Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:41:39.882037Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:41:39.882037Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-14T19:27:29.843866Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-10T12:15:01.137692Z
83 of 83 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 590dd849-9fdc-4cb2-9c2a-a8d657e5fcdf · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs https://huggingface.co/ blog/smolvlm2, 2025
Reference 1
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Observation 53434356-bcfc-4a62-85aa-714e81b14705 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs GPT-4 Technical Report
Reference 2
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Observation 97e9437a-4105-4dda-b307-0f1fcec02fb2 · outbound
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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Observation 594055c8-92bc-44cd-8a98-098970bdff97 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs The snli corpus
Reference 4
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Observation 23e3db30-430d-4ab3-938e-ffee2a357ce6 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Activitynet: A large-scale video benchmark for human activity understanding
Reference 5
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs e-snli: Natural language inference with natural language explanations
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark
Reference 7
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Panda-70m: Captioning 70m videos with multiple cross-modality teachers
Reference 8
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning
Reference 9
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Observation 8f774eab-0042-4aef-909f-e623f53af606 · outbound
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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Observation daada15a-9842-4e3e-9409-13fce30079e2 · outbound
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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Observation 8ff0d009-fb19-4dac-9bd3-b6c8c90a9cfa · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs VidHal: Benchmarking Temporal Hallucinations in Vision LLMs
Reference 12
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Observation 8790372f-2667-4003-8322-fb3d0e44679f · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Transforming Question Answering Datasets Into Natural Language Inference Datasets
Reference 13
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Observation cc096888-3b71-41e3-b9eb-acd30d47cd74 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Sketch, ground, and refine: Top-down dense video caption- ing
Reference 14
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Observation 0f633d05-c3ae-4abc-99e4-cdd89b624e87 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs diffusers/shot-categorizer-v0
Reference 15
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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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Observation f9d3a925-7cf2-41e0-8c54-ce28d147afb5 · outbound
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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Observation 7f920541-4fe9-4695-b8a7-0ec9e816b893 · outbound
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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Observation 604cd840-4811-4ca3-a5b2-7c32a906c890 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models
Reference 19
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Observation 853c9b63-4469-4c28-985b-029a6dc028ad · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs The Llama 3 Herd of Models
Reference 20
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Observation e5e70f61-5368-4429-8731-bf0fa61fdcde · outbound
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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Observation 497078f1-6181-4f4c-8d86-578b877f8d17 · outbound
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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Observation 8e79c9fe-81c7-4c4b-871e-10cfeb9b434c · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 23
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Observation 78b48fdc-9398-45be-8cdf-acb5b6892294 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs CIEM: Contrastive Instruction Evaluation Method for Better Instruction Tuning
Reference 24
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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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Observation 842241d2-a3ab-4efa-8959-58b73cfcc793 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Multi-modal dense video captioning
Reference 26
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Observation c9a6224b-e33c-4b5d-8107-1ccf937b0b42 · outbound
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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Observation bb8401a1-1690-4515-8742-939acb8bcdab · outbound
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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Observation dc8eae4b-c5fa-4bfa-a9b4-4288505245ed · outbound
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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Observation 0a44e6d2-41bf-4282-94e6-6f4739e841e9 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs LLaVA-OneVision: Easy Visual Task Transfer
Reference 30
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Observation 9e51ca5a-fd6e-436d-8e09-b1acf0016e1a · outbound
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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Observation 3235d002-c515-44c3-bca8-56d0f099ac3c · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Jointly localizing and describing events for dense video captioning
Reference 32
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Evaluating Object Hallucination in Large Vision-Language Models
Reference 33
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Observation ecbdd126-2c17-4950-8c3c-f65d8f2cea17 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Revisiting the Role of Language Priors in Vision-Language Models
Reference 34
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Observation f391b0fa-d002-4c69-bccb-db675f60a44d · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs DeepSeek-V3 Technical Report
Reference 35
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Observation 64f98fc9-7c03-41f9-8be1-ef8aa579352d · outbound
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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Observation 7ccf135e-3002-481c-b3af-6b83f96d1452 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs A Survey on Hallucination in Large Vision-Language Models
Reference 37
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Logical Reasoning in Large Language Models: A Survey
