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Paper Citation Record · LEDGER

Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2503.19622.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2503.19622 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:26:02.018102Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T10:19:47.494246Z

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 0463ea95-d515-4e75-818a-a298e5fa2aa9 · inbound

Position: Reasoning After Perception Means Reasoning Without Vision cites this paper.

Position: Reasoning After Perception Means Reasoning Without Vision Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T15:26:02.018102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:26:02.018102Z digest=sha256:810710a38ed54d6c819f7a7d882ada710287f97b0fea57411baae0f2a72e84d1

Observation 97ce195b-edf5-44bd-876c-ec9c41d713e0 · inbound

Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs cites this paper.

Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:36:44.178097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-18T18:35:01.328250Z digest=sha256:5d6212d78657f1ae92843122a242445567293aaf72783917b5a54e0c7484c7ce

Observation 47c1b3e6-57a4-4dab-94d9-c39b6b685622 · inbound

Enhancing Video Representations with Spatiotemporal-Semantic Residual to Mitigate Hallucinations in Video Large Multimodal Models cites this paper.

Enhancing Video Representations with Spatiotemporal-Semantic Residual to Mitigate Hallucinations in Video Large Multimodal Models Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-03T06:36:25.319744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:36:25.319744Z digest=sha256:4f02b184746a4f7c1bb2b952b20649ee8fdbd02631264d612cd6de706f5b86a8

Observation 884fc93a-6ad0-4eaf-a160-9d45845439b3 · inbound

Relaxing Anchor-Frame Dominance for Mitigating Hallucinations in Video Large Language Models cites this paper.

Relaxing Anchor-Frame Dominance for Mitigating Hallucinations in Video Large Language Models Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:26:03.410203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T14:54:52.710686Z digest=sha256:66962f83fdcec617e07d5e7b7ae825d4cbebad1a2e462cbfef8323ab22ccce71

Observation 2ccaa472-8b4e-4ff6-9427-76e5f5c7c32e · inbound

When Text Hijacks Vision: Benchmarking and Mitigating Text Overlay-Induced Hallucination in Vision Language Models cites this paper.

When Text Hijacks Vision: Benchmarking and Mitigating Text Overlay-Induced Hallucination in Vision Language Models Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:46:37.516386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T06:41:59.641410Z digest=sha256:e1782bfea7b9e5b41fc6c2f1ca3c0183b65415daeee9d8ea785018eb9f992789

Observation f1550ced-2296-4758-8472-36a13f95c6f1 · inbound

MultiToP: Learning to Patch Visual Tokens to Mitigate Hallucinations in Video Large Multimodal Models cites this paper.

MultiToP: Learning to Patch Visual Tokens to Mitigate Hallucinations in Video Large Multimodal Models Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:27:56.147601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-27T10:02:58.341050Z digest=sha256:36d785bb3c3cc4ed043409324f5f685e163ce42f0e6de0c9bdc05d9757210814

Observation 013e244e-4fb7-49fa-9708-13a75743d96e · inbound

MotionHalluc: Diagnosing Kinematic Hallucinations in Fine-Grained Motion Reasoning cites this paper.

MotionHalluc: Diagnosing Kinematic Hallucinations in Fine-Grained Motion Reasoning Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:19:47.495721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-26T08:58:37.673268Z digest=sha256:0d0b2a930f025183ae73c10cdfe72873370bfc376908258d64cbb421641978f1

Observation 970c98c7-f783-4042-9bea-44d19dea1eeb · inbound

DAIN: Dynamic Agent-Based Interaction Network for Efficient and Collaborative Multimodal Reasoning cites this paper.

DAIN: Dynamic Agent-Based Interaction Network for Efficient and Collaborative Multimodal Reasoning Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:04:21.395611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T06:01:20.803078Z digest=sha256:a9be8ecc71e52790ba2d01a5bd265f7beb24cd412ef2af78ad7c578046682421

Observation 415b78e4-c270-4d21-8b86-818d954b2980 · inbound

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs cites this paper.

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-07-01T10:25:41.318229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-01T05:35:08.200219Z digest=sha256:36cf2b6ad73e0c2220f0f4fd606922351bbb0825c1850dabfd1a9fbbd4249967

Observation 8674ced2-4dfa-4b5d-81f6-ad5b1491a4a8 · inbound

ProWAFT: A ROMA-LPD Instance for Workload-Aware and Dynamic Fault Tolerance in FPGA-Based CNN Accelerators cites this paper.

ProWAFT: A ROMA-LPD Instance for Workload-Aware and Dynamic Fault Tolerance in FPGA-Based CNN Accelerators Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-07-03T15:28:33.661815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-03T15:23:48.748933Z digest=sha256:789cdc07a3220198b4e390d665b04cc140ca36efda80dc0611818e79dd1f2d97