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Paper Citation Record · LEDGER

Dense Reward for Free in Reinforcement Learning from Human Feedback

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2402.00782.

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

pith.paper-citation-record.v1
2402.00782 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:13:53.482971Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:39:45.380468Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c62c326f-aff4-402f-9beb-a0c31d46f666 · inbound

Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents cites this paper.

Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 212

Resolution
verified exact
arxiv_id, observed 2026-05-20T09:42:04.405371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-20T09:41:59.979595Z digest=sha256:584a4cc698101cca2f7dcc7d1b1f85a87d7cf15dd699a765d05b159d94911f32

Observation bcf49968-5ddc-40c2-9b11-23bece0c6c06 · inbound

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

T-REG: Preference Optimization with Token-Level Reward Regularization Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 4

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no resolver link, observed 2026-08-11T23:15:55.920133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:15:55.920133Z digest=sha256:26321ae42fe3174974c844e3ce8d8f6db8fa89c3adde2d60aed21119a7f97f3c

Observation b23a981a-acb5-4d02-9a70-57804152c202 · inbound

CLIP-RLDrive: Human-Aligned Autonomous Driving via CLIP-Based Reward Shaping in Reinforcement Learning cites this paper.

CLIP-RLDrive: Human-Aligned Autonomous Driving via CLIP-Based Reward Shaping in Reinforcement Learning Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 15

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no resolver link, observed 2026-08-11T14:10:08.607669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:10:08.607669Z digest=sha256:ef980d9f982e48f544bc8d898906bd2b33d2a3ed0de09c343a497ced16c4db7e

Observation 1e3c7ecc-4f96-4ca3-b566-5173bc5ddc35 · inbound

A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directions cites this paper.

A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directions Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 98

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unresolved
no resolver link, observed 2026-08-11T14:15:31.667310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:15:31.667310Z digest=sha256:76957187d66e4220a45c223f03408fe81a7047a19313680515a038c1ff2e28cd

Observation 0cf3d6ff-6d29-49ed-942a-da79774322f7 · inbound

Learning Explainable Dense Reward Shapes via Bayesian Optimization cites this paper.

Learning Explainable Dense Reward Shapes via Bayesian Optimization Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 10

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unresolved
no resolver link, observed 2026-08-16T11:13:53.482971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:13:53.482971Z digest=sha256:fa894a13ebf3644f428ff1025e39221ab2ada8992887c1ef5cdbf96aa04756bd

Observation 396035c5-2347-4a06-9f4c-7781119f8e61 · inbound

A Survey on Progress in LLM Alignment from the Perspective of Reward Design cites this paper.

A Survey on Progress in LLM Alignment from the Perspective of Reward Design Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 111

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unresolved
no resolver link, observed 2026-08-16T00:52:06.982211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:52:06.982211Z digest=sha256:a38f75a9d9c2bedffc9f440b5948a7570ff52686cf96f80700b1e2b4f45ebaee

Observation 89aedb79-5dcd-4cae-bd54-dd6f3cd454ff · inbound

OpenReview Should be Protected and Leveraged as a Community Asset for Research in the Era of Large Language Models cites this paper.

OpenReview Should be Protected and Leveraged as a Community Asset for Research in the Era of Large Language Models Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 134

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:46.566747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:31:46.566747Z digest=sha256:c94a161c04a731f6b04b440aa050448cb2eb5500e09d35f180073ed8c0291a76

Observation 04b3437d-e8a2-4c38-90df-e92982a2163d · inbound

Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy cites this paper.

Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-07T13:24:30.201304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:24:30.201304Z digest=sha256:51ccf700806f29d6c8b825e17b3d7cc390249191b439e672580fd8ddc779e14f

Observation 3d4739b4-8fbb-4f16-9d85-ca8afd503afd · inbound

Response-Level Rewards Are All You Need for Online Reinforcement Learning in LLMs: A Mathematical Perspective cites this paper.

Response-Level Rewards Are All You Need for Online Reinforcement Learning in LLMs: A Mathematical Perspective Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T11:32:29.474618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:32:29.474618Z digest=sha256:9c30d545d2120a446a3e35d0ea262f3f19af9fdb374b5e5e2ebe5eb1ed65e142

Observation eeafc856-3917-4b89-81e4-fc7dc8fc5775 · inbound

Enhancing RLHF with Human Gaze Modeling cites this paper.

Enhancing RLHF with Human Gaze Modeling Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T18:11:15.717117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:11:15.717117Z digest=sha256:9b41840f639323141baa8f99a77bd2816272c438d424bfaaff2e4ca3efc650d2

Observation 86dc17e9-3288-47f0-beb1-d6f026a9a300 · inbound

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities cites this paper.

