Paper Citation Record · LEDGER

GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2504.00891.

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

pith.paper-citation-record.v1
2504.00891 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:44:05.432691Z

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

1
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 76ff2eb6-6d36-49cd-8018-38ebf2b9cdc7 · inbound

CEC-Zero: Chinese Error Correction Solution Based on LLM cites this paper.

CEC-Zero: Chinese Error Correction Solution Based on LLM GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T21:44:05.432691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0606978e-3802-4f8d-be98-70a2a53d2731 · 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 GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:14:21.245461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20a05919-d3b7-4492-afd8-954af94a293b · inbound

RewardAnything: Generalizable Principle-Following Reward Models cites this paper.

RewardAnything: Generalizable Principle-Following Reward Models GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:06.860706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7891e27b-3d91-4bbf-8f8b-c79929b233b8 · inbound

EduFlow: Advancing MLLMs' Problem-Solving Proficiency through Multi-Stage, Multi-Perspective Critique cites this paper.

EduFlow: Advancing MLLMs' Problem-Solving Proficiency through Multi-Stage, Multi-Perspective Critique GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T18:04:55.568956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e0c21f7-4a31-4d49-aa00-3063fb45931f · inbound

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning cites this paper.

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:25:45.293816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 498826c1-e615-4c11-9bb6-b9d0c2b1e64c · inbound

Stabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVR cites this paper.

Stabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVR GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T23:24:26.313096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d9c29762-dc39-4dfa-94d2-f5d15191f27b · inbound

VRPRM: Process Reward Modeling via Visual Reasoning cites this paper.

VRPRM: Process Reward Modeling via Visual Reasoning GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-22T12:21:31.015089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 09feaf30-5189-45e0-ba59-9a6d8c2827e0 · inbound

VRPRM: Process Reward Modeling via Visual Reasoning cites this paper.

VRPRM: Process Reward Modeling via Visual Reasoning GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T04:27:05.504961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21956489-8630-4de6-be2c-d86c29306425 · 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 GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T00:59:54.544029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b17e8c60-dd13-46b4-9bf3-6a46a0cd282b · inbound

LLaVA-Critic-R1: Your Critic Model is Secretly a Strong Policy Model cites this paper.

LLaVA-Critic-R1: Your Critic Model is Secretly a Strong Policy Model GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-05T13:24:39.969937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9ff55b3-f345-4883-b400-6c450a78b296 · inbound

Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training cites this paper.

Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T22:40:43.181401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4cfd4f57-14b9-4ecf-b437-59dc73f21466 · inbound

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle cites this paper.

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 248

Resolution: unresolved; no resolver link, observed 2026-08-04T16:07:47.889822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cfcb354-9fa0-46ac-8c05-00e28e555a11 · inbound

Rethinking Reward Models for Multi-Domain Test-Time Scaling cites this paper.

Rethinking Reward Models for Multi-Domain Test-Time Scaling GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T13:27:05.292849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fa7736a-1c50-4957-948d-cc2c222b8e8f · inbound

OpenClaw-RL: Train Any Agent Simply by Talking cites this paper.

OpenClaw-RL: Train Any Agent Simply by Talking GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T13:00:00.778623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5071457f-3064-4b6d-9403-5c11d55f4eb2 · inbound

Cut Your Losses! Learning to Prune Paths Early for Efficient Parallel Reasoning cites this paper.

Cut Your Losses! Learning to Prune Paths Early for Efficient Parallel Reasoning GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:53:03.631287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 150769c8-fde7-4410-96b5-e1bbb638392f · inbound

Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis cites this paper.

Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 77

Resolution: verified exact; arxiv_id, observed 2026-05-09T00:19:26.060306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 55fb33bd-8353-4aa3-9d71-e11beff6a47a · inbound

Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis cites this paper.

Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 77

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:15:42.607003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 902af584-c4ad-43c0-bd49-f7955164ed3a · inbound

Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning cites this paper.

Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 180

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T23:15:49.434131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 21a0c66c-7784-4175-989a-a8e94a6ee721 · inbound

Unsupervised Process Reward Models cites this paper.

Unsupervised Process Reward Models GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:21:18.928968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 88537622-2749-48fa-9e25-640d33ac42cf · inbound

Not only where, But when: Temporal Scheduling for RLVR cites this paper.

Not only where, But when: Temporal Scheduling for RLVR GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:44:01.838000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4fa6bd11-97f4-4a59-9fd0-a64de946cd65 · inbound

Trust Region On-Policy Distillation cites this paper.

Trust Region On-Policy Distillation GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 196

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:46:14.328394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 554fc23f-eb35-46a2-b280-ccf2419f76d4 · inbound

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning cites this paper.

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 114

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:37:25.321817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fc0c13be-1a6b-4d1a-afd0-91d8030837c1 · inbound

The Hidden Bias of Process Reward Models:PRISM for Rewarding the Right Reasoning cites this paper.

The Hidden Bias of Process Reward Models:PRISM for Rewarding the Right Reasoning GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:37:30.065159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 275c856d-35b4-46b1-83da-a774dafbc60f · inbound

KV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time Scaling cites this paper.

KV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time Scaling GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-13T05:02:55.608400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 890c36e8-81db-45f0-b5d5-67bbcd0237eb · inbound

Test-Time Scaling for Small VLMs on Multilingual Visual MCQ cites this paper.

Test-Time Scaling for Small VLMs on Multilingual Visual MCQ GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-13T03:00:51.318412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4066ecfe-4bb9-4e54-a632-564d9fc718a5 · inbound

Proxy Exploration and Reusable Guidance: A Modular LLM Post-Training Paradigm via Proxy-Guided Update Signals cites this paper.

Proxy Exploration and Reusable Guidance: A Modular LLM Post-Training Paradigm via Proxy-Guided Update Signals GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T05:09:00.865375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.