Neural Distribution Prior for LiDAR Out-of-Distribution Detection | Paper Citation Record

Observation 75755c99-ed9a-42fb-9298-fb75c2c835f3 · outbound

This paper cites Se- manticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Se- manticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.207498Z

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Observation 49ea63f3-f4b8-4982-bc90-8809a21757c1 · outbound

This paper cites Seeing through fog without seeing fog: Deep multimodal sensor fu- sion in unseen adverse weather.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Seeing through fog without seeing fog: Deep multimodal sensor fu- sion in unseen adverse weather

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.021152Z

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Observation 15a1921d-c890-4eb5-bec4-1c69f764b11a · outbound

This paper cites Nieto, Roland Y.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Nieto, Roland Y

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.078927Z

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Observation bdb914fd-fa28-4fc1-9a35-d8894cc17d64 · outbound

This paper cites The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation.Interna- tional Journal on Computer Vision (IJCV).

Neural Distribution Prior for LiDAR Out-of-Distribution Detection The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation.Interna- tional Journal on Computer Vision (IJCV)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.086935Z

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Observation a293f920-8546-4fcb-be55-70645be2e558 · outbound

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

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.090791Z

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Observation 2ad31638-8127-4d81-8318-9ef3ddc68946 · outbound

This paper cites Learning imbalanced datasets with label- distribution-aware margin loss.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Learning imbalanced datasets with label- distribution-aware margin loss

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.056457Z

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Observation 2dfc39a5-a10f-4fb9-98fe-61152b7cc108 · outbound

This paper cites Open- world semantic segmentation for lidar point clouds.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Open- world semantic segmentation for lidar point clouds

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.101184Z

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Observation 5093b969-ddac-4c3a-8f44-5a0532dd1869 · outbound

This paper cites SegmentMeIfYou- Can: A Benchmark for Anomaly Segmentation.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection SegmentMeIfYou- Can: A Benchmark for Anomaly Segmentation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.182151Z

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Observation fc72115c-64f4-4daf-887e-0599a04cb692 · outbound

This paper cites Entropy maximization and meta classification for out-of- distribution detection in semantic segmentation.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Entropy maximization and meta classification for out-of- distribution detection in semantic segmentation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.097841Z

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Observation 69c6a111-844e-4775-93e8-4c453116c4ae · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection ShapeNet: An Information-Rich 3D Model Repository

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T16:09:06.508173Z

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Observation 51b4263f-7e56-4a69-8168-1006207cf4ca · outbound

This paper cites Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.094298Z

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Observation 6aa730a9-f2eb-4619-a414-e9b41d1ad877 · outbound

This paper cites Dual energy-based model with open- world uncertainty estimation for out-of-distribution detec- tion.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Dual energy-based model with open- world uncertainty estimation for out-of-distribution detec- tion

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.059826Z

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Observation 35863c6a-0b70-44d3-afd8-4ff073de02b5 · outbound

This paper cites Schwing, Alexan- der Kirillov, and Rohit Girdhar.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Schwing, Alexan- der Kirillov, and Rohit Girdhar

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.077327Z

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Observation f4eaa415-ec5c-4c14-a480-073dda79eaa4 · outbound

This paper cites Schwing, and Alexander Kir- illov.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Schwing, and Alexander Kir- illov

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.070645Z

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Observation 864fbb81-5d40-4030-bc34-44c4c229edbe · outbound

This paper cites 3d-pnas: 3d industrial surface anomaly synthesis with perlin noise.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection 3d-pnas: 3d industrial surface anomaly synthesis with perlin noise

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.104710Z

Source-reported events for the cited work

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Observation 6a36d40c-4ae6-41fc-9a03-4cb20e26f50d · outbound

This paper cites Bal- anced energy regularization loss for out-of-distribution de- tection.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Bal- anced energy regularization loss for out-of-distribution de- tection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.037081Z

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Observation f7595e14-93b8-4a3b-a548-ee1571d55839 · outbound

This paper cites 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neu- ral Networks.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neu- ral Networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.074546Z

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Observation 6a21da85-6c8f-4fbb-9047-c5982fa9495d · outbound

This paper cites Outlier detec- tion by ensembling uncertainty with negative objectness.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Outlier detec- tion by ensembling uncertainty with negative objectness

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.115538Z

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Observation 42609c9f-b2b4-44fb-b388-e0ca21546d6d · outbound

This paper cites V os: Learning what you don’t know by virtual outlier synthe- sis.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection V os: Learning what you don’t know by virtual outlier synthe- sis

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:09.990311Z

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Observation f5b99cee-84f2-4496-bc5c-a5aa305a7234 · outbound

This paper cites A density-based algorithm for discovering clusters in large spatial databases with noise.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection A density-based algorithm for discovering clusters in large spatial databases with noise