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 1995

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unresolved
no resolver link, observed 2026-08-06T16:34:24.959248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:34:24.959248Z digest=sha256:34f57788475334bc93c518b7549f8cbfe32ff62750b1c04be23f6630cfd5353a

Observation 0d5c9c75-420b-4e5e-8e4a-28b9c5425713 · inbound

GRPO-VPS: Enhancing Group Relative Policy Optimization with Verifiable Process Supervision for Effective Reasoning cites this paper.

GRPO-VPS: Enhancing Group Relative Policy Optimization with Verifiable Process Supervision for Effective Reasoning Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:14:46.356805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T00:14:29.531510Z digest=sha256:dba84eacec526d7475fab7e5508c8b677eb9ab321b271e18b879711131932edd

Observation c5392912-1faf-4e67-a8c5-ad70b0730da2 · inbound

BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models cites this paper.

BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 80

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arxiv_id, observed 2026-05-12T03:11:18.973585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-12T03:09:40.321500Z digest=sha256:edd74bf5345c5b229f66f0fdc693d313422bbefe438084c41259e0f9f8d20d9a

Observation adaaacc2-3461-49f7-b636-482d7be0e49b · inbound

BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models cites this paper.

BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 87

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metadata mismatch
arxiv_id, observed 2026-05-13T06:07:22.397309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-13T06:03:32.270553Z digest=sha256:b1da0c987b5ee3e170582d75ba7e88f3b504011180b6874141607084e871cdff

Observation f64647a0-71af-4baf-9b8e-a5e4a8c7f973 · inbound

Multi-Rollout On-Policy Distillation via Peer Successes and Failures cites this paper.

Multi-Rollout On-Policy Distillation via Peer Successes and Failures Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 41

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verified exact
arxiv_id, observed 2026-05-14T21:32:59.813847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-14T21:29:36.803832Z digest=sha256:0561150f11f82897ae1e625f79a422d80f4e5f38ee65fe7311a5933acaaf7e16

Observation 445c0768-7675-4872-ad45-920470cccdbd · inbound

Multi-Rollout On-Policy Distillation via Peer Successes and Failures cites this paper.

Multi-Rollout On-Policy Distillation via Peer Successes and Failures Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T22:05:05.717282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-30T22:01:38.639580Z digest=sha256:d068c8bb4bcfaf3ebeab6b8d11e92d15543ff932627662c1f5f2e83a4bfc42fe

Observation 65932d75-77af-4ff1-a506-947e7a565913 · inbound

BALTO: Balanced Token-Level Policy Optimization for Hallucination Mitigation cites this paper.

BALTO: Balanced Token-Level Policy Optimization for Hallucination Mitigation Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 4

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verified exact
arxiv_id, observed 2026-07-03T17:28:44.652844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-27T04:07:26.224919Z digest=sha256:2839dbac0fc0fce8b407b9a6e6181db19a62e4aabc228d4e4ba0bb9f1211d532

Observation aa517d00-67a1-44a2-a698-d2b0ee743b75 · inbound

Dense Reward for Multi-View 3D Reasoning with Global Maps and Local Views cites this paper.

Dense Reward for Multi-View 3D Reasoning with Global Maps and Local Views Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:39:45.381977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-26T08:38:46.044079Z digest=sha256:fa43fe76e80765aeaeea5a3a43e6affbdd1e07f4f176f0bd258f00e28dab636d

Observation cf6a8f44-ebf0-4252-9e1f-b8ab5467c684 · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 290

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unresolved
no resolver link, observed 2026-07-11T13:53:36.775836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T13:53:36.775836Z digest=sha256:94697ccd96baac5e2ccb905721c7f3db4d7095e4c2153196ad82a8128a4fc2a3

Observation dc916ebb-4544-40d8-a59a-ffbe1455bcca · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 291

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unresolved
no resolver link, observed 2026-08-02T08:41:06.582566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T08:41:06.582566Z digest=sha256:02bcf6c663523d8f9e7c98499f0c07b8d07931654a65b61a8f34631ce07a52fa

Observation 497c2e34-36c3-4fa8-897d-2935a505487d · inbound

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text cites this paper.

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 96

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unresolved
no resolver link, observed 2026-08-02T13:37:01.518021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T13:37:01.518021Z digest=sha256:c0adb66f3769c85d5755459f825c17cb7b00b06e2f79073baf9f5f38d27c1f55

Observation 781e0aaa-5162-4176-b331-8e8e6057cad7 · inbound

Token-Level Credit Assignment Optimization for Generative Document Retrieval cites this paper.

Token-Level Credit Assignment Optimization for Generative Document Retrieval Dense Reward for Free in Reinforcement Learning from Human Feedback

Reference 3

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no resolver link, observed 2026-08-16T00:23:44.319058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:23:44.319058Z digest=sha256:6868527d52f7f90142f5f62ce3680d851447d3e2b020d69b68beced8a694aa3b