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Paper Citation Record · LEDGER

Incorporating Visual Experts to Resolve the Information Loss in Multimodal Large Language Models

As of 9 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.

pith.paper-citation-record.v1
2401.03105 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:25:05.227814Z

measured 0 of 1 external citation measurements

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T12:33:32.631346Z digest=sha256:5004931854c4697e44631fd14c41104904c380bcec0a737ea09121ba7129ca5d

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.

source=pdf_text observed=2026-08-07T12:25:05.227814Z digest=sha256:088c813fca22957128e8fddde015d424907b9a2824be23570138b4f461e954b6

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.

source=pdf_text observed=2026-08-06T18:09:05.646100Z digest=sha256:9c14f97b07ea923bb44f56a45873a651cbac810df78e31f9370660e4be3d93a7

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.

source=pdf_text observed=2026-08-06T13:18:01.418539Z digest=sha256:f0e7d516a5a6f18fa83bd4b3e9b92a2b7f7722a7d9d835e073ad6aef0b35bcb8

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T01:50:54.242508Z digest=sha256:f2b20005d47125d405abfef73986fd2bb7f033ae16313270d035e0bedf7244f1