Paper Citation Record · LEDGER

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

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 37 inbound Pith citation observations for arXiv:2401.06080.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2401.06080 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 37 of 37 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:34:01.351960Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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External citation measurements

7
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 73fa1a52-2f38-4c64-a58c-de79b310f68f · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-16T09:34:04.707958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0b09bcf4-e9eb-4ddc-840d-b79250750aaf · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-16T09:16:17.483570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6fc7a908-e2fc-48ce-bc07-3bf1539d8369 · inbound

Qwen2.5 Technical Report cites this paper.

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

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:25:27.899604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-09T20:34:01.351960Z

Source-reported events for the cited work

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Observation 791982b8-e588-4887-bc77-7e90d866e91f · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-09T11:47:17.634354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5842996-e851-443c-bc8d-630bf3aa9e5c · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.959132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 67d604db-332f-4d2e-a985-bce45b67d65c · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-08T19:07:35.445137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b94a2143-d519-4a37-9fa7-fbb3ac0946b1 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-08T11:57:11.983807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c93a8b98-a211-439d-86d1-bf05ae4a3959 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:26:05.576663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T15:34:52.624148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 987cc69d-84de-4dab-9a7e-544ac5e73b2c · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-07T14:57:31.942943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fea45f8-50fa-4f09-9407-96a73b02ce3a · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-19T13:42:19.352622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T13:15:55.913770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T00:33:56.965198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39dc39f2-8afa-497d-ba50-1883950b60d0 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-06T19:57:28.485425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27fdfeb5-0952-486b-a2b7-02ddb351d597 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-06T18:51:30.462615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-04T14:52:22.806003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified exact; arxiv_id, observed 2026-05-18T08:21:07.012995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:16:04.419338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:00:28.159008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:20:25.604855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:20:41.718303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:16:18.568531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T07:37:29.945673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T06:51:44.296018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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

Resolution: unresolved; no resolver link, observed 2026-07-14T15:37:01.391649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-02T08:00:53.827430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-01T03:14:12.745471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.