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.134681Z

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Observation 02e191ae-fa5e-4e06-95c1-9a4f6ff37a31 · outbound

This paper cites Is out-of-distribution detection learnable? InPro- ceedings of the 36th International Conference on Neural In- formation Processing Systems, Red Hook, NY , USA.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Is out-of-distribution detection learnable? InPro- ceedings of the 36th International Conference on Neural In- formation Processing Systems, Red Hook, NY , USA

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.162141Z

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Observation 04651307-68ce-412f-a09f-7ff369b02c6b · outbound

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

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Vision meets robotics: The kitti dataset.Interna- tional Journal of Robotics Research (IJRR)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.158329Z

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Observation 707f5c90-1a49-4a7a-ba0c-91f557021bbc · outbound

This paper cites Densehy- brid: Hybrid anomaly detection for dense open-set recogni- tion.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Densehy- brid: Hybrid anomaly detection for dense open-set recogni- tion

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.119809Z

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Observation 660131b6-2c22-4be9-898e-de0d61907e63 · outbound

This paper cites A Baseline for Detect- ing Misclassified and Out-of-Distribution Examples in Neu- ral Networks.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection A Baseline for Detect- ing Misclassified and Out-of-Distribution Examples in Neu- ral Networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.204833Z

Source-reported events for the cited work

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Observation 4db9adfc-47ec-410a-893f-3078c85ea99a · outbound

This paper cites Deep Anomaly Detection with Outlier Exposure.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Deep Anomaly Detection with Outlier Exposure

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:09.977423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3df11a56-14e7-43d9-9c62-e68b8f2131e4 · outbound

This paper cites Scaling Out-of-Distribution Detection for Real- World Settings.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Scaling Out-of-Distribution Detection for Real- World Settings

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.142457Z

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Observation 6aab88a9-763e-4371-b660-2a627966f781 · outbound

This paper cites Czarnecki.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Czarnecki

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.168391Z

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Observation 4f3c8af1-30c4-424a-bb9a-a53e8107849a · outbound

This paper cites On the impor- tance of gradients for detecting distributional shifts in the wild.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection On the impor- tance of gradients for detecting distributional shifts in the wild

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.175156Z

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Observation 4e0d3bab-e521-4d53-bf61-5662a64d6b4d · outbound

This paper cites Detecting out-of-distribution data through in-distribution class prior.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Detecting out-of-distribution data through in-distribution class prior

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.202334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9b6a6de2-cf4a-4098-9590-b46730059316 · outbound

This paper cites Negative label guided OOD detection with pretrained vision-language models.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Negative label guided OOD detection with pretrained vision-language models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.188557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7b90c200-39dd-486f-b9ff-19935c1b97a7 · outbound

This paper cites Panoptic Segmentation.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Panoptic Segmentation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:09.997434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 99636c0c-f35d-4c25-9678-16a1452f0cff · outbound

This paper cites Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.171886Z

Source-reported events for the cited work

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Observation 7f4ebc5d-604d-40ad-8de2-59236b95b18e · outbound

This paper cites Simple and Scalable Predictive Uncertainty Es- timation using Deep Ensembles.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Simple and Scalable Predictive Uncertainty Es- timation using Deep Ensembles

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.199789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 85720cd4-b29a-4eea-9091-fea019cf7e08 · outbound

This paper cites A simple unified framework for detecting out-of-distribution samples and adversarial attacks.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection A simple unified framework for detecting out-of-distribution samples and adversarial attacks

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.046750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 60f79062-6869-43cf-9d69-eac4bc216d7b · outbound

This paper cites Open-set semantic segmenta- tion for point clouds via adversarial prototype framework.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Open-set semantic segmenta- tion for point clouds via adversarial prototype framework

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.049759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b00cc4df-ec55-44f4-8daf-1be0db705e9b · outbound

This paper cites Das3d: Dual-modality anomaly synthesis for 3d anomaly de- tection.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Das3d: Dual-modality anomaly synthesis for 3d anomaly de- tection

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.185823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f6451ef1-9b95-415b-921b-e8f41c8f7abd · outbound

This paper cites Out-of-distribution detection in 3D applications: a review.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Out-of-distribution detection in 3D applications: a review

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:10:54.889179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bc4ba217-e76e-41bd-8b79-8712f2a8fd36 · outbound

This paper cites Relative Energy Learning for LiDAR Out-of-Distribution Detection.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Relative Energy Learning for LiDAR Out-of-Distribution Detection

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-06-02T04:04:26.012187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 818061f8-ef8a-4a1d-a9b4-eeee0ddf2976 · outbound

This paper cites From open vocabulary to open world: Teach- ing vision language models to detect novel objects.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection From open vocabulary to open world: Teach- ing vision language models to detect novel objects

