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Paper Citation Record · LEDGER

ARGUS: Hallucination and Omission Evaluation in Video-LLMs

As of 7 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 3 inbound Pith citation observations for arXiv:2506.07371.

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

pith.paper-citation-record.v1
2506.07371 v2

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:41:39.882037Z

measured 86 of 86 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T19:27:29.843866Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T12:15:01.137692Z

Reference resolution

83 of 83 outbound references displayed

  • verified exact1
  • verified fuzzy32
  • unresolved49
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 590dd849-9fdc-4cb2-9c2a-a8d657e5fcdf · outbound

This paper cites https://huggingface.co/ blog/smolvlm2, 2025.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs https://huggingface.co/ blog/smolvlm2, 2025

Reference 1

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source=pdf_text observed=2026-08-07T05:41:39.567708Z digest=sha256:f2da827ee4eaa4d8c0be01849c8c51eeb27948193bb9aa9aa4eac5d2910e4d33

Observation 53434356-bcfc-4a62-85aa-714e81b14705 · outbound

This paper cites GPT-4 Technical Report.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs GPT-4 Technical Report

Reference 2

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source=pdf_text observed=2026-08-07T05:41:39.572337Z digest=sha256:83ec1c0e57689ec867093b9bb292f451a7d807af0d9eea3190e4f392ef7d4091

Observation 97e9437a-4105-4dda-b307-0f1fcec02fb2 · outbound

This paper cites Are language models better at generating an- swers or validating solutions?, 2025.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Are language models better at generating an- swers or validating solutions?, 2025

Reference 3

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source=pdf_text observed=2026-08-07T05:41:39.576307Z digest=sha256:ac49c651d1ff59ee96fe7475c2f84fedd098f07354d196d956d8923e23c06189

Observation 594055c8-92bc-44cd-8a98-098970bdff97 · outbound

This paper cites The snli corpus.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs The snli corpus

Reference 4

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source=pdf_text observed=2026-08-07T05:41:39.580023Z digest=sha256:e789e1c8b032e7c2f8d95241756b1641a9fb999e0027e7ea1803fb56ec12739f

Observation 23e3db30-430d-4ab3-938e-ffee2a357ce6 · outbound

This paper cites Activitynet: A large-scale video benchmark for human activity understanding.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Activitynet: A large-scale video benchmark for human activity understanding

Reference 5

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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.

source=pdf_text observed=2026-08-07T05:41:39.583724Z digest=sha256:30fa8628386083d4d5d773d8e8b6b8135c6ca6291623a82f60483dd6f1851511

Observation b0071cc1-0381-46c1-bc38-2c8f19ae1834 · outbound

This paper cites e-snli: Natural language inference with natural language explanations.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs e-snli: Natural language inference with natural language explanations

Reference 6

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:41:39.587569Z digest=sha256:aedb7f53ef19afde3a4c4367eb090721238decdec1f1cdc4f0fc76e20ddbec82

Observation ea527a28-a167-4066-bada-0ccd3e18f566 · outbound

This paper cites AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark

Reference 7

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source=pdf_text observed=2026-08-07T05:41:39.591343Z digest=sha256:9d78abcacd3ff5ce30e63389297cd41fad42185940d799c73868eeaf49efef7a

Observation de01e0d6-572a-471e-be62-177d0913e4fd · outbound

This paper cites Panda-70m: Captioning 70m videos with multiple cross-modality teachers.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Panda-70m: Captioning 70m videos with multiple cross-modality teachers

Reference 8

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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.

source=pdf_text observed=2026-08-07T05:41:39.595465Z digest=sha256:31b023fb8c1e799c0a2197bbc05d74cca039a0824a4196eec2b357e1a6096532

Observation e3b75960-d454-47e7-94a1-33433d9612bc · outbound

This paper cites NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning

Reference 9

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local_arxiv, observed 2026-08-07T05:41:40.503375Z

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.

source=pdf_text observed=2026-08-07T05:41:39.599610Z digest=sha256:25930ee39f133025964e9ae1fbefe54e10f969334d8f3e6421a9bae683ef3d24

Observation 8f774eab-0042-4aef-909f-e623f53af606 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 10

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source=pdf_text observed=2026-08-07T05:41:39.603674Z digest=sha256:f1480d5bbfded2f141f1a1eb831e0d1aa6c91d3448fc8d9495c157889741f4cf

