The 3D Mirage: Probing and Taming 3D Hallucinations | Paper Citation Record

Observation f016db4c-ba5d-4b3e-964d-5a53db5126e9 · outbound

This paper cites Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning.

The 3D Mirage: Probing and Taming 3D Hallucinations Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

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Observation 97ad751b-7cd5-4955-bd89-ada1d3bdee24 · outbound

This paper cites Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail.

The 3D Mirage: Probing and Taming 3D Hallucinations Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail

Reference 2

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Observation 52517b15-7616-4352-afd8-987d825d7df9 · outbound

This paper cites Anomaly detection in 3d point clouds using deep geometric descriptors.

The 3D Mirage: Probing and Taming 3D Hallucinations Anomaly detection in 3d point clouds using deep geometric descriptors

Reference 3

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Observation 7767a61b-bc41-452b-bd10-7798b2947d10 · outbound

This paper cites ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth.

The 3D Mirage: Probing and Taming 3D Hallucinations ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

Reference 4

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Observation 7e039b29-602e-493f-9438-58c30f354e76 · outbound

This paper cites Unsuper- vised scale-consistent depth and ego-motion learning from monocular video.

The 3D Mirage: Probing and Taming 3D Hallucinations Unsuper- vised scale-consistent depth and ego-motion learning from monocular video

Reference 5

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Observation e98900e6-ea0b-4d8a-a16e-6a37dbab7e14 · outbound

This paper cites Richter, and Vladlen Koltun.

The 3D Mirage: Probing and Taming 3D Hallucinations Richter, and Vladlen Koltun

Reference 6

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Observation 19dd119b-042b-46f3-a1d7-10501041371d · outbound

This paper cites Brostow, Jamie Shotton, Julien Fauqueur, and Roberto Cipolla.

The 3D Mirage: Probing and Taming 3D Hallucinations Brostow, Jamie Shotton, Julien Fauqueur, and Roberto Cipolla

Reference 7

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Observation 603b9f33-9018-4f35-b207-8303ac7887ca · outbound

This paper cites Comple- mentary pseudo multimodal feature for point cloud anomaly detection.Pattern Recognition, 2024.

The 3D Mirage: Probing and Taming 3D Hallucinations Comple- mentary pseudo multimodal feature for point cloud anomaly detection.Pattern Recognition, 2024

Reference 8

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Observation 457d199a-58ff-445e-8ef9-17631d322360 · outbound

This paper cites an unresolved cited work.

The 3D Mirage: Probing and Taming 3D Hallucinations Unresolved cited work

Reference 9

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Observation c034a0fb-938c-4cec-a206-a245bf6772a5 · outbound

This paper cites Fpr: False-positive rec- tification for weakly-supervised semantic segmentation.

The 3D Mirage: Probing and Taming 3D Hallucinations Fpr: False-positive rec- tification for weakly-supervised semantic segmentation

Reference 10

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Observation ed5fa22c-c091-479d-9bfe-b6b66cc9592c · outbound

This paper cites EasyNet: An Easy Network for 3D Industrial Anomaly Detection.

The 3D Mirage: Probing and Taming 3D Hallucinations EasyNet: An Easy Network for 3D Industrial Anomaly Detection

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:52.438647Z

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Observation 14363ef1-d39b-4046-bd35-727b2e771b4d · outbound

This paper cites Single- image depth perception in the wild.

The 3D Mirage: Probing and Taming 3D Hallucinations Single- image depth perception in the wild

Reference 12

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Observation 3e2ae41e-057d-47d5-8a8e-13e01b5677b3 · outbound

This paper cites Learning depth estimation for transparent and mirror surfaces.

The 3D Mirage: Probing and Taming 3D Hallucinations Learning depth estimation for transparent and mirror surfaces

Reference 13

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Observation 2e502830-8bb8-4c05-bcfb-50cf65374e0f · outbound

This paper cites Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner.

The 3D Mirage: Probing and Taming 3D Hallucinations Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner

Reference 14

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Observation b6d13911-c580-4b4c-9896-8898dbbafc24 · outbound

This paper cites Depth map prediction from a single image using a multi-scale deep net- work.

