Secrets of RLHF in Large Language Models Part II: Reward Modeling | Paper Citation Record

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ORPO: Monolithic Preference Optimization without Reference Model cites this paper.

ORPO: Monolithic Preference Optimization without Reference Model Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 53

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CHAI for LLMs: Improving Code-Mixed Translation in Large Language Models through Reinforcement Learning with AI Feedback cites this paper.

CHAI for LLMs: Improving Code-Mixed Translation in Large Language Models through Reinforcement Learning with AI Feedback Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 38

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Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization cites this paper.

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 97

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AddrLLM: Address Rewriting via Large Language Model on Nationwide Logistics Data cites this paper.

AddrLLM: Address Rewriting via Large Language Model on Nationwide Logistics Data Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 54

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T-REG: Preference Optimization with Token-Level Reward Regularization cites this paper.

T-REG: Preference Optimization with Token-Level Reward Regularization Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 41

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Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective cites this paper.

Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 18

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Qwen2.5 Technical Report cites this paper.

Qwen2.5 Technical Report Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 36

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Observation b44864e9-f666-4875-a8b8-13dd0bb47821 · inbound

MPPO: Multi Pair-wise Preference Optimization for LLMs with Arbitrary Negative Samples cites this paper.

MPPO: Multi Pair-wise Preference Optimization for LLMs with Arbitrary Negative Samples Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 17

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Divide and Conquer: A Hybrid Strategy Defeats Multimodal Large Language Models cites this paper.

Divide and Conquer: A Hybrid Strategy Defeats Multimodal Large Language Models Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 45

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An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems cites this paper.

An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 110

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Many of Your DPOs are Secretly One: Attempting Unification Through Mutual Information cites this paper.

Many of Your DPOs are Secretly One: Attempting Unification Through Mutual Information Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 45

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Observation 418f59c4-f5d4-4007-8983-11201a86c7f9 · inbound

PairJudge RM: Perform Best-of-N Sampling with Knockout Tournament cites this paper.

PairJudge RM: Perform Best-of-N Sampling with Knockout Tournament Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 31

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Observation 98c2e227-9c84-4ac3-b7b7-dc299e2ecb9b · inbound

The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking cites this paper.

The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 36

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Reviving The Classics: Active Reward Modeling in Large Language Model Alignment cites this paper.

Reviving The Classics: Active Reward Modeling in Large Language Model Alignment Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 40

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Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs cites this paper.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 27

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Observation 95f05551-4bd2-4d8b-8c57-24adc9473adc · inbound

How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators cites this paper.

How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:57:29.575352Z

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Refining Positive and Toxic Samples for Dual Safety Self-Alignment of LLMs with Minimal Human Interventions cites this paper.

Refining Positive and Toxic Samples for Dual Safety Self-Alignment of LLMs with Minimal Human Interventions Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 27

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Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples cites this paper.

Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 71

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A Survey of Slow Thinking-based Reasoning LLMs using Reinforced Learning and Inference-time Scaling Law cites this paper.

A Survey of Slow Thinking-based Reasoning LLMs using Reinforced Learning and Inference-time Scaling Law Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 111

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Observation ff05ea61-5cf2-4448-bb54-cb05ad9c6d9f · inbound

Learning Guarantee of Reward Modeling Using Deep Neural Networks cites this paper.

Learning Guarantee of Reward Modeling Using Deep Neural Networks Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 41

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Seed1.5-VL Technical Report cites this paper.

Seed1.5-VL Technical Report Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 138

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Observation 0246dc54-b726-4841-9133-fb45a8521d82 · inbound

On the Robustness of Reward Models for Language Model Alignment cites this paper.

On the Robustness of Reward Models for Language Model Alignment Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 63

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Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment cites this paper.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 9

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Observation a812a115-e4e8-4789-8eca-a48adb5d8948 · inbound

Reward Reasoning Model cites this paper.

Reward Reasoning Model Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 58

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MPO: Multilingual Safety Alignment via Reward Gap Optimization cites this paper.

MPO: Multilingual Safety Alignment via Reward Gap Optimization Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 68

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Incentivizing High-Quality Human Annotations with Golden Questions cites this paper.

Incentivizing High-Quality Human Annotations with Golden Questions Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 35

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Observation 3952763d-ace7-4824-9572-3163cc78be12 · inbound

Adaptive Detoxification: Safeguarding General Capabilities of LLMs through Toxicity-Aware Knowledge Editing cites this paper.

Adaptive Detoxification: Safeguarding General Capabilities of LLMs through Toxicity-Aware Knowledge Editing Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 33

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Observation 0b0cd5c5-7278-4c5a-a7b3-0ea7ca8dfc02 · inbound

Pairwise Calibrated Rewards for Pluralistic Alignment cites this paper.

Pairwise Calibrated Rewards for Pluralistic Alignment Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 56

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Observation 712e93bf-a4be-4b77-8f3b-32299be42706 · inbound

VL-GenRM: Enhancing Vision-Language Verification via Vision Experts and Iterative Training cites this paper.

