling as next-token prediction , year =

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.841712Z

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Observation 9680b05a-c1c1-4367-81c7-ec56d5854582 · outbound

This paper cites Foundations of large language models , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Foundations of large language models , year =

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.825586Z

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Observation d3e6dc32-ce32-44c9-ae07-f5a2d468a4ab · outbound

This paper cites Step-level verifier-guided hybrid test-time scaling for large language models , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Step-level verifier-guided hybrid test-time scaling for large language models , year =

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.808971Z

Source-reported events for the cited work

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Observation f1499bb0-3728-49e7-ba81-b386ef8fedb2 · outbound

This paper cites s1: Simple test-time scaling , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction s1: Simple test-time scaling , year =

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.791856Z

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Observation 6962bda8-8b9a-482d-885d-ab4b684d4b79 · outbound

This paper cites Ziegler and Ryan Lowe and Chelsea Voss and Alec Radford and Dario Amodei and Paul F.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Ziegler and Ryan Lowe and Chelsea Voss and Alec Radford and Dario Amodei and Paul F

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.773679Z

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Observation 2e27ccf8-bc49-44e0-8a17-e6ad72a664fb · outbound

This paper cites Christiano and Jan Leike and Tom B.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Christiano and Jan Leike and Tom B

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.757551Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8475e862-f0f7-479e-9626-806ee73707bc · outbound

This paper cites Pku-saferlhf: Towards multi-level safety alignment for llms with human preference , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Pku-saferlhf: Towards multi-level safety alignment for llms with human preference , year =

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.739933Z

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Observation c4d27562-bd7a-497e-9384-c35c7d3df281 · outbound

This paper cites Training a helpful and harmless assistant with reinforcement learning from human feedback , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Training a helpful and harmless assistant with reinforcement learning from human feedback , year =

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T05:49:51.396419Z

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Observation 6a7abe3c-2669-44aa-a261-06f63631e3f5 · outbound

This paper cites Hybrid alignment training for large language models , year =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Hybrid alignment training for large language models , year =

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:49:51.714830Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 42a3a541-e686-4a72-8b1d-e169d7cf4070 · outbound

This paper cites an unresolved cited work.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:49:51.698270Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4fe81ff3-0c90-4e39-99a0-995292c5cf9f · outbound

This paper cites Scaling Learning Algorithms Towards.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction Scaling Learning Algorithms Towards

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T05:49:51.589012Z

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Observation 85bf7a5a-2af4-417c-ad49-306fdf7e79fd · outbound

This paper cites and Osindero, Simon and Teh, Yee Whye , journal =.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction and Osindero, Simon and Teh, Yee Whye , journal =

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T05:49:51.593444Z

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Observation 88a5e574-b9ad-4d50-83de-e772ac4b4c88 · outbound

This paper cites 2016 , publisher=.

RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction 2016 , publisher=

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T05:49:51.597998Z

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