The 3D Mirage: Probing and Taming 3D Hallucinations Depth map prediction from a single image using a multi-scale deep net- work

Reference 15

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Observation d780efa3-bb20-449a-be1f-76c7a8e7d011 · outbound

This paper cites Vision meets robotics: The kitti dataset.Interna- tional Journal of Robotics Research (IJRR), 2013.

The 3D Mirage: Probing and Taming 3D Hallucinations Vision meets robotics: The kitti dataset.Interna- tional Journal of Robotics Research (IJRR), 2013

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:53.176329Z

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Observation 801fd226-4e3e-42ce-a91a-0b4c8f9ddca6 · outbound

This paper cites an unresolved cited work.

The 3D Mirage: Probing and Taming 3D Hallucinations Unresolved cited work

Reference 17

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Observation ada1ef50-205b-4005-95f5-88b7a0f0bdc1 · outbound

This paper cites an unresolved cited work.

The 3D Mirage: Probing and Taming 3D Hallucinations Unresolved cited work

Reference 18

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Observation 3ca25b19-eeb2-4566-bd6f-087623d884fe · outbound

This paper cites Rethinking reverse distillation for multi-modal anomaly detection.

The 3D Mirage: Probing and Taming 3D Hallucinations Rethinking reverse distillation for multi-modal anomaly detection

Reference 19

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Observation 2f0e9b09-b95a-4fdd-8f4c-02f8e649ee1e · outbound

This paper cites Depthfm: Fast monocular depth estimation with flow matching.

The 3D Mirage: Probing and Taming 3D Hallucinations Depthfm: Fast monocular depth estimation with flow matching

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:53.697113Z

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Observation 2d00122e-3958-4a6b-80b1-365a18900b59 · outbound

This paper cites 3d packing for self-supervised monocular depth estimation.

The 3D Mirage: Probing and Taming 3D Hallucinations 3d packing for self-supervised monocular depth estimation

Reference 21

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Observation 253cdb05-822c-42e1-a831-2ba2043558c3 · outbound

This paper cites Monocular depth estimation using whole strip masking and reliability-based refinement.

The 3D Mirage: Probing and Taming 3D Hallucinations Monocular depth estimation using whole strip masking and reliability-based refinement

Reference 22

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Observation 58d6b9c1-525f-454e-8e22-b6047efe2357 · outbound

This paper cites Back to the feature: clas- sical 3d features are (almost) all you need for 3d anomaly detection.

The 3D Mirage: Probing and Taming 3D Hallucinations Back to the feature: clas- sical 3d features are (almost) all you need for 3d anomaly detection

Reference 23

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Observation 38b96d49-df1e-494f-a994-a33b97c5a25c · outbound

This paper cites Parameter-Efficient Transfer Learning for NLP.

The 3D Mirage: Probing and Taming 3D Hallucinations Parameter-Efficient Transfer Learning for NLP

Reference 24

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Observation c2cb2b74-6c60-4701-9de9-efecc49a13f4 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

The 3D Mirage: Probing and Taming 3D Hallucinations Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:54.126364Z

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Observation 3ff75565-9917-424e-ae49-dd7c651997c3 · outbound

This paper cites OPERA: Alleviating hallucination in multi- modal large language models via over-trust penalty and retrospection-allocation.

The 3D Mirage: Probing and Taming 3D Hallucinations OPERA: Alleviating hallucination in multi- modal large language models via over-trust penalty and retrospection-allocation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:54.280493Z

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Observation 8cbd54af-a24a-42a0-82a9-ab67f3dc29e0 · outbound

This paper cites Hallucination In Object Detection -- A Study In Visual Part Verification.

The 3D Mirage: Probing and Taming 3D Hallucinations Hallucination In Object Detection -- A Study In Visual Part Verification

Reference 27

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Observation c9c17d42-4d83-4d8c-9171-9fe8a607f824 · outbound

This paper cites an unresolved cited work.

The 3D Mirage: Probing and Taming 3D Hallucinations Unresolved cited work

Reference 28

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Observation 9a877d2e-2d29-43b5-b401-ea5f748f4c21 · outbound

This paper cites Automated audit and self- correction algorithm for seg-hallucination using meshcnn- based on-demand generative ai.Bioengineering (Basel), 12 (1):81, 2025.