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.178656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b0af759b-91ec-498c-9bf6-1b2b1fdb8096 · outbound

This paper cites GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.138548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f9fdcba1-5b80-488d-bae4-71961a364837 · outbound

This paper cites an unresolved cited work.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-05-17T06:04:10.130953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 056237e5-01d1-48a0-af9a-6dd53965dd5f · outbound

This paper cites Rethinking out-of-distribution detection on imbalanced data distribution.Advances in Neural Information Processing Systems, 38.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Rethinking out-of-distribution detection on imbalanced data distribution.Advances in Neural Information Processing Systems, 38

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.111807Z

Source-reported events for the cited work

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Observation 2d758adb-aecd-46b0-b8d0-10706062db2d · outbound

This paper cites Energy-based out-of-distribution detection.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Energy-based out-of-distribution detection

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.108184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fdc90858-640c-45a0-baf5-9e3da707dc08 · outbound

This paper cites Reid, and Gustavo Carneiro.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Reid, and Gustavo Carneiro

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.043625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 07f40e37-4d8c-4b2b-8af5-1b585e6fcc82 · outbound

This paper cites an unresolved cited work.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-05-17T06:04:10.146050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b67d9291-69e9-406b-8c04-825d82e3fc6a · outbound

This paper cites Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.040584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3c7d75c0-80d3-4154-8de7-f5a7b4579510 · outbound

This paper cites Out-of-distribution detection in long-tailed recogni- tion with calibrated outlier class learning.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Out-of-distribution detection in long-tailed recogni- tion with calibrated outlier class learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.033052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation da718402-c4d9-41cf-9491-69c8b7dea3c3 · outbound

This paper cites Henriques, and Fatma G¨uney.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Henriques, and Fatma G¨uney

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.009243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 09d1c221-ba29-4ec0-870b-c11c0b3b22dd · outbound

This paper cites A likeli- hood ratio-based approach to segmenting unknown objects.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection A likeli- hood ratio-based approach to segmenting unknown objects

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.197365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6923bc56-c05a-496c-9751-22fc1af7fe5c · outbound

This paper cites Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Seg- mentation in Autonomous Driving.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Seg- mentation in Autonomous Driving

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.185477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5c53a0a1-adf7-496f-8d6e-6f8591cec0c3 · outbound

This paper cites The majority can help the minority: Context-rich minority oversampling for long-tailed classifi- cation.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection The majority can help the minority: Context-rich minority oversampling for long-tailed classifi- cation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:09.973932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d906f30a-9543-4a9a-9520-e101b8b09b79 · outbound

This paper cites An image synthesizer.SIGGRAPH Comput.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection An image synthesizer.SIGGRAPH Comput

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.127217Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fa45bc40-f9e0-4812-b2b6-747c1548d848 · outbound

This paper cites Unmasking Anomalies in Road-Scene Segmentation.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Unmasking Anomalies in Road-Scene Segmentation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.082970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6b728788-8a2e-4c42-8472-6ec78b913887 · outbound

This paper cites Adaptive robust evidential opti- mization for open set detection from imbalanced data.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Adaptive robust evidential opti- mization for open set detection from imbalanced data

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.182073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation aeb7626d-1176-4005-9e78-ab2384c71a7d · outbound

This paper cites Scheirer, Anderson de Rezende Rocha, Archana Sapkota, and Terrance E.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Scheirer, Anderson de Rezende Rocha, Archana Sapkota, and Terrance E

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.178926Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b8abecda-67c3-420d-a3e9-0a224b8b31f3 · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfitting.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Dropout: a simple way to prevent neural networks from overfitting

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.123547Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 449dc83d-9773-4e36-9d94-f777dfec256b · outbound

This paper cites G2sf: Geometry-guided score fusion for multimodal industrial anomaly detection.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection G2sf: Geometry-guided score fusion for multimodal industrial anomaly detection

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.154636Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3125822d-4724-4334-bb74-568adb9a4422 · outbound

This paper cites Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Com- plex Urban Driving Scenes.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Com- plex Urban Driving Scenes

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.080496Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0cb4d41c-0926-4ac6-8591-6c326224082d · outbound

This paper cites Panoptic-CUDAL Technical Report: Ru- ral Australia Point Cloud Dataset in Rainy Conditions.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Panoptic-CUDAL Technical Report: Ru- ral Australia Point Cloud Dataset in Rainy Conditions

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:10:54.896719Z

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Observation c5ad1084-0c98-4f50-9d97-a5b505117c00 · outbound

This paper cites Partial and asymmetric contrastive learning for out-of-distribution detection in long- tailed recognition.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Partial and asymmetric contrastive learning for out-of-distribution detection in long- tailed recognition

