Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T07:27:54.456241Z
Paper Citation Record · LEDGER
As of 21 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2607.05264.
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 2026-07-11T07:27:54.456241Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T21:12:58.548393Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T21:12:58.593946Z
39 of 39 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation affe6582-bed9-4e9a-96c5-8911af3c31ce · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Quo vadis, action recognition? a new model and the kinetics dataset
Reference 1
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Observation 26aa29ea-bcec-4d31-a062-a31e05773830 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments ActivityNet: A large-scale video benchmark for human activity understanding
Reference 2
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Observation e01849a8-2c79-49fb-9170-be84307f5c85 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments A V A: A video dataset of spatio-temporally localized atomic visual actions
Reference 3
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Observation 4d49fa25-0aad-4918-ac1b-49fd6eabdbee · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Ego4d: Around the world in 3,000 hours of egocentric video
Reference 4
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Observation e97b1a78-ace9-403e-93b4-a9795f7cca53 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Assembly101: A large-scale multi-view video dataset for understanding procedural activities
Reference 5
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Observation 48b6ba9c-06af-4cfe-a363-294bc5f2691d · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments IndustryEQA: Pushing the frontiers of embodied question answering in industrial scenarios
Reference 6
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Observation 51cd453b-c88f-4cd2-9752-e68a0d0b8a1e · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments SH17: A dataset for human safety and personal protective equipment detection in manufacturing industry.Journal of Safety Science and Resilience, 2024
Reference 7
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Observation d21ccefa-026a-418b-aa7f-f0f812704329 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 8
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Observation 33fc2c4e-5f6e-46ef-924e-87abd09e5777 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Vision language model for interpretable and fine-grained detection of safety compliance in diverse workplaces.Expert Systems with Applications, 265:125769, 11 2024
Reference 9
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Observation 3720651b-fcbe-49c7-a3e3-ff27d9e80403 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Human-LLM collabora- tive annotation through effective verification of LLM labels
Reference 10
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Observation aef6b8b3-248d-417f-be0e-8775c7ca6827 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments The State of Data Curation at NeurIPS: An Assessment of Dataset Development Practices in the Datasets and Benchmarks Track
Reference 11
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Observation 777f2235-0cca-4525-a1b9-1068de59d745 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments The Kinetics Human Action Video Dataset
Reference 12
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Observation c5ed64c2-a275-45ac-b810-662938f02eda · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
Reference 13
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Observation 7ab53443-34e6-46f3-a75d-8d74635e3ec7 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Preference leakage: A contamination problem in LLM-as-a-judge
Reference 14
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Observation 4e18583c-4e8e-4d18-b139-7335806bf2dc · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Just put a human in the loop? investigating LLM-assisted annotation for subjective tasks
Reference 15
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Unavailable: canonical work link unavailable.
Observation b600ac63-3076-423b-9482-55469e7771cf · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Datasheets for datasets.Communications of the ACM, 64(12): 86–92, 2021
Reference 16
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Observation 9162af95-4ca5-4a25-9dcb-31d0cafdc4fc · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments The MECCANO dataset: Understanding human-object interactions from egocentric videos in an industrial-like domain
Reference 17
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Observation 2ccc4406-9093-4930-9e0c-b33bc17eca06 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Toyota smarthome: Real-world activities of daily living
Reference 18
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Observation 45470b38-38b9-40bd-9add-a26c2b52037d · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Real-world anomaly detection in surveillance videos
Reference 19
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Observation 47b293fc-de40-41ab-bea8-8f7afbba935d · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Future frame prediction for anomaly detection — a new baseline
Reference 20
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Observation 011dddc8-c7ff-403a-a95f-b41b8d4069f7 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments iSafetyBench: A video-language benchmark for safety in industrial environments
Reference 21
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Observation 77478e94-13fe-451f-bacb-4e7fab6fb6bf · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Inspecsafe-v1: A multimodal benchmark for safety assessment in industrial inspection scenarios, 2026
Reference 22
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Observation 085bbdf1-7e8a-432d-86ba-30090f314c92 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments MMMU: A massive multi-discipline multimodal understanding and reasoning benchmark for expert AGI
Reference 23
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Observation 0e27fc0e-c29f-4400-8f91-55aec9ee79a7 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Video-MME: The first-ever comprehensive evaluation benchmark of multi-modal LLMs in video analysis
Reference 24
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Observation 5bbb2675-171c-4e31-84a7-5725b842a9b1 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments MVBench: A comprehensive multi-modal video understanding benchmark
Reference 25
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Observation 00857507-d218-4272-b2b5-e86828b87701 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Benchmarking neural network robustness to common corruptions and perturbations
Reference 26
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Observation fd84bd44-419c-451e-b426-4a3820049cd3 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments NaturalBench: Evaluating vision-language models on natural adversarial samples
Reference 27
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Observation c6a79ca0-3180-44e4-be5c-9d24d0d2039b · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Fields/clip
Reference 28
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Observation b99f544e-501b-4c11-9296-017609a54e8a · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 29
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Observation 4a809ac2-392a-4ce8-8d12-291f22ffe80a · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 30
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Observation d4e9e799-5ef2-4f86-a0be-ee021aed640a · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 31
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Observation 5b677058-eb61-47da-bd83-75cdb0e5f105 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 32
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Observation 7a51d79d-a3b3-44e3-800b-075b02ef19c3 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 33
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Observation ba2bd0e5-48ca-487a-a7ee-ad8cdaecdd87 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 34
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Observation 3aa229b9-1c65-49e3-854b-ba7a314c38dd · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 35
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Observation c1649052-d06f-42dc-95d3-4f37409459f9 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 36
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Observation 943f7433-9871-4327-9672-6a8c8407fb1e · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Unresolved cited work
Reference 37
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Observation dc568af3-21d1-4af2-b398-28216992e238 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments worn” only if clearly visible; use “cannot_determine
Reference 38
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Observation 1a50b927-af9c-46a5-8e92-187da86c75e3 · outbound
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments Experts and the Safety Officer are nominated by the plant to support the research
Reference 39
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Observation 643e46c7-13e4-4d2a-bea2-a1d0c20f02f0 · inbound
SafeSceneReason: A Multimodal Reasoning Benchmark Connecting Industrial Hazards with Accident Knowledge SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.