MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents | Paper Citation Record

Observation 0d9377ec-aca2-4c4c-9df6-124e074d8486 · outbound

This paper cites Adversarial patch.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Adversarial patch

Reference 1

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Observation f347fe36-dec9-4725-abe3-c07dc54c3653 · outbound

This paper cites Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.434454Z

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Observation 90f37915-c44a-4850-a22b-07dd97cc1639 · outbound

This paper cites SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.439929Z

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Observation 7a5fd30d-472c-4796-904a-c5f20d6a260a · outbound

This paper cites Robust feature-level adversaries are inter- pretability tools.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Robust feature-level adversaries are inter- pretability tools

Reference 4

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Observation 1bbdb3b5-33f2-40cd-b7b3-04e8ca5abcc0 · outbound

This paper cites End-to-end autonomous driving: Challenges and frontiers.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents End-to-end autonomous driving: Challenges and frontiers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.450975Z

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Observation d94ad4e1-7d3a-43a9-ba60-b0b51a758fb0 · outbound

This paper cites Shapeshifter: Robust physical adversarial attack on faster r-cnn object detector.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Shapeshifter: Robust physical adversarial attack on faster r-cnn object detector

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.455529Z

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Observation f9a1f1e4-dadf-4097-9115-828961324adb · outbound

This paper cites Physical attack on monocular depth estimation with optimal adversarial patches.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Physical attack on monocular depth estimation with optimal adversarial patches

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.460569Z

Source-reported events for the cited work

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Observation b53d4a46-af29-4443-96e6-65594143dd34 · outbound

This paper cites Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.466815Z

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Observation c19ff410-3d8e-4fef-88e0-ffeacc5fd648 · outbound

This paper cites Talk2car: Taking control of your self-driving car.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Talk2car: Taking control of your self-driving car

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.471549Z

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Observation b6733a86-ce90-44ac-b834-9906282d45a6 · outbound

This paper cites Towards universal physical attacks on single object tracking.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Towards universal physical attacks on single object tracking

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.476465Z

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Observation a389c685-1282-4206-b718-627a42a70c36 · outbound

This paper cites Tnt attacks! universal naturalis- tic adversarial patches against deep neural network systems.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Tnt attacks! universal naturalis- tic adversarial patches against deep neural network systems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.481001Z

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Observation d652d33b-6828-4212-b74c-b2d99b0b296e · outbound

This paper cites Physical adversarial attacks on an aerial imagery object detector.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Physical adversarial attacks on an aerial imagery object detector

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.484861Z

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Observation df6e8a00-e286-466b-9e10-819b0b2c9c26 · outbound

This paper cites Tenen- baum, and Igor Mordatch.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Tenen- baum, and Igor Mordatch

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.488974Z

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Observation ea53670f-2aec-4c68-b3a4-12885532a34c · outbound

This paper cites Robust physical-world attacks on deep learning visual classification.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Robust physical-world attacks on deep learning visual classification

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.492705Z

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Observation 38b6d68e-1ad5-40a6-90af-1b40d46813ff · outbound

This paper cites Robust physical-world attacks on deep learning visual classification.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Robust physical-world attacks on deep learning visual classification

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.496741Z

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Observation 68fb3c19-d3a1-4c8b-aac3-e282f9f343ce · outbound

This paper cites Robust physical-world attacks on deep learning visual classification.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Robust physical-world attacks on deep learning visual classification

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.505915Z

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Observation 58ae7a93-5d93-4ac4-b59b-5adfa9154b24 · outbound

This paper cites Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.510262Z

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Observation 372766fd-7225-41f3-82ff-0c4daa529ec4 · outbound

This paper cites BLINK: Multimodal Large Language Models Can See but Not Perceive.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents BLINK: Multimodal Large Language Models Can See but Not Perceive

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.515784Z

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Observation af0a796d-54b2-49c0-8338-88aefb5207c5 · outbound

This paper cites Tsang, and Qing Guo.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Tsang, and Qing Guo

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.520746Z

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Observation a60c80cb-4c51-4f88-b449-d80d7a3c21a2 · outbound