The 3D Mirage: Probing and Taming 3D Hallucinations Automated audit and self- correction algorithm for seg-hallucination using meshcnn- based on-demand generative ai.Bioengineering (Basel), 12 (1):81, 2025

Reference 29

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Observation 896831ac-9138-48f7-a544-454e9088b3b3 · outbound

This paper cites Volcano: Mitigating Multimodal Hallucination through Self-Feedback Guided Revision.

The 3D Mirage: Probing and Taming 3D Hallucinations Volcano: Mitigating Multimodal Hallucination through Self-Feedback Guided Revision

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:54.783724Z

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Observation cc5158b2-5852-457a-b6ea-9b6bc4917fae · outbound

This paper cites Mitigat- ing object hallucinations in large vision-language models through visual contrastive decoding.

The 3D Mirage: Probing and Taming 3D Hallucinations Mitigat- ing object hallucinations in large vision-language models through visual contrastive decoding

Reference 31

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Observation 31cfcf5d-4a74-4258-a7cf-587dd4a011b2 · outbound

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

The 3D Mirage: Probing and Taming 3D Hallucinations Towards scalable 3d anomaly detection and localization: A benchmark via 3d anomaly synthesis and a self-supervised learning network

Reference 32

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Observation cc1207a9-0591-4501-991e-35ac60ea6294 · outbound

This paper cites Multi-sensor object anomaly detection: Unifying appearance, geometry, and in- ternal properties.

The 3D Mirage: Probing and Taming 3D Hallucinations Multi-sensor object anomaly detection: Unifying appearance, geometry, and in- ternal properties

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Observation 43c62a5b-7041-4e40-99d1-fe0742cc7fc5 · outbound

This paper cites Online Video Instance Segmentation via Robust Context Fusion.

The 3D Mirage: Probing and Taming 3D Hallucinations Online Video Instance Segmentation via Robust Context Fusion

Reference 34

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Observation 2859950a-fa31-407b-a719-9adbc4cf421e · outbound

This paper cites Robust referring video object segmentation with cyclic structural consensus.

The 3D Mirage: Probing and Taming 3D Hallucinations Robust referring video object segmentation with cyclic structural consensus

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Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:55.440796Z

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Observation 48f818a0-3cbf-4c63-bdd8-485b0b1c7680 · outbound

This paper cites Towards noise-tolerant speech-referring video object segmentation: Bridging speech and text.

The 3D Mirage: Probing and Taming 3D Hallucinations Towards noise-tolerant speech-referring video object segmentation: Bridging speech and text

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Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:55.555955Z

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Observation da1823bb-7201-4b5d-a22a-90ee85a83e54 · outbound

This paper cites R 2-bench: Benchmarking the robustness of referring perception models under perturbations.

The 3D Mirage: Probing and Taming 3D Hallucinations R 2-bench: Benchmarking the robustness of referring perception models under perturbations

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Observation 87b29a7b-4751-44e3-a3d6-ee44ecc1a3a5 · outbound

This paper cites Qdformer: Towards ro- bust audiovisual segmentation in complex environments with quantization-based semantic decomposition.

The 3D Mirage: Probing and Taming 3D Hallucinations Qdformer: Towards ro- bust audiovisual segmentation in complex environments with quantization-based semantic decomposition

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Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:55.845951Z

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Observation 5ad4deda-ec10-43ea-923c-eecaf9fe5d40 · outbound

This paper cites Optimizing lidar placements for robust driving perception in adverse conditions.CoRR, 2024.

The 3D Mirage: Probing and Taming 3D Hallucinations Optimizing lidar placements for robust driving perception in adverse conditions.CoRR, 2024

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Observation 0820d0bd-7e70-40b3-8cf6-261a74c2c663 · outbound

This paper cites Real3d- ad: A dataset of point cloud anomaly detection.Advances in Neural Information Processing Systems, 36:30402–30415,.

The 3D Mirage: Probing and Taming 3D Hallucinations Real3d- ad: A dataset of point cloud anomaly detection.Advances in Neural Information Processing Systems, 36:30402–30415,

Reference 40

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Observation 319c2192-42ad-4552-998f-4881500fa9ae · outbound

This paper cites Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models.

The 3D Mirage: Probing and Taming 3D Hallucinations Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:56.199269Z

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Observation cc5ebadd-42c6-46a4-a483-a08fe79529b2 · outbound

This paper cites Universal adversarial perturba- tions.