Observation daada15a-9842-4e3e-9409-13fce30079e2 · outbound

This paper cites How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Reference 11

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source=pdf_text observed=2026-08-07T05:41:39.607296Z digest=sha256:2b731453650a3661dab57ff8816a7001ce41869bf918326fb58e21ebd441e0e4

Observation 8ff0d009-fb19-4dac-9bd3-b6c8c90a9cfa · outbound

This paper cites VidHal: Benchmarking Temporal Hallucinations in Vision LLMs.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs VidHal: Benchmarking Temporal Hallucinations in Vision LLMs

Reference 12

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source=pdf_text observed=2026-08-07T05:41:39.611326Z digest=sha256:af994881ad74984a5123438b821413d9304b73d26a4697456fd66f0b499931b1

Observation 8790372f-2667-4003-8322-fb3d0e44679f · outbound

This paper cites Transforming Question Answering Datasets Into Natural Language Inference Datasets.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Transforming Question Answering Datasets Into Natural Language Inference Datasets

Reference 13

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source=pdf_text observed=2026-08-07T05:41:39.615131Z digest=sha256:430b68677d5d78cda9e3ab8492e787c914fed3bc4e02e75d571cc901fadbb017

Observation cc096888-3b71-41e3-b9eb-acd30d47cd74 · outbound

This paper cites Sketch, ground, and refine: Top-down dense video caption- ing.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Sketch, ground, and refine: Top-down dense video caption- ing

Reference 14

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raw_fallback, observed 2026-08-07T05:41:40.978542Z

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.

source=pdf_text observed=2026-08-07T05:41:39.618862Z digest=sha256:2449a2a4e91349dc47cfbebbf415c452c75be1197daefb416bd09306c2701b91

Observation 0f633d05-c3ae-4abc-99e4-cdd89b624e87 · outbound

This paper cites diffusers/shot-categorizer-v0.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs diffusers/shot-categorizer-v0

Reference 15

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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.

source=pdf_text observed=2026-08-07T05:41:39.622535Z digest=sha256:1841937fb61497305f6b6c43c5b4f34980aa87de8d6bbff3ab7bb78ea0f0f3e5

Observation 11436196-dc89-46e8-992c-55015e1c57bb · outbound

This paper cites Eva: Exploring the limits of masked visual representa- tion learning at scale.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Eva: Exploring the limits of masked visual representa- tion learning at scale

Reference 16

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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.

source=pdf_text observed=2026-08-07T05:41:39.626122Z digest=sha256:d04697d9a75de408abff2323a99702332a2322b70c4a11b1265e5858dab89513

Observation f9d3a925-7cf2-41e0-8c54-ce28d147afb5 · outbound

This paper cites TC-Bench: Benchmarking Temporal Compositionality in Text-to-Video and Image-to-Video Generation.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs TC-Bench: Benchmarking Temporal Compositionality in Text-to-Video and Image-to-Video Generation

Reference 17

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source=pdf_text observed=2026-08-07T05:41:39.629628Z digest=sha256:c45ceb07ee033f669f5aad3c21431aedf48b85bae0c5063bdf9a46f6590e2a5d

Observation 7f920541-4fe9-4695-b8a7-0ec9e816b893 · outbound

This paper cites Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 18

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source=pdf_text observed=2026-08-07T05:41:39.633535Z digest=sha256:46d069efd4212dc1e3b1276548eb7c3ca14c53c29ea4cb08fee0bf0edf08a62e

Observation 604cd840-4811-4ca3-a5b2-7c32a906c890 · outbound

This paper cites TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models

Reference 19

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source=pdf_text observed=2026-08-07T05:41:39.637353Z digest=sha256:a8f697be526441ea190e4c38d184b248bb11c9434c321683abf88029d62646f9

Observation 853c9b63-4469-4c28-985b-029a6dc028ad · outbound

This paper cites The Llama 3 Herd of Models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs The Llama 3 Herd of Models

Reference 20

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source=pdf_text observed=2026-08-07T05:41:39.641007Z digest=sha256:1ad40b08066aa6f2fab7ddf88901bc6d7ec6a04b330ec29b6f6429e88f2a7412

Observation e5e70f61-5368-4429-8731-bf0fa61fdcde · outbound

This paper cites Ego4d: Around the world in 3,000 hours of egocentric video.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Ego4d: Around the world in 3,000 hours of egocentric video

