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Paper Citation Record · LEDGER

Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2408.09429.

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

pith.paper-citation-record.v1
2408.09429 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:42:39.211105Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T06:14:19.277132Z

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 fe14f953-bbb1-404b-9ca8-8c6ece7482a9 · inbound

Hallucination of Multimodal Large Language Models: A Survey cites this paper.

Hallucination of Multimodal Large Language Models: A Survey Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 221

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:33:33.447852Z

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=sha256:5917619181538b82dfea678480574981fc48fccb41dd4f11631a3dc655d34471

Observation 26e69ea4-d823-4e60-88c0-5da7588b24d4 · inbound

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection cites this paper.

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:13:24.681459Z

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=arxiv_source observed=2026-05-23T20:10:59.264484Z digest=sha256:a614121889615fb2f49cf9e83a845fda12b0c9e36d32dd64c587af51e502bb84

Observation d0956ce7-fe6e-479f-9a1b-770901ad5d0b · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 262

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:32:32.573195Z

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=arxiv_source observed=2026-05-23T04:30:38.804702Z digest=sha256:1e241c40058ccc3e916d64182c9332bb58c427bcc12b9387ed4ba86a5e61d1c0

Observation 039303be-362f-43c2-a3dd-a7334c2e3ae0 · inbound

CAFES: A Collaborative Multi-Agent Framework for Multi-Granular Multimodal Essay Scoring cites this paper.

CAFES: A Collaborative Multi-Agent Framework for Multi-Granular Multimodal Essay Scoring Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:39.211105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:42:39.211105Z digest=sha256:57ebd7ecec151edd0616dab0f143065ecb504ce6c8d0da0bbb61dd113bcfce42

Observation 1ab64307-bc9c-4e40-bf65-9952f29c3e1a · inbound

Pierce the Mists, Greet the Sky: Decipher Knowledge Overshadowing via Knowledge Circuit Analysis cites this paper.

Pierce the Mists, Greet the Sky: Decipher Knowledge Overshadowing via Knowledge Circuit Analysis Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T15:39:21.868847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:39:21.868847Z digest=sha256:150b08e29e7bf527a14b75ecbef65a84d95cd008eb8c5a28cc64671971a3cec0

Observation 024b687b-ba56-4761-b2c7-6e02fdea8397 · inbound

GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning cites this paper.

GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T00:59:54.687764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:59:54.687764Z digest=sha256:0087a332cd7a1b09a321c9a2cdd7fa12d86466374ba75c4ef153709b123cbaad

Observation aab9b760-309d-4689-8ab9-86a6933752ee · inbound

Unveiling the Response of Large Vision-Language Models to Visually Absent Tokens cites this paper.

Unveiling the Response of Large Vision-Language Models to Visually Absent Tokens Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-05T11:15:21.804745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:15:21.804745Z digest=sha256:d0ad3591e3338f94b4444d383e611c64ddfd521adc156d854302411b4a08be27

Observation 59435987-101f-430d-9c59-ffc0a1f19e2e · inbound

Measuring Epistemic Humility in Multimodal Large Language Models cites this paper.

Measuring Epistemic Humility in Multimodal Large Language Models Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-04T18:49:39.326525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:49:39.326525Z digest=sha256:3521e116655deaf296eabcb0d582fa81dfe8b1889a3ab9e8e480b2ea93199199

Observation 39cbe1e5-6c6d-4751-8973-71a902410f1a · inbound

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise cites this paper.

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:21:09.174267Z

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=2026-05-08T17:40:14.089081Z digest=sha256:1a6c5a05ccb7475fbdd7c2c6b9a9946f3aaa71c7b37806a22cc461f7c0403d47

Observation 81aed7bf-e75e-49ac-9e86-b3d485180fba · inbound

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise cites this paper.

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:51:29.231277Z

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=2026-05-12T03:52:44.531016Z digest=sha256:a547d47e2cd10de143862ab7f6d37aaeb10f791797ad3fe89dbd973d407f632c

Observation bb0a3ef7-248e-4e64-bb70-58b88fbb4c71 · inbound

When Looking Is Not Enough: Visual Attention Structure Reveals Hallucination in MLLMs cites this paper.

When Looking Is Not Enough: Visual Attention Structure Reveals Hallucination in MLLMs Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:57:05.278955Z

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=2026-05-13T01:55:07.172228Z digest=sha256:e3c90455cb0173a90bd780c84ccab7c2ff6827a25d0e1ec11571723bb5e90d24

Observation b556ecc5-ea23-4e1f-bc04-b7b5a82ada69 · inbound

Consistency as Inductive Bias: Learning Cross-View Invariance for Robust Multimodal Reasoning cites this paper.

Consistency as Inductive Bias: Learning Cross-View Invariance for Robust Multimodal Reasoning Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:14:19.279010Z

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=2026-06-30T06:10:41.786328Z digest=sha256:c5cc7cc01f643a89f1eddd540a858b4be24edf4d7c4abdcadb349788448bb17e