VL-GenRM: Enhancing Vision-Language Verification via Vision Experts and Iterative Training Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 23

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SymbolicThought: Integrating Language Models and Symbolic Reasoning for Consistent and Interpretable Human Relationship Understanding cites this paper.

SymbolicThought: Integrating Language Models and Symbolic Reasoning for Consistent and Interpretable Human Relationship Understanding Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 9

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Bradley-Terry and Multi-Objective Reward Modeling Are Complementary cites this paper.

Bradley-Terry and Multi-Objective Reward Modeling Are Complementary Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 55

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Observation 6e2155e5-e488-4033-a71f-79949deb1a4c · inbound

Adaptive Margin RLHF via Preference over Preferences cites this paper.

Adaptive Margin RLHF via Preference over Preferences Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 33

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Observation b1810d4c-e22a-4a9e-b1f4-565668a357f8 · inbound

Users as Annotators: LLM Preference Learning from Comparison Mode cites this paper.

Users as Annotators: LLM Preference Learning from Comparison Mode Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 25

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Observation b3c752b3-7b51-4c17-af23-0b4694293918 · inbound

Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration cites this paper.

Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 32

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ee674794-cfa2-4c6b-abdd-e3641071a541 · inbound

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges cites this paper.

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 4

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Observation d3ebbd09-47a7-412e-97bf-eac652a28814 · inbound

Reinforcement Learning via Value Gradient Flow cites this paper.

Reinforcement Learning via Value Gradient Flow Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 66

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8bdc2aa2-39d8-4cc2-a6a1-fa90e214838c · inbound

DT2IT-MRM: Debiased Preference Construction and Iterative Training for Multimodal Reward Modeling cites this paper.

DT2IT-MRM: Debiased Preference Construction and Iterative Training for Multimodal Reward Modeling Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:26:03.869033Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3a406e49-0558-4235-92b8-ab3799e9c7d8 · inbound

Gradient-Gated DPO: Stabilizing Preference Optimization in Language Models cites this paper.

Gradient-Gated DPO: Stabilizing Preference Optimization in Language Models Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 14

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9dcd4027-37e4-456c-b1e5-32c00cd4bbd3 · inbound

Personalized Alignment Revisited: The Necessity and Sufficiency of User Diversity cites this paper.

Personalized Alignment Revisited: The Necessity and Sufficiency of User Diversity Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 8

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Observation 9e9cfa9b-6513-47ce-a9ae-ac8768437ab2 · inbound

Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization cites this paper.

Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 47

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Observation 90b60aec-fea5-48c8-a609-4e07d988c717 · inbound

Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance cites this paper.

Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-15T03:19:43.017450Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8fe3cacf-d709-4e12-97df-291176f3fe31 · inbound

Boosting Self-Consistency with Ranking cites this paper.

Boosting Self-Consistency with Ranking Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 185

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7b24150e-32d1-49a0-aa08-65e809dabaa6 · inbound

DynaCF: Mitigating Shortcut Learning in Reward Models via Dynamic Counterfactual Sensitivity cites this paper.

DynaCF: Mitigating Shortcut Learning in Reward Models via Dynamic Counterfactual Sensitivity Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-06-27T17:31:06.957727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bcf61e05-b703-4838-96f2-ca6ee50f3ef2 · inbound

Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization cites this paper.

Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 115

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T01:37:30.515245Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 24da175c-92c6-47ff-9ec0-a4ccd107e1a7 · inbound

Representation-Aware Advantage Estimation: Your Reward Model Provides More Than A Scalar Output cites this paper.

Representation-Aware Advantage Estimation: Your Reward Model Provides More Than A Scalar Output Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T04:47:38.282385Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 84b2b752-56a8-4a70-ac76-0f528db5dc7a · inbound

Understanding helpfulness and harmless tension in reward models cites this paper.

Understanding helpfulness and harmless tension in reward models Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T14:18:22.991762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 33796558-f5e7-46a1-87c9-9ca4b3415e13 · inbound

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 210

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:59:40.105153Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 90eb243c-e305-431b-99ab-b8b2084915af · inbound

BV-Blend: Uncertainty-Weighted Historical Baselines for Stable Critic-Free RL with Verifiable Rewards cites this paper.

BV-Blend: Uncertainty-Weighted Historical Baselines for Stable Critic-Free RL with Verifiable Rewards Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 34

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T12:44:40.135832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e39d2557-3329-4f19-bc1b-9b02bb77a51b · inbound

Metadata-Free Meta-Reweighted Direct Preference Optimization under Noisy Preference Labels cites this paper.

Metadata-Free Meta-Reweighted Direct Preference Optimization under Noisy Preference Labels Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 9

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Observation e433b4e7-168e-4078-ad68-e57a0bc95423 · inbound

Metadata-Free Meta-Reweighted Direct Preference Optimization under Noisy Preference Labels cites this paper.

Metadata-Free Meta-Reweighted Direct Preference Optimization under Noisy Preference Labels Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 8

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Observation 36eec2bb-fe64-48d6-9715-b767de896496 · inbound

Meta-Learned Reward Shaping for Reinforcement Learning from Human Feedback cites this paper.

Meta-Learned Reward Shaping for Reinforcement Learning from Human Feedback Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 14

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Pith citing papers