This paper cites Contributions of shape, texture, and color in visual recog- nition.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Contributions of shape, texture, and color in visual recog- nition

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.524737Z

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Observation 2efab9b0-52f0-4769-90bf-1cf8e4a89add · outbound

This paper cites Goodfellow, Jonathon Shlens, and Christian Szegedy.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Goodfellow, Jonathon Shlens, and Christian Szegedy

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.528138Z

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Observation dce1cf9c-5e8b-48f7-bb94-2f3393610721 · outbound

This paper cites The human visual cortex.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents The human visual cortex

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.532202Z

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Observation 04184664-b312-455a-9033-dff54ed79bf4 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.537136Z

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Observation ef9ce08c-fc3d-4585-8df1-b9d234d01299 · outbound

This paper cites Spark: Spatial- aware online incremental attack against visual tracking.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Spark: Spatial- aware online incremental attack against visual tracking

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.541906Z

Source-reported events for the cited work

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Observation be80a300-6bff-45b4-a406-b5f6d3cad9ba · outbound

This paper cites Natural adversarial examples.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Natural adversarial examples

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.547289Z

Source-reported events for the cited work

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Observation a6d43206-0453-4cc6-a79d-3678db1f6b6a · outbound

This paper cites Naturalistic physical adversarial patch for object detectors.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Naturalistic physical adversarial patch for object detectors

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.551770Z

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Observation 9e46c0fd-70fd-42a5-9347-7a8665cdabdc · outbound

This paper cites Audiogpt: Understanding and generating speech, music, sound, and talking head.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Audiogpt: Understanding and generating speech, music, sound, and talking head

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.200672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b8f3d04b-fc47-4985-b5a2-1938f6c9ab4e · outbound

This paper cites Inner monologue: Embodied reasoning through planning with language models.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Inner monologue: Embodied reasoning through planning with language models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.186389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6afe9d55-5769-41ef-8d6a-45ab1c365de9 · outbound

This paper cites ALA: Naturalness-aware Adversarial Lightness Attack.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents ALA: Naturalness-aware Adversarial Lightness Attack

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-11T18:24:50.068739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dbfbfe01-6ce5-4604-b5ea-12c5d1cfb370 · outbound

This paper cites Joshi, Kyle Jeffrey, Rosario Jauregui Ruano, Jasmine Hsu, Keerthana Gopalakr- ishnan, Byron David, Andy Zeng, and Chu yuan Kelly Fu.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Joshi, Kyle Jeffrey, Rosario Jauregui Ruano, Jasmine Hsu, Keerthana Gopalakr- ishnan, Byron David, Andy Zeng, and Chu yuan Kelly Fu

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.174211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation af9acb75-0899-4dc6-b483-1cc3dae7ac9b · outbound

This paper cites Adversarial examples are not bugs, they are features.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Adversarial examples are not bugs, they are features

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.162268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b4a48b4d-ddc1-46fa-9b88-6d7b94d2a9f5 · outbound

This paper cites Adversarial examples are not bugs, they are features.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Adversarial examples are not bugs, they are features

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.149800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7f070d55-1185-4f22-9398-19881cdec8f9 · outbound

This paper cites Adversarial examples are not bugs, they are features.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Adversarial examples are not bugs, they are features

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.136293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 81ea22cb-5254-4b89-bb48-63d4678f0491 · outbound

This paper cites Fast and accurate object detector for autonomous driving based on improved yolov5.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Fast and accurate object detector for autonomous driving based on improved yolov5

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.124157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bbd11029-f07f-4ce5-be71-19d601e14d96 · outbound

This paper cites Ultralytics yolov5, 2020.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Ultralytics yolov5, 2020

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.109987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0e1ab1b3-9856-4523-a861-21474e1c3a50 · outbound

This paper cites Physgan: Generating physical-world-resilient adversarial examples for autonomous driving.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Physgan: Generating physical-world-resilient adversarial examples for autonomous driving

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.095061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5410724c-e93b-4505-8563-5ef295742cff · outbound

