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Paper Citation Record · LEDGER

R-PRM: Reasoning-Driven Process Reward Modeling

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2503.21295.

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

pith.paper-citation-record.v1
2503.21295 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:21:22.161333Z

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
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
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 4bcda4fe-1756-49ff-af56-4157e78c42d3 · inbound

From System 1 to System 2: A Survey of Reasoning Large Language Models cites this paper.

From System 1 to System 2: A Survey of Reasoning Large Language Models R-PRM: Reasoning-Driven Process Reward Modeling

Reference 166

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:36:24.184410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T01:36:23.845366Z digest=sha256:d6f2b89cf72eca9cee4fd1004d04334422d24be9ff0c5514b41f032afd5ece3a

Observation 41e25044-f111-4b51-9009-c90103c76094 · inbound

PATS: Process-Level Adaptive Thinking Mode Switching cites this paper.

PATS: Process-Level Adaptive Thinking Mode Switching R-PRM: Reasoning-Driven Process Reward Modeling

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:21:22.161333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:21:22.161333Z digest=sha256:cd061e11475d6d51ba245c08cc7e38bb76fa17d4853f953720cbca4cfb4115ea

Observation a86bc2bd-c4a8-4c07-8e90-39319c29e13c · inbound

Error Typing for Smarter Rewards: Improving Process Reward Models with Error-Aware Hierarchical Supervision cites this paper.

Error Typing for Smarter Rewards: Improving Process Reward Models with Error-Aware Hierarchical Supervision R-PRM: Reasoning-Driven Process Reward Modeling

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:19.876368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:14:19.876368Z digest=sha256:3a0f7a8070028f23baaf272ac7ffbe0302abf5adeaf6556f8fdb4762273eeb41

Observation 5faa7b4d-a619-40c7-960d-67388866537f · inbound

GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning cites this paper.

GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning R-PRM: Reasoning-Driven Process Reward Modeling

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T00:59:53.063654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:59:53.063654Z digest=sha256:a0f6a6dbba2bd051020a2c5518eb702d3c929a177109e1ffc94a6f1f6bbe6bc9

Observation 718a23d0-7989-4f4c-9022-a75a6ae2d9d8 · inbound

StructVRM: Aligning Multimodal Reasoning with Structured and Verifiable Reward Models cites this paper.

StructVRM: Aligning Multimodal Reasoning with Structured and Verifiable Reward Models R-PRM: Reasoning-Driven Process Reward Modeling

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T23:29:17.085079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:29:17.085079Z digest=sha256:f1d42a62abb57e9dfda4ff89b1d24186727f5f3f4ad7f8a1cd50b43bdd2b2652

Observation d56a3dea-70eb-4900-b1f1-aac1f265c022 · inbound

An Explainable Machine Learning Framework for Railway Predictive Maintenance using Data Streams from the Metro Operator of Portugal cites this paper.

An Explainable Machine Learning Framework for Railway Predictive Maintenance using Data Streams from the Metro Operator of Portugal R-PRM: Reasoning-Driven Process Reward Modeling

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T23:25:50.437799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:25:50.437799Z digest=sha256:9fad3da38cefd0d6548cad295c05070296b7f2c0571ad47c4f0511ff7e4b577c

Observation f55eaf23-b8f5-4587-8d6a-d6dca882a93c · inbound

AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Models cites this paper.

AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Models R-PRM: Reasoning-Driven Process Reward Modeling

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T22:58:50.079618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:58:50.079618Z digest=sha256:a6133c35a1d790e54b582ba918d44da2697642b0a4737939506728a25b103516

Observation a393c6a9-5bd3-4a51-8cf1-56aecfb7a3fa · inbound

ToolPRM: Fine-Grained Inference Scaling of Structured Outputs for Function Calling cites this paper.

ToolPRM: Fine-Grained Inference Scaling of Structured Outputs for Function Calling R-PRM: Reasoning-Driven Process Reward Modeling

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-18T06:30:59.606855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T06:30:39.858246Z digest=sha256:12b2d84c69ea7edaa14a67f7523dc94a341b7693764db07ce979898af2a01b0e

Observation 2a30bd6c-6d1a-4085-ae26-802f37b13c27 · inbound

HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs cites this paper.

HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs R-PRM: Reasoning-Driven Process Reward Modeling

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-03T20:43:42.331901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:43:42.331901Z digest=sha256:746938011ae86222ec47291ee6ac95d386d0aee00291191c96eb68ff8cd314ed

Observation 4fd6eea1-b460-4f99-8258-c69097cc812c · inbound

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation cites this paper.

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation R-PRM: Reasoning-Driven Process Reward Modeling

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-03T03:04:44.303909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:04:44.303909Z digest=sha256:4e83a1bea0b7d0f1ae839eb09d61d333c312c27cc0dddf18305713f322962d98

Observation b4ee02a4-07ff-42d9-81b8-cb80e3007941 · inbound

Reasoning-targeted Jailbreak Attacks on Large Reasoning Models via Semantic Triggers and Psychological Framing cites this paper.

Reasoning-targeted Jailbreak Attacks on Large Reasoning Models via Semantic Triggers and Psychological Framing R-PRM: Reasoning-Driven Process Reward Modeling

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:08:26.234113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T08:24:43.494005Z digest=sha256:67e46edba43037fa8619adf0976b41cf533963ae6358e3f5194398108bbfff3e

Observation 8576d876-f414-40ab-ae32-bc9bbf4c0dd7 · inbound

Pause or Fabricate? Training Language Models for Grounded Reasoning cites this paper.

Pause or Fabricate? Training Language Models for Grounded Reasoning R-PRM: Reasoning-Driven Process Reward Modeling

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-10T03:03:36.662326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T03:01:58.366028Z digest=sha256:c187e68d107b1583f042940010954b8c82da34655f676e12316c3919be172a69

Observation 63e4b679-207e-4c0d-a4bd-32fea6b1e59b · inbound

From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding cites this paper.

From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding R-PRM: Reasoning-Driven Process Reward Modeling

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-20T18:43:38.772927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T18:39:11.904941Z digest=sha256:d09e680016fcb5def60f9dcd8f694f3e191ec64fa9ff2177459e00e36d3dce66

Observation 24989b75-f624-45b4-a5ac-7d75c5c20002 · inbound

MARD: Mirror-Augmented Reasoning Distillation for Mechanism-Level Drug-Drug Interaction Prediction cites this paper.

MARD: Mirror-Augmented Reasoning Distillation for Mechanism-Level Drug-Drug Interaction Prediction R-PRM: Reasoning-Driven Process Reward Modeling

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:58:03.356407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T09:44:38.871250Z digest=sha256:9af7bd464466c1b2c8bf79c91280d78f31c2b3985e18f8e2c45e564045285f9c

Observation 8a8debba-b69b-46d0-8a60-8c98e2030c48 · inbound

Reinforcement Learning without Ground-Truth Solutions can Improve LLMs cites this paper.

Reinforcement Learning without Ground-Truth Solutions can Improve LLMs R-PRM: Reasoning-Driven Process Reward Modeling

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:59:51.863366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T04:47:47.691913Z digest=sha256:9b415a31447e43dcf3285d08f582a7dfc2f30bfa18e49a3bafda0d877b17535b