Pith. sign in

Paper Citation Record · LEDGER

AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2406.10900.

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

pith.paper-citation-record.v1
2406.10900 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:40:58.968730Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:18:56.619359Z

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 ad7278ce-b8e9-4fc0-b928-a74fcfd77ee9 · inbound

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model cites this paper.

Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:58.968730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:58.968730Z digest=sha256:85b18df1e5c4ec1e51fe83dc9b03ab0fe8cdb50dec672a1869d01da30c035244

Observation 85533a89-f4f5-42e4-a519-bbd9dd3cbd31 · inbound

From Hallucinations to Jailbreaks: Rethinking the Vulnerability of Large Foundation Models cites this paper.

From Hallucinations to Jailbreaks: Rethinking the Vulnerability of Large Foundation Models AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T12:34:36.773583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:34:36.773583Z digest=sha256:09c0ad413a5d723de497a8b744d4d56d25693c6f6a95e6c15049d2dee675aa3d

Observation cdc4c725-886e-4113-8257-8d1651bade11 · inbound

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images cites this paper.

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T05:43:35.049938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:35.049938Z digest=sha256:cb49cb3877bd824c4e2fae48079ceda64ac7862122f075caef1dcac2f68484dc

Observation ba96c738-9179-45e6-aab5-624306115f80 · inbound

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey cites this paper.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T20:28:47.015807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:28:47.015807Z digest=sha256:ccdaef0e78d6d867cca2f699fa971dd8dafa47dd6b8382783136d684299e96f6

Observation 16292844-c8d1-4df3-93e7-67e2dac2207d · inbound

MASS: Motion-Aware Spatial-Temporal Grounding for Physics Reasoning and Comprehension in Vision-Language Models cites this paper.

MASS: Motion-Aware Spatial-Temporal Grounding for Physics Reasoning and Comprehension in Vision-Language Models AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-17T05:59:08.733182Z

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=2026-05-17T05:55:11.495430Z digest=sha256:dcfe34b31cca3debe23abc4ebb692a71e421d3a0d0f72a49b45be32090990a6c

Observation 208f81bc-7599-420f-8677-ebc2ff9c4668 · inbound

MLLMs Get It Right, Then Get It Wrong: Tracing and Correcting Late-Layer Textual Bias cites this paper.

MLLMs Get It Right, Then Get It Wrong: Tracing and Correcting Late-Layer Textual Bias AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-03T20:18:56.621305Z

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=2026-06-27T01:28:50.021432Z digest=sha256:9e28695356b0654a4307ca6e84df4161f4f9714a1a5a87cdf7c2d02a45746f79

Observation 356c9562-2eb2-4a97-b227-1ce8c6c25b70 · 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 AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 77

Resolution
verified exact
arxiv_id, observed 2026-07-01T10:25:41.403835Z

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=2026-07-01T05:35:08.200219Z digest=sha256:f4bf2ad89144ff0efadcf93deb2ec65e6dfea775358bd72d6a3bc98ceb3552d6