Reference 21

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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.

source=pdf_text observed=2026-08-07T05:41:39.644523Z digest=sha256:34573924343e1bb66d2196d50c92c099d3192ea3cbfcdc6a3d5b9efb97ee5381

Observation 497078f1-6181-4f4c-8d86-578b877f8d17 · outbound

This paper cites Hallusionbench: an advanced diagnos- tic suite for entangled language hallucination and visual il- lusion in large vision-language models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Hallusionbench: an advanced diagnos- tic suite for entangled language hallucination and visual il- lusion in large vision-language models

Reference 22

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:41:39.648115Z digest=sha256:4908842002852f7e2eaf9ae94324c6de49495028c3c6db3d691f6cfc861feb8a

Observation 8e79c9fe-81c7-4c4b-871e-10cfeb9b434c · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 23

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source=pdf_text observed=2026-08-07T05:41:39.652319Z digest=sha256:974c5aa2f5a3dd19bdc593ef2854067ba3c1b89563fcb7166254e14d5d8f5538

Observation 78b48fdc-9398-45be-8cdf-acb5b6892294 · outbound

This paper cites CIEM: Contrastive Instruction Evaluation Method for Better Instruction Tuning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs CIEM: Contrastive Instruction Evaluation Method for Better Instruction Tuning

Reference 24

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source=pdf_text observed=2026-08-07T05:41:39.656753Z digest=sha256:a071549a4766dc0321d5891e9cb6604bba84f9f6664ccbdfcd9e23af170d8798

Observation 9d6a5c6b-4b6b-4c48-a86b-7691c995894f · outbound

This paper cites A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer

Reference 25

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source=pdf_text observed=2026-08-07T05:41:39.660603Z digest=sha256:3cc4506f2cfe77fe13a78ab7d01e699049612e4b6579088fb81d60b96ffcde05

Observation 842241d2-a3ab-4efa-8959-58b73cfcc793 · outbound

This paper cites Multi-modal dense video captioning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Multi-modal dense video captioning

Reference 26

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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.

source=pdf_text observed=2026-08-07T05:41:39.664440Z digest=sha256:200473414f6693310b8566f05fd7bf87f8c8b9b7f9dbe2db581b832db8b7395d

Observation c9a6224b-e33c-4b5d-8107-1ccf937b0b42 · outbound

This paper cites FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models

Reference 27

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source=pdf_text observed=2026-08-07T05:41:39.667967Z digest=sha256:27395ba00b5cdeaf628c66962505910e64cd64e1e51d39de183ac66001aa2575

Observation bb8401a1-1690-4515-8742-939acb8bcdab · outbound

This paper cites Throne: An object-based hallucination benchmark for the free-form generations of large vision-language models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Throne: An object-based hallucination benchmark for the free-form generations of large vision-language models

Reference 28

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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.

source=pdf_text observed=2026-08-07T05:41:39.672119Z digest=sha256:b83c5c8f36e89f1228db2fcca38f476bda4304dd5c4ce904e672dd21454b328a

Observation dc8eae4b-c5fa-4bfa-a9b4-4288505245ed · outbound

This paper cites Do you remember? dense video captioning with cross-modal memory retrieval.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Do you remember? dense video captioning with cross-modal memory retrieval

Reference 29

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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.

source=pdf_text observed=2026-08-07T05:41:39.675772Z digest=sha256:31540a0e36469c5d093c52e7fe2e811d2fc313f52d6b8ac997a1e20d9ccd7fe7

Observation 0a44e6d2-41bf-4282-94e6-6f4739e841e9 · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs LLaVA-OneVision: Easy Visual Task Transfer

Reference 30

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source=pdf_text observed=2026-08-07T05:41:39.679348Z digest=sha256:74f0ca712c0da2d652e41b945a60c08fc18202603e6bcd08b620055cf132bafc

Observation 9e51ca5a-fd6e-436d-8e09-b1acf0016e1a · outbound

This paper cites LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods

Reference 31

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source=pdf_text observed=2026-08-07T05:41:39.683048Z digest=sha256:fbcaea7c247c809d47f0a7c6f3ea91ab299d0ea2b67d126365f23f12d3ff2781

Observation 3235d002-c515-44c3-bca8-56d0f099ac3c · outbound

This paper cites Jointly localizing and describing events for dense video captioning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Jointly localizing and describing events for dense video captioning

Reference 32

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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.

