Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2311.09336.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T11:18:35.661984Z
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 00868247-cc74-4295-8907-727268ca5f79 · inbound
Error-driven Data-efficient Large Multimodal Model Tuning cites this paper.
Error-driven Data-efficient Large Multimodal Model Tuning LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback
Reference 73
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:18:35.661984Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f073ad85-5d42-4e25-917d-cd383d583d9a · inbound
Early evidence of how LLMs outperform traditional systems on OCR/HTR tasks for historical records cites this paper.
Early evidence of how LLMs outperform traditional systems on OCR/HTR tasks for historical records LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T18:06:38.193969Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a5f72b0-486c-475a-9874-9b454c8931c8 · inbound
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention cites this paper.
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback
Reference 69
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T20:56:50.436665Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 65cc583b-0952-4c72-ba8c-e838df959c5a · inbound
A-SEA3L-QA: A Fully Automated Self-Evolving, Adversarial Workflow for Arabic Long-Context Question-Answer Generation cites this paper.
A-SEA3L-QA: A Fully Automated Self-Evolving, Adversarial Workflow for Arabic Long-Context Question-Answer Generation LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:23:44.798688Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aa90ed5f-c288-496d-a858-8dba83f0ea9f · inbound
REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations cites this paper.
REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback
Reference 160
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T20:17:56.280390Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.