Reference 38
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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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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Streamlined dense video captioning
Reference 40
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Observation 40e8b251-8ace-4e9d-ba64-119b03a54a5b · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Neptune: The Long Orbit to Benchmarking Long Video Understanding
Reference 41
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Observation d340bd51-3c6c-4172-b062-c3df7d13eb43 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs MINERVA: Evaluating Complex Video Reasoning
Reference 42
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work
Reference 43
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Per- ception test: A diagnostic benchmark for multimodal video models
Reference 44
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Dense video captioning: A survey of techniques, datasets and evalu- ation protocols
Reference 45
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Learning transferable visual models from natural language supervi- sion
Reference 46
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs SAM 2: Segment Anything in Images and Videos
Reference 47
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs CinePile: A Long Video Question Answering Dataset and Benchmark
Reference 48
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Object Hallucination in Image Captioning
Reference 49
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs FENICE: Factuality Evaluation of summarization based on Natural language Inference and Claim Extraction
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Aligning Large Multimodal Models with Factually Augmented RLHF
Reference 51
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Gemini: A Family of Highly Capable Multimodal Models
Reference 52
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Laion-aesthetics predictor v1
Reference 53
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training
Reference 54
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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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Observation 272f68dc-8c74-48c3-841d-1b0aea410c5a · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs End-to-end dense video captioning with parallel decoding
Reference 56
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs LVBench: An Extreme Long Video Understanding Benchmark
Reference 57
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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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ARGUS: Hallucination and Omission Evaluation in Video-LLMs A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Reference 59
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs ANLIzing the Adversarial Natural Language Inference Dataset
Reference 60
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Joint event detection and description in continuous video streams
Reference 61
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Qwen2.5 Technical Report
Reference 62
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs mplug- owl3: Towards long image-sequence understanding in multi- modal large language models
Reference 63
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Sigmoid loss for language image pre-training
Reference 64
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Eventhallusion: Diagnosing event hal- lucinations in video llms
Reference 65
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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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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Streaming dense video captioning
Reference 67
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Apollo: An Exploration of Video Understanding in Large Multimodal Models
Reference 68
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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
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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
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs a person is cooking,
Reference 72
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work
Reference 73
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs - **Contradiction**: Contains information that directly conflicts and is unsupported by the source_caption
Reference 74
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Reference 75
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs SUNFEAST PASTA TREAT,
Reference 76
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Observation 874c3d87-e3e1-44de-ac49-63f4c3ab4484 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work
Reference 77
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ARGUS: Hallucination and Omission Evaluation in Video-LLMs Sunfeast Pasta Treat
Reference 78
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Observation 2699120f-4ad9-4311-94d9-262fa15f5fa6 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work
Reference 79
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Observation a3a9c83b-57be-44b6-9dae-4d84078b2644 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work
Reference 80
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Observation ed7cf2fa-d875-45eb-9b67-1e041f8e2702 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work
Reference 81
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.
Observation 87586a80-fd26-450d-8225-09c6a45c0483 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Recipe Card
Reference 82
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.
Observation fb88127b-ae8a-4e03-a2b4-ac02c886da56 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Quick and Easy
Reference 83
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.
Observation 278b13a9-a20b-4cf0-8118-c70e186f7894 · outbound
ARGUS: Hallucination and Omission Evaluation in Video-LLMs Unresolved cited work
Reference 2022
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.
Observation 5b0bf116-a3cc-4bbf-a064-779e84b2e2d4 · inbound
Towards Temporal Compositional Reasoning in Long-Form Sports Videos ARGUS: Hallucination and Omission Evaluation in Video-LLMs
Reference 25
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.
Observation a51a5976-a148-47b5-b556-9b23dbc5f62a · inbound
Towards Temporal Compositional Reasoning in Long-Form Sports Videos ARGUS: Hallucination and Omission Evaluation in Video-LLMs
Reference 25
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3cd54224-1dff-4d00-bfe9-a76e6a256085 · inbound
VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning ARGUS: Hallucination and Omission Evaluation in Video-LLMs
Reference 35
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.