source=pdf_text observed=2026-08-07T05:41:39.687410Z digest=sha256:0215620f94ec71ee3c95f7f0fbd6e14d606bf27db3cfa775eb8fd864c4a7d003

Observation 0faea484-9839-4129-a027-1a92b565eff9 · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Evaluating Object Hallucination in Large Vision-Language Models

Reference 33

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source=pdf_text observed=2026-08-07T05:41:39.691477Z digest=sha256:a8e6dd1e6b7e25fab57aa54c457f5e246f8be63dc83a877d853ee51e3106f613

Observation ecbdd126-2c17-4950-8c3c-f65d8f2cea17 · outbound

This paper cites Revisiting the Role of Language Priors in Vision-Language Models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Revisiting the Role of Language Priors in Vision-Language Models

Reference 34

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source=pdf_text observed=2026-08-07T05:41:39.695176Z digest=sha256:4cdd28e4e6186e73c488bee87b9234d384fd2537e903d79d1886c870a22b9a69

Observation f391b0fa-d002-4c69-bccb-db675f60a44d · outbound

This paper cites DeepSeek-V3 Technical Report.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs DeepSeek-V3 Technical Report

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.699034Z digest=sha256:f9c78a78d20973a95b3d5021c5da348672e3e6ae9c0ec5856bccb23215d21a6a

Observation 64f98fc9-7c03-41f9-8be1-ef8aa579352d · outbound

This paper cites Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 36

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source=pdf_text observed=2026-08-07T05:41:39.702539Z digest=sha256:311451e0ef41893e05df64919a2948b296e2e482ebebd765d990c7ff8cb6fa23

Observation 7ccf135e-3002-481c-b3af-6b83f96d1452 · outbound

This paper cites A Survey on Hallucination in Large Vision-Language Models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs A Survey on Hallucination in Large Vision-Language Models

Reference 37

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source=pdf_text observed=2026-08-07T05:41:39.706447Z digest=sha256:0abbca8c0d0f80baac01641a855e9e44d42c39e5fa13800fb0b80ccf66425349

Observation e2b20e15-00a1-4698-bfd0-95a6354a65c2 · outbound

This paper cites Logical Reasoning in Large Language Models: A Survey.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Logical Reasoning in Large Language Models: A Survey

Reference 38

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source=pdf_text observed=2026-08-07T05:41:39.710210Z digest=sha256:71b4aac82c5916e19650fe2b887cea01393fe22fe8526765fee58b1066da85ed

Observation 9330aa65-f803-4b44-b874-5622c5d3b6e6 · outbound

This paper cites Egoschema: A diagnostic benchmark for very long- form video language understanding.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Egoschema: A diagnostic benchmark for very long- form video language understanding

Reference 39

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raw_fallback, observed 2026-08-07T05:41:40.873149Z

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.

source=pdf_text observed=2026-08-07T05:41:39.714030Z digest=sha256:24483b709b2897334ae2d25fad402fcc41d52311063e1cafa9d9207446a3b928

Observation d20a118c-b451-4449-931b-f595327e946e · outbound

This paper cites Streamlined dense video captioning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Streamlined dense video captioning

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.861710Z

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.

source=pdf_text observed=2026-08-07T05:41:39.717536Z digest=sha256:98d4ffc24b522741f0da4b3fce8aba16d3b21a9fc59ba02d451c8c101cfa9f43

Observation 40e8b251-8ace-4e9d-ba64-119b03a54a5b · outbound

This paper cites Neptune: The Long Orbit to Benchmarking Long Video Understanding.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Neptune: The Long Orbit to Benchmarking Long Video Understanding

Reference 41

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.721179Z digest=sha256:91f94bbbab4e1ee887d94056d5e52a474d5d500d88a0ccbb8771c8674a8afa09

Observation d340bd51-3c6c-4172-b062-c3df7d13eb43 · outbound

This paper cites MINERVA: Evaluating Complex Video Reasoning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs MINERVA: Evaluating Complex Video Reasoning

Reference 42

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.724979Z digest=sha256:a479515ec6cc65504da0e4ef83dc8724ac7490182b9111a65cb68b3206b1b3b9

Observation 28a66fb7-a3a0-4adf-b23a-f80e97d8af3a · outbound

This paper cites an unresolved cited work.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work

Reference 43

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raw_fallback, observed 2026-08-07T05:41:40.849414Z

