Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing Constraint
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.06081.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T23:15:55.932024Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T07:59:40.603282Z
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 762490b2-eab8-414a-a0b1-1607676e4f2a · inbound
T-REG: Preference Optimization with Token-Level Reward Regularization cites this paper.
T-REG: Preference Optimization with Token-Level Reward Regularization Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing Constraint
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T23:15:55.932024Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f2ec2345-4ab6-4990-9830-98a7c3e08882 · inbound
Flipping Knowledge Distillation: Leveraging Small Models' Expertise to Enhance LLMs in Text Matching cites this paper.
Flipping Knowledge Distillation: Leveraging Small Models' Expertise to Enhance LLMs in Text Matching Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing Constraint
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:29:06.123726Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c759aa96-9b15-4886-a252-845523337abd · inbound
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing Constraint
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T07:59:40.604575Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.