This paper cites VILA: on pre-training for visual language models.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents VILA: on pre-training for visual language models

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.081961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b39fcb17-4477-42a0-920a-ee673cb7e863 · outbound

This paper cites Perceptual-sensitive gan for generating adversarial patches.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Perceptual-sensitive gan for generating adversarial patches

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.068865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 98964ff1-9268-424d-b316-9afd0e9a8b9d · outbound

This paper cites Bias-based universal ad- versarial patch attack for automatic check-out.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Bias-based universal ad- versarial patch attack for automatic check-out

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.053455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 02141796-9900-457b-9f62-c3570f990066 · outbound

This paper cites Detrs beat yolos on real-time object detection, 2023.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Detrs beat yolos on real-time object detection, 2023

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.031105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 536884dc-868e-44c7-ae84-6c993fee8100 · outbound

This paper cites GPT-Driver: Learning to Drive with GPT.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents GPT-Driver: Learning to Drive with GPT

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.624608Z

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Unavailable: canonical work link unavailable.

Observation 3da61ca0-55cb-4b35-adee-4c97299e3f65 · outbound

This paper cites 3d object detection for autonomous driving: A comprehensive survey.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents 3d object detection for autonomous driving: A comprehensive survey

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:51.014538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 705bfaf9-88fb-4946-b885-1aa02c309eb8 · outbound

This paper cites Adversarial Attacks on Traffic Sign Recognition: A Survey.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Adversarial Attacks on Traffic Sign Recognition: A Survey

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-11T18:24:50.032943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 59398818-91f6-457d-a825-b4e71d28b829 · outbound

This paper cites MP5: A multi-modal open-ended embodied system in minecraft via active perception.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents MP5: A multi-modal open-ended embodied system in minecraft via active perception

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.998257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 32e7ac9c-ad41-4134-b36a-245723b2e55a · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents High-resolution image synthesis with latent diffusion models

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.986120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 23a2543e-ced3-460d-aadc-c9523bc770b5 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents High-resolution image synthesis with latent diffusion models

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.968975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ea09b233-6803-428e-9d6b-687d26e4fa1e · outbound

This paper cites Intriguing properties of diffusion models: An empirical study of the natural attack capability in text- to-image generative models.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Intriguing properties of diffusion models: An empirical study of the natural attack capability in text- to-image generative models

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.951135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5447bc38-ff80-4361-831f-d66f6267219e · outbound

This paper cites Role play with large language models.Nature, 623(7987):493–498,.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Role play with large language models.Nature, 623(7987):493–498,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.934974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2036c38f-3570-4927-8086-95bc08660f72 · outbound

This paper cites SoK: On the Semantic AI Security in Autonomous Driving.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents SoK: On the Semantic AI Security in Autonomous Driving

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.660401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7058c2e5-16e0-4e5e-9754-3ff36655a0dd · outbound

This paper cites LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.666316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0204cb69-f9ef-498e-bc02-4545e3ce9833 · outbound

This paper cites Dta: Phys- ical camouflage attacks using differentiable transformation network.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Dta: Phys- ical camouflage attacks using differentiable transformation network

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.921395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8b3a47d7-f2f6-4353-a317-ef20fe77d685 · outbound

This paper cites Legiti- mate adversarial patches: Evading human eyes and detection models in the physical world.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Legiti- mate adversarial patches: Evading human eyes and detection models in the physical world

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.906804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 159d4c04-f482-41b2-864f-a6c1a450801c · outbound

This paper cites Fooling automated surveillance cameras: adversarial patches to attack person detection.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Fooling automated surveillance cameras: adversarial patches to attack person detection

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.890528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f2868885-ae53-4bd9-a91a-20a4c2ee479c · outbound

This paper cites YOLOv10: Real-Time End-to-End Object Detection.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents YOLOv10: Real-Time End-to-End Object Detection

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.682689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bd1a973-8aea-461d-8771-65d7e4a1f67c · outbound

This paper cites V oyager: An open-ended embodied agent with large language models.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents V oyager: An open-ended embodied agent with large language models