The 3D Mirage: Probing and Taming 3D Hallucinations Universal adversarial perturba- tions

Reference 42

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Observation fa4e0064-12c5-40b7-b66a-bd963f27bdbf · outbound

This paper cites Hallucinat- ing hidden obstacles for unmanned surface vehicles using a compositional model.

The 3D Mirage: Probing and Taming 3D Hallucinations Hallucinat- ing hidden obstacles for unmanned surface vehicles using a compositional model

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Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:56.429863Z

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Observation 230e92e7-96d5-47bc-a31a-a5a57f323fb9 · outbound

This paper cites Deep neural networks are easily fooled: High confidence predictions for unrecognizable images.

The 3D Mirage: Probing and Taming 3D Hallucinations Deep neural networks are easily fooled: High confidence predictions for unrecognizable images

Reference 44

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Observation e2f81b8a-e148-4e7b-a345-60fff0dec929 · outbound

This paper cites Penn- fudan database for pedestrian detection and segmentation,.

The 3D Mirage: Probing and Taming 3D Hallucinations Penn- fudan database for pedestrian detection and segmentation,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:56.727716Z

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Observation 410ddd2b-b90a-462e-9a55-d088e3e036ef · outbound

This paper cites Image tokenizer needs post-training.arXiv preprint arXiv:2509.12474, 2025.

The 3D Mirage: Probing and Taming 3D Hallucinations Image tokenizer needs post-training.arXiv preprint arXiv:2509.12474, 2025

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Observation 2014b138-2185-42a4-944e-a171d0140c40 · outbound

This paper cites Robust Latent Matters: Boosting Image Generation with Sampling Error Synthesis.

The 3D Mirage: Probing and Taming 3D Hallucinations Robust Latent Matters: Boosting Image Generation with Sampling Error Synthesis

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Observation 00d074d9-5744-4ded-adc3-b23bdba8f8e2 · outbound

This paper cites Vi- sion transformers for dense prediction.

The 3D Mirage: Probing and Taming 3D Hallucinations Vi- sion transformers for dense prediction

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Observation 5f19a010-3103-4189-baa1-42e21d47114e · outbound

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The 3D Mirage: Probing and Taming 3D Hallucinations Unresolved cited work

Reference 49

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Observation 3bce621d-5824-40c6-b83f-a25e988dbba3 · outbound

This paper cites Asymmetric student-teacher networks for indus- trial anomaly detection.

The 3D Mirage: Probing and Taming 3D Hallucinations Asymmetric student-teacher networks for indus- trial anomaly detection

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Observation 1bb25248-384c-422b-8522-0b80e52b38b9 · outbound

This paper cites Chung, and Andrew Y.

The 3D Mirage: Probing and Taming 3D Hallucinations Chung, and Andrew Y

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Observation 8361f4ec-a1fc-4aec-ba44-3e658ced4b5d · outbound

This paper cites Indoor segmentation and support inference from RGBD images.

The 3D Mirage: Probing and Taming 3D Hallucinations Indoor segmentation and support inference from RGBD images

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Observation e19e57f5-303b-49aa-a178-cbb4f2c460f6 · outbound

This paper cites Don’t judge an object by its context: Learning to overcome con- textual bias.

The 3D Mirage: Probing and Taming 3D Hallucinations Don’t judge an object by its context: Learning to overcome con- textual bias

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Observation 199ca8ee-cf62-4c1a-b99e-ddec7a862933 · outbound

This paper cites an unresolved cited work.

The 3D Mirage: Probing and Taming 3D Hallucinations Unresolved cited work

Reference 54

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Observation 872b65bd-45cb-4242-ab06-3a4a3a290283 · outbound

This paper cites Self-supervised feature adaptation for 3d industrial anomaly detection.

The 3D Mirage: Probing and Taming 3D Hallucinations Self-supervised feature adaptation for 3d industrial anomaly detection

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Observation c39138ba-d325-41c0-89a7-7f38969c84db · outbound

This paper cites Tartanair: A dataset to push the limits of visual SLAM.

The 3D Mirage: Probing and Taming 3D Hallucinations Tartanair: A dataset to push the limits of visual SLAM

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Observation 3d12707e-84bc-43d8-9090-ed1704691c74 · outbound

This paper cites Multimodal industrial anomaly detection via hybrid fusion.