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:09.986041Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e74c5905-4749-4703-91a9-28e6904a80ab · outbound

This paper cites Watermarking for out-of-distribution detection.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Watermarking for out-of-distribution detection

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.067063Z

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Observation 04824faa-581b-492c-8813-742b097685d3 · outbound

This paper cites Learning to augment distributions for out-of-distribution detection.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Learning to augment distributions for out-of-distribution detection

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.053084Z

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Observation e9d4adaf-4894-42d1-b841-26b7036beb21 · outbound

This paper cites Out- of-distribution detection with implicit outlier transformation.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Out- of-distribution detection with implicit outlier transformation

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.063560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b42eb18f-433a-49ca-84c0-95f0a0cfc98c · outbound

This paper cites Eat: towards long-tailed out-of-distribution detection.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Eat: towards long-tailed out-of-distribution detection

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.013200Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e551a5a2-b5c7-4583-85c5-f5902d296372 · outbound

This paper cites Identifying Unknown Instances for Autonomous Driving.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Identifying Unknown Instances for Autonomous Driving

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:09.970456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7c533ab4-5076-43ce-b733-93eebb420443 · outbound

This paper cites Lion: learn- ing point-wise abstaining penalty for lidar outlier detection using diverse synthetic data.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Lion: learn- ing point-wise abstaining penalty for lidar outlier detection using diverse synthetic data

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.025052Z

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Observation fef553dd-2eab-4064-81a5-ce54c9f167fe · outbound

This paper cites Generalized out-of-distribution detection: A survey.Inter- national Journal of Computer Vision, pages 1–28.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Generalized out-of-distribution detection: A survey.Inter- national Journal of Computer Vision, pages 1–28

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.194507Z

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Observation 0355b0fa-9fa5-4df3-960c-2fac9ea9b234 · outbound

This paper cites Mask4Former: Mask Transformer for 4D Panoptic Segmentation.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Mask4Former: Mask Transformer for 4D Panoptic Segmentation

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.002643Z

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Observation f5404484-d028-4c56-ade8-5ffe19d929fe · outbound

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

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Keep drÆming: Discriminative 3d anomaly detection through anomaly simulation.Pattern Recognition Letters, 181:113– 119

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.083597Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0a8187ca-90ed-481d-ba90-7f7a1625f60c · outbound

This paper cites Darl: Mitigating gradient conflicts in long-tailed out-of-distribution learning.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Darl: Mitigating gradient conflicts in long-tailed out-of-distribution learning

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:04:10.149857Z

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Observation db7a272c-20ca-43c9-b747-2d3d19c563d7 · outbound

This paper cites Out-of-distribution detec- tion learning with unreliable out-of-distribution sources.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Out-of-distribution detec- tion learning with unreliable out-of-distribution sources

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.065379Z

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Observation bcd5cbdb-c11e-4280-a76a-b914c92abb56 · outbound

This paper cites Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmenta- tion.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmenta- tion

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.071516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6e3c17c2-c0bf-4f8a-910b-3d91e4af0532 · outbound

This paper cites The model is then fine-tuned for up to 10 epochs on the downstream datasets, with Perlin noise–synthesized OOD samples included during training.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection The model is then fine-tuned for up to 10 epochs on the downstream datasets, with Perlin noise–synthesized OOD samples included during training

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.062345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f1e96cb5-c4d8-4538-a678-5b9dd183cced · outbound

This paper cites These metrics are widely used in OOD detection and anomaly segmenta- tion [3, 8, 50, 67].

Neural Distribution Prior for LiDAR Out-of-Distribution Detection These metrics are widely used in OOD detection and anomaly segmenta- tion [3, 8, 50, 67]

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.191550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a5b0ea4d-1d9c-46bb-8916-3b2afe2b5f8f · outbound

This paper cites 4 and Fig.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection 4 and Fig

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.074010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f23dfa03-fa74-4755-9588-0fa205aca826 · outbound

This paper cites 8 presents an ablation study on the template sizedof the NDP matrixψ, whereddetermines the dimensionality of the vectors stored inψas the learnable prior.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection 8 presents an ablation study on the template sizedof the NDP matrixψ, whereddetermines the dimensionality of the vectors stored inψas the learnable prior

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.068488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bab748e0-3ac7-4eee-8bb1-5c92ae9521a7 · outbound

This paper cites This motivates the use of adaptive mechanisms such as distribution-aware priors or dynamic reweighting.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection This motivates the use of adaptive mechanisms such as distribution-aware priors or dynamic reweighting

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.056224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation cf2bcabb-c28d-4455-8241-281cc54d0e3c · outbound

This paper cites As shown in Fig.

Neural Distribution Prior for LiDAR Out-of-Distribution Detection As shown in Fig

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:01:36.052501Z

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