Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2501.15140.
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 2026-08-07T12:51:42.318376Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T14:53:00.639638Z
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 19fea118-45d9-4fe5-9c13-0b0e861f7fef · inbound
MCFNet: A Multimodal Collaborative Fusion Network for Fine-Grained Semantic Classification cites this paper.
MCFNet: A Multimodal Collaborative Fusion Network for Fine-Grained Semantic Classification Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:51:42.318376Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f0bde27f-7f93-4454-ad3b-16cdc8c8e9f6 · inbound
FineBadminton: A Multi-Level Dataset for Fine-Grained Badminton Video Understanding cites this paper.
FineBadminton: A Multi-Level Dataset for Fine-Grained Badminton Video Understanding Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:06:31.509968Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0995a2e7-fa06-4569-8a64-7ffa16ba4f66 · inbound
Can Textual Reasoning Improve the Performance of MLLMs on Fine-grained Visual Classification? cites this paper.
Can Textual Reasoning Improve the Performance of MLLMs on Fine-grained Visual Classification? Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T14:53:00.642018Z
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 f71f9330-686e-4719-97f0-99f229fd491d · inbound
Fine-R1: Make Multi-modal LLMs Excel in Fine-Grained Visual Recognition by Chain-of-Thought Reasoning cites this paper.
Fine-R1: Make Multi-modal LLMs Excel in Fine-Grained Visual Recognition by Chain-of-Thought Reasoning Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:17:26.624076Z
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 f20cbdea-c7fb-47ff-ab85-b55ed29a3387 · inbound
Learning Taxonomic Trees with Hierarchical Representation Regularization for Large Multimodal Models cites this paper.
Learning Taxonomic Trees with Hierarchical Representation Regularization for Large Multimodal Models Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T06:12:39.481162Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.