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.

source=pdf_text observed=2026-08-07T05:41:39.729103Z digest=sha256:5cb93fd27dd9c09fa9b87fc5b26c045d696ac86b41f4523cafdd5bf5b47f92f7

Observation cb402e6e-1dd4-485f-83f1-c6ef69ce98b7 · outbound

This paper cites Per- ception test: A diagnostic benchmark for multimodal video models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Per- ception test: A diagnostic benchmark for multimodal video models

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.838364Z

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.

source=pdf_text observed=2026-08-07T05:41:39.732461Z digest=sha256:fa5386226a2041a0c20660f273ad5c382f6f70d4c58bbe9738f699678d3cb690

Observation fc36960e-67ce-4338-be28-82def6011f08 · outbound

This paper cites Dense video captioning: A survey of techniques, datasets and evalu- ation protocols.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Dense video captioning: A survey of techniques, datasets and evalu- ation protocols

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.827001Z

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.

source=pdf_text observed=2026-08-07T05:41:39.736074Z digest=sha256:df65970e580c48d3c28507a89a67da8c86684974fbcd5676e8b25da4d4eb1de4

Observation d9522d15-3ffc-4202-8232-b29cd8fb2c3f · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Learning transferable visual models from natural language supervi- sion

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.815178Z

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.

source=pdf_text observed=2026-08-07T05:41:39.739626Z digest=sha256:4c21cd269a6d9e0955c126fecd9679e8b00d417ec822bfde5cf701efe17899ff

Observation 8b0b80fd-8d51-4c1e-8171-e57f3938b3aa · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs SAM 2: Segment Anything in Images and Videos

Reference 47

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no resolver link, observed 2026-08-07T05:41:39.743102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.743102Z digest=sha256:32e29ab09878fa361f5b4aa3b9d4a39b3e6111530d45cb04ed48bb99783b2662

Observation c327895c-27f6-407b-a9e4-89b92372a249 · outbound

This paper cites CinePile: A Long Video Question Answering Dataset and Benchmark.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.746918Z digest=sha256:c50b4a52d43cbe4d17444e9b2d39e961f3202e0af9ba70bf57eebfbd667759a4

Observation 3474a064-b49d-4ea5-a3d0-0a392fdbebd6 · outbound

This paper cites Object Hallucination in Image Captioning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Object Hallucination in Image Captioning

Reference 49

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no resolver link, observed 2026-08-07T05:41:39.750672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.750672Z digest=sha256:d18dd985f02507af0994fa27826f4a214fc3f1f9d4d1ef628c052d2109f96538

Observation bfc6ec04-dc45-4cbe-b75c-726f0cd293ea · outbound

This paper cites FENICE: Factuality Evaluation of summarization based on Natural language Inference and Claim Extraction.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs FENICE: Factuality Evaluation of summarization based on Natural language Inference and Claim Extraction

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.754931Z digest=sha256:c85fb17805203234465c3b876feef442f548e41d1d47ae924887d5a906ec9366

Observation 968c5eb9-0ece-4a9d-b022-39ef207dc3b0 · outbound

This paper cites Aligning Large Multimodal Models with Factually Augmented RLHF.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 51

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no resolver link, observed 2026-08-07T05:41:39.758699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.758699Z digest=sha256:8c5ac2f352501752f153d1caa7d129ae846dcbee422657a385d6b0c22a57fd8d

Observation 032d637b-cfd8-4f28-90b0-4a4a011601a5 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Gemini: A Family of Highly Capable Multimodal Models

Reference 52

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no resolver link, observed 2026-08-07T05:41:39.762539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.762539Z digest=sha256:9159f05c2e71dbb9a87d96d4167a6454ff68904aed513632b16cec16e3941a6d

Observation 78c9d01d-10fd-482b-a514-635336999edc · outbound

This paper cites Laion-aesthetics predictor v1.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Laion-aesthetics predictor v1

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.802807Z

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.

source=pdf_text observed=2026-08-07T05:41:39.766700Z digest=sha256:4a9fe0d76a4e87b54e5f7f969128869b5800a085fbe5e67114df01acf0ea1419

Observation b189f98f-a727-4500-ab51-687af6709944 · outbound

This paper cites Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.777404Z

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.

source=pdf_text observed=2026-08-07T05:41:39.774382Z digest=sha256:b2e309f04fd6072df12b920013762e32bc26ffa77de50830926cf95e4245ccf3

