Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
From Trial-and-Error to Improvement: A Systematic Analysis of LLM Exploration Mechanisms in RLVR
As of 31 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2508.07534.
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 2026-07-31T06:34:12.847434+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-18T00:02:24.352947Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T00:02:25.252362Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- 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 9a761aa7-9967-4ef2-81d7-1f3f78de71b1 · inbound
A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.
A Survey of Reinforcement Learning for Large Reasoning Models From Trial-and-Error to Improvement: A Systematic Analysis of LLM Exploration Mechanisms in RLVR
Reference 106
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T00:02:25.255020Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation ffad19ef-e6cf-4214-9ca7-868e40a51bff · inbound
ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning cites this paper.
ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning From Trial-and-Error to Improvement: A Systematic Analysis of LLM Exploration Mechanisms in RLVR
Reference 62
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T15:41:45.790129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 5c712013-bb5f-41fa-9ad7-1ab6b67256b3 · inbound
ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning cites this paper.
ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning From Trial-and-Error to Improvement: A Systematic Analysis of LLM Exploration Mechanisms in RLVR
Reference 62
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T03:55:56.685011Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.