Paper Citation Record · LEDGER

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models

As of 9 August 2026, this Paper Citation Record lists 100 of 116 outbound references and 7 inbound Pith citation observations for arXiv:2502.07601.

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

pith.paper-citation-record.v1
2502.07601 v2

Coverage vector

measured 100 of 116 reference resolution

Typed states for the displayed outbound observations.

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measured 107 of 107 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 2026-08-06T18:34:48.043962Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:56:59.022805Z

Reference resolution

100 of 116 outbound references displayed

verified exact2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5251cacb-ee9a-4756-853d-c82bf6765c83 · outbound

This paper cites Bmad: Benchmarks for medical anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Bmad: Benchmarks for medical anomaly detection

Reference 1

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Observation 16beb027-d33d-4682-951f-59092485be62 · outbound

This paper cites Mvtec ad–a comprehensive real-world dataset for unsupervised anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Mvtec ad–a comprehensive real-world dataset for unsupervised anomaly detection

Reference 2

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Observation c1a49393-7017-4dc0-963c-6b9494fe3363 · outbound

This paper cites Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings

Reference 3

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Observation 7f7a930a-6146-42b6-a6ca-ddca2a95386b · outbound

This paper cites The mvtec 3d-ad dataset for unsupervised 3d anomaly detection and localization.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models The mvtec 3d-ad dataset for unsupervised 3d anomaly detection and localization

Reference 4

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Observation 91020dee-bd40-412d-af52-30c0eebcda37 · outbound

This paper cites Anomaly de- tection under distribution shift.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Anomaly de- tection under distribution shift

Reference 5

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Observation 1576dde6-3e62-4de8-ae51-823a3c7c714a · outbound

This paper cites Adaclip: Adapting clip with hybrid learnable prompts for zero-shot anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Adaclip: Adapting clip with hybrid learnable prompts for zero-shot anomaly detection

Reference 6

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Source-reported events for the cited work

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Observation 6659cced-29fc-4962-b4f2-5f4288776798 · outbound

This paper cites Spatialvlm: Endow- ing vision-language models with spatial reasoning capabili- ties.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Spatialvlm: Endow- ing vision-language models with spatial reasoning capabili- ties

Reference 7

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Observation 5ee7da13-bf68-4278-ade0-20ba06ddddde · outbound

This paper cites Sharegpt4v: Improving large multi-modal models with better captions,.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Sharegpt4v: Improving large multi-modal models with better captions,

Reference 8

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Observation 774a8392-0f72-4a1b-b4ee-fe28d193c77e · outbound

This paper cites A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization

Reference 9

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Observation 82f71480-ee12-48f3-9288-a12c1525d2e1 · outbound

This paper cites Clip2scene: Towards label-efficient 3d scene understanding by clip.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Clip2scene: Towards label-efficient 3d scene understanding by clip

Reference 10

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Observation 3f2e2f85-d716-4f48-b534-c87687e2aed7 · outbound

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Unresolved cited work

Reference 11

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Observation 809943ab-af17-41a4-9551-032d96cdee07 · outbound

This paper cites Deep one-class classification via interpolated gaussian descriptor.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Deep one-class classification via interpolated gaussian descriptor

Reference 12

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Observation f3bfa126-e4a9-4c60-9e3e-917abc90eea8 · outbound

This paper cites How far are we to gpt-4v? closing the gap to commercial multimodal models with open- source suites, 2024.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models How far are we to gpt-4v? closing the gap to commercial multimodal models with open- source suites, 2024

Reference 13

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Observation 9dcd80d6-142a-4ab8-871a-cd33b2af471e · outbound

This paper cites Emotion-llama: Multimodal emotion recognition and reasoning with instruction tuning.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Emotion-llama: Multimodal emotion recognition and reasoning with instruction tuning

Reference 14

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Observation ded92600-a5be-465f-be47-772e41d8a0a9 · outbound