Observation beccbad5-5d4a-48a8-9403-44c96a1d2121 · outbound

This paper cites AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation

Reference 55

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.778625Z digest=sha256:792d136bff6a2ccf5fe97dcd604ea4fe99209ecae1a35c2815b78bf71d838d63

Observation 272f68dc-8c74-48c3-841d-1b0aea410c5a · outbound

This paper cites End-to-end dense video captioning with parallel decoding.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs End-to-end dense video captioning with parallel decoding

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.764422Z

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.

source=pdf_text observed=2026-08-07T05:41:39.782388Z digest=sha256:e0ecdedb0e2e873ea5e94cccc942b08a26ca4af4d609bea251bcc70a9969ef5b

Observation 46706f6f-7aae-4888-9b32-f568e6a899ee · outbound

This paper cites LVBench: An Extreme Long Video Understanding Benchmark.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs LVBench: An Extreme Long Video Understanding Benchmark

Reference 57

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no resolver link, observed 2026-08-07T05:41:39.786245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.786245Z digest=sha256:191d91ef00e01c2dbc2c45524ce93e4bc13343280cf36348438ceb0fc0faeb84

Observation d7d201a4-5e4f-4a6d-b11d-e3d890e46e7a · outbound

This paper cites VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models

Reference 58

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no resolver link, observed 2026-08-07T05:41:39.790898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.790898Z digest=sha256:91afe6e4c7bd89a0e4c3d56c492cef578aea739313d639557fc62a512641d929

Observation 237327f6-1c10-4e24-9a56-bc0da2a5377d · outbound

This paper cites A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

Reference 59

Resolution
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no resolver link, observed 2026-08-07T05:41:39.795166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.795166Z digest=sha256:3f883590c14efdc9ccc49f1a9ec849630710c9dee72217fc485be705cb59b5c5

Observation 7121c4c7-ecc8-4b16-883c-ddc3e5f5fa3b · outbound

This paper cites ANLIzing the Adversarial Natural Language Inference Dataset.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs ANLIzing the Adversarial Natural Language Inference Dataset

Reference 60

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.799211Z digest=sha256:ab1387a984c91814e33544a6620aea0d15560969523033d72f0467e43fb63eeb

Observation 9981f233-237e-49e4-ac79-383070b7792c · outbound

This paper cites Joint event detection and description in continuous video streams.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Joint event detection and description in continuous video streams

Reference 61

Resolution
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raw_fallback, observed 2026-08-07T05:41:40.751725Z

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.

source=pdf_text observed=2026-08-07T05:41:39.802826Z digest=sha256:6aee6099a92967db48a511d50d37e6c6374e9297e81749e94cb065e5ba1c603e

Observation c428ba8b-8618-4704-899e-92a1a8d914a6 · outbound

This paper cites Qwen2.5 Technical Report.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Qwen2.5 Technical Report

Reference 62

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.806096Z digest=sha256:61b904f242866a1de862d52b47d8b23c87f13c8d6a8ba29f08956be77eeb31e4

Observation f4cc3595-ad19-4bfd-85b0-93f590950b96 · outbound

This paper cites mplug- owl3: Towards long image-sequence understanding in multi- modal large language models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs mplug- owl3: Towards long image-sequence understanding in multi- modal large language models

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.739115Z

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.

source=pdf_text observed=2026-08-07T05:41:39.809799Z digest=sha256:2219c3908665e59b73a13dce815cf29e2975de618bdd317062de352929ef9611

Observation 60c2cd09-2368-4c53-911d-ff2627913e71 · outbound

This paper cites Sigmoid loss for language image pre-training.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Sigmoid loss for language image pre-training

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.726197Z

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.

source=pdf_text observed=2026-08-07T05:41:39.813223Z digest=sha256:aeafef851560c6b677ca64ff07b54624bd5df5802a96a81b8d1d27a9981fbde4

Observation ab331a25-ef26-468e-ad59-7ec1fcd9dcda · outbound

This paper cites Eventhallusion: Diagnosing event hal- lucinations in video llms.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Eventhallusion: Diagnosing event hal- lucinations in video llms

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:39.816835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.816835Z digest=sha256:4b7b4a941ae3857f4e7e139ab6c6d6c41cc8c09545b65ca2aa5364362261e821

