Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.05046.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:57:06.069990Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T08:35:32.544536Z
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 284c11df-c240-457f-96f5-e9968c74f38d · inbound
Hallucination of Multimodal Large Language Models: A Survey cites this paper.
Hallucination of Multimodal Large Language Models: A Survey FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback
Reference 82
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T12:33:33.864804Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e6595046-8b54-4a70-a9a5-f3918fbb52ee · inbound
Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models cites this paper.
Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:57:06.069990Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f41038fe-c266-4a23-b176-e79d8f69683d · inbound
Mitigating Object Hallucinations via Sentence-Level Early Intervention cites this paper.
Mitigating Object Hallucinations via Sentence-Level Early Intervention FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T08:35:32.547950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation dd1e8d19-788f-481c-8135-6a6577e1f933 · inbound
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges cites this paper.
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback
Reference 280
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:13:07.288520Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 890ed4af-e217-4132-9b46-8b1009af927c · inbound
Empowering Multimodal LLMs with External Tools: A Comprehensive Survey cites this paper.
Empowering Multimodal LLMs with External Tools: A Comprehensive Survey FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback
Reference 191
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T20:29:02.201967Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.