The 3D Mirage: Probing and Taming 3D Hallucinations Multimodal industrial anomaly detection via hybrid fusion

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Observation 27845f0c-1c13-490a-8819-b6f64457713e · outbound

This paper cites an unresolved cited work.

The 3D Mirage: Probing and Taming 3D Hallucinations Unresolved cited work

Reference 58

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Observation 9836c506-bff1-40a2-85e3-eb2a20950360 · outbound

This paper cites Targeted adver- sarial perturbations for monocular depth prediction.

The 3D Mirage: Probing and Taming 3D Hallucinations Targeted adver- sarial perturbations for monocular depth prediction

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:58.229934Z

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Observation 393417a9-f874-4afd-8459-d237df711327 · outbound

This paper cites Customizing visual-language foundation models for multi-modal anomaly detection and reasoning.

The 3D Mirage: Probing and Taming 3D Hallucinations Customizing visual-language foundation models for multi-modal anomaly detection and reasoning

Reference 60

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Observation b19a9513-1a0d-4417-831a-f501ae25b085 · outbound

This paper cites Towards Ambiguity-Free Spatial Foundation Model: Rethinking and Decoupling Depth Ambiguity.

The 3D Mirage: Probing and Taming 3D Hallucinations Towards Ambiguity-Free Spatial Foundation Model: Rethinking and Decoupling Depth Ambiguity

Reference 61

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Observation 0458193f-ac25-48be-a959-69c82acf337a · outbound

This paper cites Scal- able benchmarking and robust learning for noise-free ego- motion and 3d reconstruction from noisy video.

The 3D Mirage: Probing and Taming 3D Hallucinations Scal- able benchmarking and robust learning for noise-free ego- motion and 3d reconstruction from noisy video

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:58.618782Z

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Observation 93102c19-f4bd-4983-8486-23459366d361 · outbound

This paper cites Depth any- thing v2.

The 3D Mirage: Probing and Taming 3D Hallucinations Depth any- thing v2

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:58.738736Z

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Observation 648b595b-6f67-49b2-9aad-d235b0522a2d · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

The 3D Mirage: Probing and Taming 3D Hallucinations Depth anything: Unleashing the power of large-scale unlabeled data

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:58.894883Z

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Observation 074020e3-f845-4336-9999-e3e0780a4af2 · outbound

This paper cites Cheat- ing depth: Enhancing 3d surface anomaly detection via depth simulation.

The 3D Mirage: Probing and Taming 3D Hallucinations Cheat- ing depth: Enhancing 3d surface anomaly detection via depth simulation

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:59.012199Z

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Observation c2707757-e2f9-4349-a477-2770a5512670 · outbound

This paper cites Keep dræming: discriminative 3d anomaly detection through anomaly simulation.Pattern Recognition Letters, 181:113– 119, 2024.

The 3D Mirage: Probing and Taming 3D Hallucinations Keep dræming: discriminative 3d anomaly detection through anomaly simulation.Pattern Recognition Letters, 181:113– 119, 2024

Reference 66

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Observation a90b83f4-cb82-4351-8588-eb4e7a624f8a · outbound

This paper cites Bridging 3d anomaly localization and repair via high-quality continuous geometric representation.

The 3D Mirage: Probing and Taming 3D Hallucinations Bridging 3d anomaly localization and repair via high-quality continuous geometric representation

Reference 67

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Observation 00086d53-90d7-4054-8003-5187f798560c · outbound

This paper cites Physical 3d adversarial attacks against monocular depth estimation in autonomous driving.

The 3D Mirage: Probing and Taming 3D Hallucinations Physical 3d adversarial attacks against monocular depth estimation in autonomous driving

Reference 68

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Observation 2a3ad187-3ac0-4c26-9ece-3c00cac3dfb2 · outbound

This paper cites an unresolved cited work.

The 3D Mirage: Probing and Taming 3D Hallucinations Unresolved cited work

Reference 69

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Observation da36efcd-dbee-44bd-b4a6-0975529df587 · outbound

This paper cites R3d-ad: Reconstruction via diffu- sion for 3d anomaly detection.

The 3D Mirage: Probing and Taming 3D Hallucinations R3d-ad: Reconstruction via diffu- sion for 3d anomaly detection

Reference 70

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