Observation 7b627c57-0fa4-443d-aa50-408e9acd89d6 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.Advances in Neural Information Processing Systems, 36:46595–46623, 2023.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Judging llm-as-a-judge with mt-bench and chatbot arena.Advances in Neural Information Processing Systems, 36:46595–46623, 2023

Reference 66

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no resolver link, observed 2026-08-07T05:41:39.820651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.820651Z digest=sha256:f0e32ec89bd631e7a96eea005b95696a8bfe1922641146c3c7082e42b1965345

Observation d81ab276-303d-48da-a435-cf4ae4673279 · outbound

This paper cites Streaming dense video captioning.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Streaming dense video captioning

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.706493Z

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.

source=pdf_text observed=2026-08-07T05:41:39.824330Z digest=sha256:0cfb527d10906744f9b55d57124167d08f22afc6a50111dc5acd47a89dcec4fa

Observation 1645717c-29a1-4eb3-8e9f-e7e2978c2325 · outbound

This paper cites Apollo: An Exploration of Video Understanding in Large Multimodal Models.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Apollo: An Exploration of Video Understanding in Large Multimodal Models

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:39.827734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.827734Z digest=sha256:2f61dbee2dfafcbb53aa2012f2537178b2415644e4ea47fde95c4d565c3af694

Observation 9bc41f06-770e-412a-8654-003eee6d9964 · outbound

This paper cites In our setting, we adapt this score by computing the average aesthetic score across all frames in a video.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs In our setting, we adapt this score by computing the average aesthetic score across all frames in a video

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.695010Z

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.

source=pdf_text observed=2026-08-07T05:41:39.832859Z digest=sha256:5f73af157556ea594294482fdd9086580820ef6449923832706ab6267f9076ec

Observation a92f3c8c-df99-4e6f-aadd-e7b7c0d94160 · outbound

This paper cites diffusers/shot-categorizer-v0 [15] to identify the lighting type in each frame of a video.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs diffusers/shot-categorizer-v0 [15] to identify the lighting type in each frame of a video

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.683387Z

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.

source=pdf_text observed=2026-08-07T05:41:39.836490Z digest=sha256:119d743d8dbdb144d10d33e2d55e6c43e20979e7f31604add4455c0196c69920

Observation b1979757-13bc-4feb-afa8-5ffe89da3e24 · outbound

This paper cites a person is cooking,.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs a person is cooking,

Reference 72

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T05:41:40.672044Z

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.

source=pdf_text observed=2026-08-07T05:41:39.840081Z digest=sha256:3006fc81a529dd0e06df71873ea6ca08fbde289864f3ee5c463b2912c9943096

Observation b5dc5497-1941-4a4e-a037-0e819dc33584 · outbound

This paper cites an unresolved cited work.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work

Reference 73

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:41:40.660632Z

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.

source=pdf_text observed=2026-08-07T05:41:39.844299Z digest=sha256:314277b0612679c8ae66edc11c8f7d4674152985209b61192820fdec6830bb2e

Observation a1c91468-e8e7-4dcd-8dfd-409e2c306c54 · outbound

This paper cites - **Contradiction**: Contains information that directly conflicts and is unsupported by the source_caption.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs - **Contradiction**: Contains information that directly conflicts and is unsupported by the source_caption

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.649092Z

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.

source=pdf_text observed=2026-08-07T05:41:39.848075Z digest=sha256:85e22be98dcc73771de437d5cf2b6e2131e5b2ca78e788adf08d9bbb8b6bad54

Observation 727e4eac-d3d9-4867-a2e0-5c17aad0d6db · outbound

This paper cites "" {source_caption}.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs "" {source_caption}

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.637407Z

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.

source=pdf_text observed=2026-08-07T05:41:39.851733Z digest=sha256:01cd190d9f2f2b6251ddfaffdb427c20477f7d935927416ab7d469038a4f0f42

Observation 85d31883-22d3-4a3e-b194-0a7dc71a8c82 · outbound

This paper cites SUNFEAST PASTA TREAT,.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs SUNFEAST PASTA TREAT,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.625690Z

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.

source=pdf_text observed=2026-08-07T05:41:39.855285Z digest=sha256:de821450365bbcfdf7398e423e97a194e2d13acb71480fc3e84990ce66796159

Observation 874c3d87-e3e1-44de-ac49-63f4c3ab4484 · outbound

This paper cites an unresolved cited work.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work

Reference 77

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:41:40.614091Z

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.

