Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2503.02382.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T03:01:41.653988Z
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 6384c430-559b-40ec-b5c6-3138d9824478 · inbound
Unlocking Exploration in RLVR: Uncertainty-aware Advantage Shaping for Deeper Reasoning cites this paper.
Unlocking Exploration in RLVR: Uncertainty-aware Advantage Shaping for Deeper Reasoning An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T07:21:04.401137Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 88bb40ad-7ed1-4801-8813-cee20273a3a0 · inbound
LLM Reasoning with Process Rewards for Outcome-Guided Steps cites this paper.
LLM Reasoning with Process Rewards for Outcome-Guided Steps An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:47:28.419331Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 97bc4bfb-ff1c-4138-82a6-6dec922afe40 · inbound
Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards cites this paper.
Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T04:45:21.116929Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b007d93f-ecba-42dc-810f-f22a70946847 · inbound
Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models cites this paper.
Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:01:41.653988Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.