Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Incorporating Visual Experts to Resolve the Information Loss in Multimodal Large Language Models
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2401.03105.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:25:05.227814Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T15:09:55.328591Z
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 d08684a8-7983-4e7a-bac1-9ec84b31873c · inbound
Hallucination of Multimodal Large Language Models: A Survey cites this paper.
Hallucination of Multimodal Large Language Models: A Survey Incorporating Visual Experts to Resolve the Information Loss in Multimodal Large Language Models
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T12:33:33.769884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6e104214-8a3f-4cf6-a3f9-cfc16d12487a · inbound
Mixpert: Mitigating Multimodal Learning Conflicts with Efficient Mixture-of-Vision-Experts cites this paper.
Mixpert: Mitigating Multimodal Learning Conflicts with Efficient Mixture-of-Vision-Experts Incorporating Visual Experts to Resolve the Information Loss in Multimodal Large Language Models
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:25:05.227814Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 81334f5d-63f5-4da6-8be4-d8f837c3ff1a · inbound
MCA-LLaVA: Manhattan Causal Attention for Reducing Hallucination in Large Vision-Language Models cites this paper.
MCA-LLaVA: Manhattan Causal Attention for Reducing Hallucination in Large Vision-Language Models Incorporating Visual Experts to Resolve the Information Loss in Multimodal Large Language Models
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:09:05.646100Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b21e7469-2038-42d5-85b6-e5790f74686a · inbound
METEOR: Multi-Encoder Collaborative Token Pruning for Efficient Vision Language Models cites this paper.
METEOR: Multi-Encoder Collaborative Token Pruning for Efficient Vision Language Models Incorporating Visual Experts to Resolve the Information Loss in Multimodal Large Language Models
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:18:01.418539Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6b02efb3-239e-4c5c-8549-e2fafc16d28d · inbound
From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models cites this paper.
From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models Incorporating Visual Experts to Resolve the Information Loss in Multimodal Large Language Models
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T15:09:55.330464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.