source=pdf_text observed=2026-08-07T05:41:39.858986Z digest=sha256:7867ac39d59809a726257c53050fbc98938c5aa4c5b675325907d7472f31dfd7

Observation 3ab7b8ee-7814-4c1e-aec7-01350acc8e0b · outbound

This paper cites Sunfeast Pasta Treat.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Sunfeast Pasta Treat

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.602040Z

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.

source=pdf_text observed=2026-08-07T05:41:39.863928Z digest=sha256:8e98f62a16d4cb753a2ec454a9b8c981021d43414bc36196602d84cb0f43fa37

Observation 2699120f-4ad9-4311-94d9-262fa15f5fa6 · outbound

This paper cites an unresolved cited work.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work

Reference 79

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:41:40.588373Z

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.

source=pdf_text observed=2026-08-07T05:41:39.867425Z digest=sha256:f1f4c5cf3ba7bf5439787f0e78096fd940f521ce88b568dec193504a51427823

Observation a3a9c83b-57be-44b6-9dae-4d84078b2644 · outbound

This paper cites an unresolved cited work.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work

Reference 80

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:41:40.576484Z

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.

source=pdf_text observed=2026-08-07T05:41:39.871096Z digest=sha256:c5b3c7bd728fb54980421b8894e50c5791dbf20f304dd970d3593660f924a774

Observation ed7cf2fa-d875-45eb-9b67-1e041f8e2702 · outbound

This paper cites an unresolved cited work.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work

Reference 81

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:41:40.564348Z

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.

source=pdf_text observed=2026-08-07T05:41:39.874517Z digest=sha256:fad823bc4fe62817b19510e9368ef00e80abd662a43cf80522675a1fa77adbe2

Observation 87586a80-fd26-450d-8225-09c6a45c0483 · outbound

This paper cites Recipe Card.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Recipe Card

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.552588Z

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.

source=pdf_text observed=2026-08-07T05:41:39.878424Z digest=sha256:c0d7e6e1f218d0a59c063a6895dcc56b255526d4250381a8cbb0cbcb5b625e0d

Observation fb88127b-ae8a-4e03-a2b4-ac02c886da56 · outbound

This paper cites Quick and Easy.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Quick and Easy

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:40.540599Z

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.

source=pdf_text observed=2026-08-07T05:41:39.882037Z digest=sha256:6172c3d1e90ae6a5e554ecaa76c2d61650cc47e1f4d8be7dc98ee48a4619e7d7

Observation 278b13a9-a20b-4cf0-8118-c70e186f7894 · outbound

This paper cites an unresolved cited work.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work

Reference 2022

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:41:40.790525Z

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.

source=pdf_text observed=2026-08-07T05:41:39.770832Z digest=sha256:ae4eb9cc2f9482940d2239f39e46f161554c95f58a9b921a62c9a429cdd0d7be

Pith citing papers

Observation 5b0bf116-a3cc-4bbf-a064-779e84b2e2d4 · inbound

Towards Temporal Compositional Reasoning in Long-Form Sports Videos cites this paper.

Towards Temporal Compositional Reasoning in Long-Form Sports Videos ARGUS: Hallucination and Omission Evaluation in Video-LLMs

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-08T21:34:15.466797Z

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.

source=pdf_text observed=2026-05-08T12:45:50.422679Z digest=sha256:fc1d15be6f6a86a5d597efc70f7448f01bb716b6cef44cf519b926ff6884f86e

Observation a51a5976-a148-47b5-b556-9b23dbc5f62a · inbound

Towards Temporal Compositional Reasoning in Long-Form Sports Videos cites this paper.

Towards Temporal Compositional Reasoning in Long-Form Sports Videos ARGUS: Hallucination and Omission Evaluation in Video-LLMs

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-14T19:27:29.843866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T19:27:29.843866Z digest=sha256:aaabd00cbfc99dd9fd90b241f3547634dd638d53c1046ad0be449ecefe309569

Observation 3cd54224-1dff-4d00-bfe9-a76e6a256085 · inbound

VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning cites this paper.

VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning ARGUS: Hallucination and Omission Evaluation in Video-LLMs

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-06-29T13:23:28.469585Z

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.

source=pdf_text observed=2026-06-29T13:13:57.599970Z digest=sha256:17c291890d104a49a3306b531f3b44612fba72cd888171c1899d2c10fc22e642