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.864372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 92ecd530-3a30-4aeb-a636-87cf0c92015b · outbound

This paper cites Uni- versal adversarial patch attack for automatic checkout using perceptual and attentional bias.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Uni- versal adversarial patch attack for automatic checkout using perceptual and attentional bias

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.844665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ab6534a5-3316-4daa-811b-2d98e1be6f1b · outbound

This paper cites Dual attention suppression attack: Generate adversarial camouflage in physical world.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Dual attention suppression attack: Generate adversarial camouflage in physical world

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.827200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c75355f8-1ecd-4f9e-8eae-6a090973ec95 · outbound

This paper cites Does physical adversarial example really matter to autonomous driving? towards system-level effect of adversarial object evasion attack.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Does physical adversarial example really matter to autonomous driving? towards system-level effect of adversarial object evasion attack

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.804930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a12470a9-64d1-44ea-8e45-cb60e7d3a8d6 · outbound

This paper cites SegLLM: Multi-round Reasoning Segmentation.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents SegLLM: Multi-round Reasoning Segmentation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-11T18:24:49.703699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 683ed998-c3fc-4fbb-9a37-84701fbfbc52 · outbound

This paper cites Physical adversarial attack meets computer vision: A decade survey.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Physical adversarial attack meets computer vision: A decade survey

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.790716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 07cf86a5-9100-423b-9cc1-be6b943fa8bb · outbound

This paper cites Chi, Quoc V.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Chi, Quoc V

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.773114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 36ea4c62-b066-47a5-8b6f-4039e08fed44 · outbound

This paper cites Simultane- ously optimizing perturbations and positions for black-box adversarial patch attacks.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Simultane- ously optimizing perturbations and positions for black-box adversarial patch attacks

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.759003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a26c1ff9-e5b3-4ef2-ad30-1b5ebb20cebd · outbound

This paper cites Unified adversarial patch for visible-infrared cross-modal attacks in the physical world.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unified adversarial patch for visible-infrared cross-modal attacks in the physical world

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.745236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6782bb04-2d81-45e0-9b18-e0607d353d47 · outbound

This paper cites Tsang, and Lei Ma.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Tsang, and Lei Ma

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.732752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 09078830-88a7-4b12-9fea-99bca26322f9 · outbound

This paper cites Adversarial t-shirt! evading person detectors in a physical world.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Adversarial t-shirt! evading person detectors in a physical world

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.719153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e01e9a1c-b057-49ec-b291-7746196e3a9a · outbound

This paper cites Diffusion-based adversarial sample generation for improved stealthiness and controllability.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Diffusion-based adversarial sample generation for improved stealthiness and controllability

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.706777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f291d3a4-5321-414a-84e6-d8061fb320cb · outbound

This paper cites invisible cloak.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents invisible cloak

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.694655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f32d35cd-4631-48a9-b835-9ba27566d8d7 · outbound

This paper cites Set-of-mark prompting unleashes ex- traordinary visual grounding in gpt-4v, 2023.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Set-of-mark prompting unleashes ex- traordinary visual grounding in gpt-4v, 2023

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.681313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1716feda-6801-4a01-8a4b-69690e931933 · outbound

This paper cites Mastering text-to-image diffusion: Re- captioning, planning, and generating with multimodal llms.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Mastering text-to-image diffusion: Re- captioning, planning, and generating with multimodal llms

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.667888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6456b0ea-1feb-4e1e-b3a0-0ed8ab945fa8 · outbound

This paper cites Llava-grounding: Grounded visual chat with large multimodal models.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Llava-grounding: Grounded visual chat with large multimodal models

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.654241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 75d2f3ea-a0f9-4ed3-bdd7-d2e6b00206d0 · outbound

This paper cites {CAPatch}: Physical adversarial patch against image captioning systems.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents {CAPatch}: Physical adversarial patch against image captioning systems

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.636730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 85c0739e-e661-40e6-ae7c-ce4282e7cff3 · outbound