This paper cites InstructBLIP: Towards general-purpose vision-language models with instruction tuning.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models InstructBLIP: Towards general-purpose vision-language models with instruction tuning

Reference 15

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Observation 8d42ff7c-43f2-4eda-85a9-1b5b89ed2f6c · outbound

This paper cites Automatic classification of defective photovoltaic module cells in electroluminescence images.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Automatic classification of defective photovoltaic module cells in electroluminescence images

Reference 16

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Observation 242de92f-4dbc-4158-af72-40db640d3c2c · outbound

This paper cites Simclip: Refining image-text alignment with simple prompts for zero-/few- shot anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Simclip: Refining image-text alignment with simple prompts for zero-/few- shot anomaly detection

Reference 17

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Source-reported events for the cited work

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Observation 983219c8-4ab3-4466-98b3-1814c5c840d3 · outbound

This paper cites Anomaly detection via reverse distillation from one-class embedding.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Anomaly detection via reverse distillation from one-class embedding

Reference 18

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Observation b6dbf93b-5b9a-4dd4-ba18-1f95b58c4c1f · outbound

This paper cites Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly Localization.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly Localization

Reference 19

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Observation 7cf54599-4abc-407b-aeff-31378cdbfde3 · outbound

This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding, 2019.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Bert: Pre-training of deep bidirectional trans- formers for language understanding, 2019

Reference 20

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Observation 57b8a415-cba6-4fc6-80de-809e5e27625a · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models An image is worth 16x16 words: Transformers for image recognition at scale

Reference 21

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Observation e582fd4b-8bcd-4ead-ae38-a4a915437ff6 · outbound

This paper cites Fastrecon: Few-shot industrial 9 anomaly detection via fast feature reconstruction.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Fastrecon: Few-shot industrial 9 anomaly detection via fast feature reconstruction

Reference 22

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Observation a20ce60e-5ee8-4528-ae21-edec39e84f62 · outbound

This paper cites Chatpose: Chatting about 3d human pose.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Chatpose: Chatting about 3d human pose

Reference 23

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Observation a2f3597d-c1ad-4444-945e-0637ae75d3c8 · outbound

This paper cites Deep learning for medical anomaly detection–a survey.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Deep learning for medical anomaly detection–a survey

Reference 24

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Observation 2b277262-4c36-4f5f-ae5d-d6301a0c1737 · outbound

This paper cites Transfusion–a transparency-based diffusion model for anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Transfusion–a transparency-based diffusion model for anomaly detection

Reference 25

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Google-images-search 1.4.7, 2024

Reference 26

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Observation 82b99abe-e8e6-49cc-9530-e040ff4cd20e · outbound

This paper cites Filo: Zero-shot anomaly detection by fine-grained description and high-quality lo- calization.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Filo: Zero-shot anomaly detection by fine-grained description and high-quality lo- calization

Reference 27

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This paper cites Anomalygpt: Detecting in- dustrial anomalies using large vision-language models.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Anomalygpt: Detecting in- dustrial anomalies using large vision-language models

Reference 28

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Observation 4670a506-937d-4d22-8edc-5245d6d52162 · outbound

This paper cites StimuVAR: Spatiotemporal Stimuli-aware Video Affective Reasoning with Multimodal Large Language Models.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models StimuVAR: Spatiotemporal Stimuli-aware Video Affective Reasoning with Multimodal Large Language Models

Reference 29

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Observation 10c03b7b-996a-49ab-95a0-14a2957ac48e · outbound

This paper cites Br35h: Brain tumor detection 2020, 2020.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Br35h: Brain tumor detection 2020, 2020

Reference 30

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Observation c0e4925d-f603-462f-9954-d69ba4337208 · outbound

This paper cites Madgan: Unsupervised medical anomaly detection gan us- ing multiple adjacent brain mri slice reconstruction.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Madgan: Unsupervised medical anomaly detection gan us- ing multiple adjacent brain mri slice reconstruction

Reference 31

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Observation 58ee2b46-a8e1-486a-aa04-e804e28352cc · outbound

This paper cites Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection

Reference 32

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Long-tailed anomaly detection with learnable class names

Reference 33

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Divide-and-assemble: Learning block-wise memory for unsupervised anomaly detection

Reference 34

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Registration based few-shot anomaly detection

Reference 35

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This paper cites Adapting visual-language models for generalizable anomaly detection in medical im- ages.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Adapting visual-language models for generalizable anomaly detection in medical im- ages

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This paper cites Towards open-world object- based anomaly detection via self-supervised outlier synthe- sis.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Towards open-world object- based anomaly detection via self-supervised outlier synthe- sis

Reference 37

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Winclip: Zero- /few-shot anomaly classification and segmentation

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Deep learning-based defect detection of metal parts: evaluating current methods in complex condi- tions

Reference 39

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Brain tumor detec- tion using mri images

Reference 40

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Head ct - hemorrhage, 2018

Reference 41

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Text-guided variational image generation for industrial anomaly detection and seg- mentation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:55.046697Z

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Zero-shot anomaly detection via batch normalization

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:55.030782Z

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Observation 596f0d4c-f678-4541-8948-9e8604fce402 · outbound

This paper cites Llava-onevision: Easy visual task transfer, 2024.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Llava-onevision: Easy visual task transfer, 2024

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:55.016171Z

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Observation 7536d9d0-65a4-4ee2-b11c-2ba50b349078 · outbound

This paper cites LLaV A-med: Training a large language- and-vision assistant for biomedicine in one day.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models LLaV A-med: Training a large language- and-vision assistant for biomedicine in one day

Reference 45

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Observation 2ed6b532-bbac-4f91-b030-31f8590a2d1e · outbound

This paper cites Cutpaste: Self-supervised learning for anomaly detection and localization.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Cutpaste: Self-supervised learning for anomaly detection and localization

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.985949Z

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Observation 4d4bd1b1-48f3-42f9-a787-d0fba4c35e45 · outbound

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models

Reference 47

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Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.970320Z

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Observation 68d9a879-ce00-4a8e-8f1f-79233de8aa34 · outbound

This paper cites Blip- 2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Blip- 2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.954048Z

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Observation 15ce009d-b8c1-4e2d-893b-21054169db4e · outbound

This paper cites Towards scalable 3d anomaly detection and localization: A benchmark via 3d anomaly synthesis and a self-supervised learning network.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Towards scalable 3d anomaly detection and localization: A benchmark via 3d anomaly synthesis and a self-supervised learning network

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.939374Z

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Observation 6804423d-60b8-4702-b29e-0751a465da41 · outbound

This paper cites Promptad: Learn- ing prompts with only normal samples for few-shot anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Promptad: Learn- ing prompts with only normal samples for few-shot anomaly detection

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.925805Z

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Observation 1b81c0c3-9df4-4ec6-b3a3-4254a154f780 · outbound

This paper cites Promptad: Zero-shot anomaly detection using text prompts.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Promptad: Zero-shot anomaly detection using text prompts

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.911041Z

Source-reported events for the cited work

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Observation a25c4e51-315b-48fe-881b-f330a5a620c7 · outbound

This paper cites Open-vocabulary semantic segmentation with mask-adapted clip.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Open-vocabulary semantic segmentation with mask-adapted clip

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.501819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33ceb8d1-8d6d-4145-8f1e-514f328a44fe · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Rouge: A package for automatic evaluation of summaries

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.884619Z

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.

Observation 3205bdc8-7ad3-4727-9807-a0b0bda6eb1e · outbound

This paper cites Microsoft coco: Common objects in context.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Microsoft coco: Common objects in context

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.509372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5730d8d2-2075-415e-80be-3b5b30078270 · outbound

This paper cites Clip is also an efficient segmenter: A text-driven approach for weakly supervised semantic segmentation.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Clip is also an efficient segmenter: A text-driven approach for weakly supervised semantic segmentation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.858892Z

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.

Observation 3ac0a8b6-7581-4471-884c-2e17d20d7a3f · outbound

This paper cites Visual instruction tuning.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Visual instruction tuning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.842820Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 254e98cf-f3a9-4e66-b194-9256c1d26756 · outbound

This paper cites Improved baselines with visual instruction tuning.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Improved baselines with visual instruction tuning

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.522667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4b3793c-1954-4fcb-8e85-3a9f30896c12 · outbound

This paper cites Llava-next: Im- proved reasoning, ocr, and world knowledge, 2024.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Llava-next: Im- proved reasoning, ocr, and world knowledge, 2024

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.527419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c08a054d-8521-4520-b5d9-894562724bdd · outbound

This paper cites Real3d- AD: A dataset of point cloud anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Real3d- AD: A dataset of point cloud anomaly detection

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.807824Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ddc1331c-7822-48b2-9daf-e29f5cd67349 · outbound

This paper cites Clip-driven universal model for organ segmentation and tumor detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Clip-driven universal model for organ segmentation and tumor detection

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.794048Z

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Observation 137878c9-ce2e-48e5-ad20-117311f14c5f · outbound

This paper cites Roberta: A robustly optimized bert pretraining approach, 2019.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Roberta: A robustly optimized bert pretraining approach, 2019

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.540697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c7ada39-edfc-428c-ad97-e74e36cbb410 · outbound

This paper cites Adversar- ially robust one-class novelty detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Adversar- ially robust one-class novelty detection

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.769489Z

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Observation d29669ab-e0bc-4217-af8a-99fe45c80531 · outbound

This paper cites SGDR: Stochastic gradi- ent descent with warm restarts.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models SGDR: Stochastic gradi- ent descent with warm restarts

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.754016Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dbf8f5b0-4363-458d-9c7e-de7c64ed50f6 · outbound

This paper cites Decoupled weight decay regularization.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Decoupled weight decay regularization

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.738401Z

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.

Observation 2b3b22e5-9e5b-4d15-92e1-c5a0ae1c2295 · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.723784Z

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Observation aa3a4a84-13f6-452c-a0d8-2ecb525039ce · outbound

This paper cites Video Anomaly Detection and Explanation via Large Language Models.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Video Anomaly Detection and Explanation via Large Language Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.563367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d9fed68-e7ef-4f5a-88d8-6a738a7911dd · outbound

This paper cites Vt-adl: A vision trans- former network for image anomaly detection and localiza- tion.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Vt-adl: A vision trans- former network for image anomaly detection and localiza- tion

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.709007Z

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.

Observation ccb3bf7d-bd10-4a5c-9274-b0de42d79aa7 · outbound

This paper cites RGI: robust GAN- inversion for mask-free image inpainting and unsupervised pixel-wise anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models RGI: robust GAN- inversion for mask-free image inpainting and unsupervised pixel-wise anomaly detection

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.693739Z

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.

Observation 956e313d-f563-49a5-b6e5-b4b1219f3d4e · outbound

This paper cites Reason2drive: Towards interpretable and chain-based reasoning for autonomous driving.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Reason2drive: Towards interpretable and chain-based reasoning for autonomous driving

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.680087Z

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.

Observation 938b045e-6084-415b-a8c0-d12b2133d011 · outbound

This paper cites Gpt-4v(ision) system card, 2023.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Gpt-4v(ision) system card, 2023

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.667030Z

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.

Observation 4801efe5-ffde-4f87-9fe4-de0b41e1d8a9 · outbound

This paper cites Gpt-4o system card, 2024.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Gpt-4o system card, 2024

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.653781Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 50d40237-7878-4827-b995-0a3c44209d35 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Learn- ing transferable visual models from natural language super- vision

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.639592Z

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.

Observation c40b9611-e583-45c3-baa4-3cc2221055a5 · outbound

This paper cites an unresolved cited work.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-08T12:15:54.625410Z

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.

Observation b09b3d67-fb72-4205-b1b9-7bc902f5e0a5 · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks, 2019.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Sentence-bert: Sentence embeddings using siamese bert-networks, 2019

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.610652Z

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.

Observation 1aeaa6d6-dc9f-4a24-bda3-75ccbde72296 · outbound

This paper cites Mean-shifted contrastive loss for anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Mean-shifted contrastive loss for anomaly detection

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.596389Z

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.

Observation 74f29015-56b3-4b7e-821f-e2e7b0ec9af8 · outbound

This paper cites Towards total recall in industrial anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Towards total recall in industrial anomaly detection

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.580448Z

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.

Observation 7fe32284-5df2-4ce3-a0e7-c86e59ec6996 · outbound

This paper cites Prompt- guided zero-shot anomaly action recognition using pre- trained deep skeleton features.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Prompt- guided zero-shot anomaly action recognition using pre- trained deep skeleton features

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.565755Z

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.

Observation 01b391f1-fd84-4407-859f-037da6ac93d9 · outbound

This paper cites Mae- day: Mae for few-and zero-shot anomaly-detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Mae- day: Mae for few-and zero-shot anomaly-detection

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.550703Z

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.

Observation 9f084ef1-2fac-459e-9472-c841ff3168c5 · outbound

This paper cites Robovqa: Multimodal long-horizon reasoning for robotics.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Robovqa: Multimodal long-horizon reasoning for robotics

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.534899Z

Source-reported events for the cited work

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Observation 86f7c917-4e03-4b11-a86f-fbcaa0895909 · outbound

This paper cites A public fabric database for defect detection methods and results.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models A public fabric database for defect detection methods and results

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.521260Z

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.

Observation 9794d84a-1b2b-4f5c-b8d9-43c04435bc33 · outbound

This paper cites GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features

Reference 82

Resolution: verified exact; local_arxiv, observed 2026-08-08T12:15:53.875324Z

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.

Observation fa01b72f-e64f-444c-a631-84e50525e4bb · outbound

This paper cites Face-mllm: A large face perception model,.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Face-mllm: A large face perception model,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.507618Z

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.

Observation 3d8076a1-cac8-4460-8c67-c07881fe4a36 · outbound

This paper cites An incremental unified framework for small defect inspection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models An incremental unified framework for small defect inspection

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.492515Z

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.

Observation 35743585-c2be-4c16-ba27-f08648224357 · outbound

This paper cites Revisiting reverse distillation for anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Revisiting reverse distillation for anomaly detection

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.477938Z

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.

Observation bbc8b73f-d170-488c-a05a-feaf2c6acbbf · outbound

This paper cites Clipn for zero-shot ood detection: Teaching clip to say no.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Clipn for zero-shot ood detection: Teaching clip to say no

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.642115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 203ab711-cbab-4986-ad1e-d911fa72137d · outbound

This paper cites Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution, 2024.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution, 2024

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.646597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4633c331-b818-487c-a731-06bf2b0c5d05 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large lan- guage models.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Chain-of-thought prompting elicits reasoning in large lan- guage models

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.442134Z

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.

Observation b4bb723b-17d8-482d-8fe9-6797034aa9a9 · outbound

This paper cites Anomaly detection for medical images based on a one-class classification.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Anomaly detection for medical images based on a one-class classification

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.426462Z

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.

Observation bbb2da57-1507-4f3b-9ef3-9c33d387ee28 · outbound

This paper cites Diffusion models for medical anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Diffusion models for medical anomaly detection

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.411277Z

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.

Observation d74f576e-4fdc-4952-83b3-d664ca3996f2 · outbound

This paper cites Funqa: Towards surprising video comprehension.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Funqa: Towards surprising video comprehension

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.394750Z

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.

Observation af221e77-25f3-4af2-a96d-e924441d1471 · outbound

This paper cites Pushing the limits of fewshot anomaly detection in industry vision: Graphcore.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Pushing the limits of fewshot anomaly detection in industry vision: Graphcore

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.378097Z

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.

Observation 8e53082f-5813-4cf1-81dd-d40c4833efba · outbound

This paper cites Emovit: Revolutionizing emotion insights with vi- sual instruction tuning.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Emovit: Revolutionizing emotion insights with vi- sual instruction tuning

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.363919Z

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.

Observation 4732ee9f-da8c-47d1-aef7-aea0f1e8ada4 · outbound

This paper cites Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.679847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17db7374-8110-459b-94bb-6272ca7da8bc · outbound

This paper cites GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection

Reference 95

Resolution: verified exact; local_arxiv, observed 2026-08-08T12:15:53.834354Z

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.

Observation dc014634-f280-4bbb-bdd1-a985697b0b90 · outbound

This paper cites Dense connector for mllms, 2024.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Dense connector for mllms, 2024

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.349535Z

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.

Observation 18049448-ec09-4522-aa53-45d3900a3d5c · outbound

This paper cites Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.694335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fe0294f-70a3-41f3-bbd9-aa6fd332b78f · outbound

This paper cites A unified model for multi-class anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models A unified model for multi-class anomaly detection

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.335814Z

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.

Observation dba8505e-b04c-447b-8f5c-5009b16993dd · outbound

This paper cites Draem- a discriminatively trained reconstruction embedding for sur- face anomaly detection.

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Draem- a discriminatively trained reconstruction embedding for sur- face anomaly detection

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:15:54.322137Z

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.

Observation 279928e5-3150-4429-9e90-b1edfde5646b · outbound

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

Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models Sigmoid loss for language image pre-training

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-08T12:15:53.706327Z

Source-reported events for the cited work

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Pith citing papers

Observation cccf2b32-a767-4ef5-8514-908e8a252a70 · inbound

SAGE: A Visual Language Model for Anomaly Detection via Fact Enhancement and Entropy-aware Alignment cites this paper.

SAGE: A Visual Language Model for Anomaly Detection via Fact Enhancement and Entropy-aware Alignment Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T18:34:48.043962Z

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Unavailable: canonical work link unavailable.

Observation 57484b60-46ea-4e24-ade4-665a9a6e1b26 · inbound

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects cites this paper.

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models

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Resolution: unresolved; no resolver link, observed 2026-08-06T17:21:55.132815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9fae0f0-539d-42d2-add4-8d2e6ea6b02a · inbound

IADGPT: Unified LVLM for Few-Shot Industrial Anomaly Detection, Localization, and Reasoning via In-Context Learning cites this paper.

IADGPT: Unified LVLM for Few-Shot Industrial Anomaly Detection, Localization, and Reasoning via In-Context Learning Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:12.587523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1859c60c-b1b4-41f4-a8a5-60221e6b99ea · inbound

MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence cites this paper.

MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-02T17:19:39.274578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8f625d4-994b-4482-9c02-b613ef14cff3 · inbound

Learning Discriminative Signed Distance Functions from Multi-scale Level-of-detail Features for 3D Anomaly Detection cites this paper.

Learning Discriminative Signed Distance Functions from Multi-scale Level-of-detail Features for 3D Anomaly Detection Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-12T11:01:30.656310Z

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.

Observation 7857fc62-e618-4346-9506-152167131094 · inbound

Learning Discriminative Signed Distance Functions from Multi-scale Level-of-detail Features for 3D Anomaly Detection cites this paper.

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-09T05:55:31.287658Z

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.

Observation c0565497-94c2-44cd-9cbe-8c702588b80b · inbound

GenAU: Language-Grounded Industrial Anomaly Understanding with Vision-Language Models cites this paper.

GenAU: Language-Grounded Industrial Anomaly Understanding with Vision-Language Models Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T13:56:59.024632Z

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.