This paper cites CAMOU: learning physical vehicle camouflages to adver- sarially attack detectors in the wild.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents CAMOU: learning physical vehicle camouflages to adver- sarially attack detectors in the wild

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.623814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d2c84f51-f4c4-43f9-afb5-fc48822ccdd0 · outbound

This paper cites You only look at screens: Multimodal chain-of-action agents.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents You only look at screens: Multimodal chain-of-action agents

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.611442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ac11c456-3b4d-4ab3-91c3-b633730994ee · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.597708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2b2fb785-cf6c-4f99-9e51-0f4dd007cd5a · outbound

This paper cites Shadows can be dangerous: Stealthy and effec- tive physical-world adversarial attack by natural phenomenon.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Shadows can be dangerous: Stealthy and effec- tive physical-world adversarial attack by natural phenomenon

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.586183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3e356da5-a466-4390-9a35-459e79e4c0ce · outbound

This paper cites All the experiments are conducted via a server with AMD EPYC 9554 64-core Processor and an NVIDIA L40 GPU, running Ubuntu 22.04.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents All the experiments are conducted via a server with AMD EPYC 9554 64-core Processor and an NVIDIA L40 GPU, running Ubuntu 22.04

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.573284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d73ba7da-b198-45ad-86aa-ccc7dc864f83 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.558712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 89404827-7ddf-44e9-ade3-fe96e60bae01 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.544523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c46fe268-3cbd-4462-9f83-84b271fb934b · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 80

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.532270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b833c839-7f1e-4070-96a9-49d1a098e55f · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 81

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.520321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d0aa284d-dfd6-4e44-b29a-527447cd40e3 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 82

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.507924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a856324a-dd7a-4ec0-8c2d-0122c1ac6b34 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 83

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.494412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ac4385f2-36c3-411f-8c75-4567e17ca071 · outbound

This paper cites first list all the regions, poles and beams in the given environment image that can be utilized to either paint or hang the visual patch b.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents first list all the regions, poles and beams in the given environment image that can be utilized to either paint or hang the visual patch b

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.478467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0f1ed653-cd96-4ca8-92b1-950cae4488a2 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 85

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.463002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2fa3e47e-e5d7-4392-b010-b3b44e320c3f · outbound

This paper cites • CONF_THRESHOLD: 0.80.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents • CONF_THRESHOLD: 0.80

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.450695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 268890df-e499-4108-a419-0d5c311ed570 · outbound

This paper cites Statistical Results of Naturalness In section Sec.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Statistical Results of Naturalness In section Sec

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.435058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9818956c-d71d-474b-b4c6-5496457264c2 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.420224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 34ba1166-d60f-45c9-b113-3f22b4a91cdc · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.404645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 72530ec9-752f-46f4-85c4-cab6cc68e690 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 90

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.382357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6c7d6ff5-e527-458b-b73f-61290aa8f13a · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 91

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.369454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c4e92039-2ef6-464a-832c-e93f3366ec3b · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 92

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.356322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 82b3e5dc-b647-4c41-b4d3-1b575ac6a25b · outbound

This paper cites Take the robust features of a stop sign as example, they contains:.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Take the robust features of a stop sign as example, they contains:

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.341503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7b398d31-5d91-480a-9d76-a5fcd96ae8a4 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 94

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.326335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4e604bcc-85d3-4feb-aea5-22d44aefb9d3 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.310628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6a820ecf-1e56-47cf-a06c-d655fe2f99ba · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 96

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.294795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 74afa452-df18-4c0e-897b-236e66a27c00 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 97

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.280059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5f97d424-7e46-4deb-b2dd-9dde8d825118 · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 98

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.258055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 13426652-c115-4f0d-826b-6068441d2c2c · outbound

This paper cites A stop sign.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents A stop sign

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.243069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a35c0da0-951f-415f-81fd-123c4b3be350 · outbound

This paper cites robustified.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents robustified

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:24:50.228335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a89214ee-ea28-406d-b638-0d6bddfcb6de · outbound

This paper cites an unresolved cited work.

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents Unresolved cited work

Reference 101

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:24:50.204531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers