TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection | Paper Citation Record

Observation 80b54a0b-3edd-4640-86a1-36c305d322aa · outbound

This paper cites Towards robust au- tonomous driving: Out-of-distribution object detection in bird’s eye view space.IEEE Open Journal of Vehicular Technology.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Towards robust au- tonomous driving: Out-of-distribution object detection in bird’s eye view space.IEEE Open Journal of Vehicular Technology

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.865065Z

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

Observation 8ccb6d31-3385-47ef-9d7d-14ec9a6d69d9 · outbound

This paper cites Id-like prompt learning for few-shot out-of-distribution detection.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Id-like prompt learning for few-shot out-of-distribution detection

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.869897Z

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 e603d8db-9915-4bbf-8c61-537cc9985200 · outbound

This paper cites In or out? fixing imagenet out- of-distribution detection evaluation.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection In or out? fixing imagenet out- of-distribution detection evaluation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.881096Z

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 794254f5-48f2-43ac-ac3e-c40c21385c77 · outbound

This paper cites Food-101–mining discriminative components with random forests.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Food-101–mining discriminative components with random forests

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.855936Z

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 8478cb2a-7c42-4f4a-ad5f-252f888c355e · outbound

This paper cites Envisioning outlier exposure by large language models for out-of-distribution detection.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Envisioning outlier exposure by large language models for out-of-distribution detection

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.843669Z

Source-reported events for the cited work

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Observation 702f7ea9-0d33-4695-99ff-0ce671828ef7 · outbound

This paper cites Conjugated semantic pool improves OOD detection with pre-trained vision-language models.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Conjugated semantic pool improves OOD detection with pre-trained vision-language models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.877437Z

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Observation 8a1d6733-5c45-4d45-9603-ba345eac9a3d · outbound

This paper cites Describing textures in the wild.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Describing textures in the wild

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.847476Z

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 021c77b5-8092-4a59-9648-9e6f0b39347a · outbound

This paper cites Imagenet: A large- scale hierarchical image database.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Imagenet: A large- scale hierarchical image database

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.851952Z

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 50612a7c-1c28-42e3-b4d6-a9d93e5f12d4 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research [best of the web].IEEE signal processing magazine, 29(6):141–142.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection The mnist database of handwritten digit images for machine learning research [best of the web].IEEE signal processing magazine, 29(6):141–142

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.873876Z

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 a7f8318b-97c0-4afb-abdd-ae45a6c83615 · outbound

This paper cites Extremely simple activation shaping for out-of-distribution detection.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Extremely simple activation shaping for out-of-distribution detection

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.888137Z

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 f34f5184-3553-4e6a-8b4f-7259e203d0f1 · outbound

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

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection An image is worth 16x16 words: Transformers for image recognition at scale

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.832331Z

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 17b3176a-8246-4159-861b-37531e4995e9 · outbound

This paper cites SIREN: shaping representations for detecting out-of-distribution objects.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection SIREN: shaping representations for detecting out-of-distribution objects

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.836105Z

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 0d896bdf-25a4-4447-8927-5b241f7f0fcf · outbound

This paper cites V os: Learning what you don’t know by virtual outlier synthesis.Proceedings of the International Conference on Learning Representa- tions.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection V os: Learning what you don’t know by virtual outlier synthesis.Proceedings of the International Conference on Learning Representa- tions

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.840098Z

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 43622142-1a70-46ce-a45e-f12a8259bd5e · outbound

This paper cites Clipscope: Enhancing zero-shot ood detection with bayesian scoring.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Clipscope: Enhancing zero-shot ood detection with bayesian scoring

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.733144Z

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 da427e55-6313-40f7-b1b5-f765568b96ed · outbound

This paper cites Aucseg: Auc-oriented pixel-level long-tail semantic segmentation.Advances in Neural Information Processing Systems, 37:126863–126907.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Aucseg: Auc-oriented pixel-level long-tail semantic segmentation.Advances in Neural Information Processing Systems, 37:126863–126907

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.775546Z

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 5374f95c-60c7-45b2-ae66-dec19d7a4b14 · outbound

This paper cites Deep residual learning for image recognition.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Deep residual learning for image recognition

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.755845Z

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 3090f296-0793-4c11-8f96-754c83dd0490 · outbound

This paper cites A baseline for detecting misclassified and out-of-distribution examples in neural networks.Proceedings of International Conference on Learning Represen- tations.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection A baseline for detecting misclassified and out-of-distribution examples in neural networks.Proceedings of International Conference on Learning Represen- tations

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.816507Z

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 d371aa56-66d7-476d-87dc-6f34731e144f · outbound

This paper cites Deep anomaly detection with outlier exposure.Proceedings of the International Conference on Learning Representations.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Deep anomaly detection with outlier exposure.Proceedings of the International Conference on Learning Representations

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.771779Z

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 e510b22a-762b-446a-9891-e95abdce2416 · outbound

This paper cites Using self-supervised learning can improve model robustness and uncertainty.Advances in neural information processing systems, 32.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Using self-supervised learning can improve model robustness and uncertainty.Advances in neural information processing systems, 32

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.952828Z

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 fa1cf818-1870-4d34-908d-cec1c9e43e08 · outbound

This paper cites AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:41:43.583795Z

Source-reported events for the cited work

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Observation f2cc94b4-fe94-4463-a791-3b43048f2851 · outbound

This paper cites The many faces of robustness: A critical analysis of out-of-distribution generalization.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection The many faces of robustness: A critical analysis of out-of-distribution generalization

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.956252Z

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 c3d2d9f2-8ec4-490a-bcda-7ca14782b731 · outbound

This paper cites Pixmix: Dreamlike pictures comprehensively improve safety measures.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Pixmix: Dreamlike pictures comprehensively improve safety measures

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.935287Z

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 93c130ae-0424-4b2b-9f70-a6414a05ddf2 · outbound

This paper cites Mos: Towards scaling out-of-distribution detection for large semantic space.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Mos: Towards scaling out-of-distribution detection for large semantic space

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.945580Z

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 7b4a6d79-2067-4e0d-a261-89747bbf529f · outbound

This paper cites On the importance of gradients for detecting distributional shifts in the wild.Advances in Neural Information Processing Systems, 34: 677–689.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection On the importance of gradients for detecting distributional shifts in the wild.Advances in Neural Information Processing Systems, 34: 677–689

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.931609Z

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 b5d7bbdb-0c59-4c91-b66c-e5af68ae42bd · outbound

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

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Negative label guided ood detection with pretrained vision-language models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.926277Z

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 64d8c3c5-2701-46d5-8c1f-07c4ab15fa11 · outbound

This paper cites Opengan: Open-set recognition via open data generation.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Opengan: Open-set recognition via open data generation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.949157Z

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 88b6a0a8-a507-4d42-a57e-ed12b9280c05 · outbound

This paper cites Learning multiple layers of features from tiny images.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Learning multiple layers of features from tiny images

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.966803Z

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 1abc610d-ca5c-4e15-9117-a232d9a6a309 · outbound

This paper cites Tiny imagenet visual recognition challenge.CS 231N, 7(7):3.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Tiny imagenet visual recognition challenge.CS 231N, 7(7):3

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.918111Z

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 fc26d173-7347-49b9-9910-a60932afd5bd · outbound

This paper cites A simple unified framework for detecting out-of-distribution samples and adversarial attacks.Advances in neural information processing systems, 31.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection A simple unified framework for detecting out-of-distribution samples and adversarial attacks.Advances in neural information processing systems, 31

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.884625Z

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 421bd409-7356-4e30-b092-5a0d81513b71 · outbound

This paper cites Enhancing the reliability of out-of-distribution image detection in neural networks.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Enhancing the reliability of out-of-distribution image detection in neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.913866Z

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 3454b5af-52a9-4031-9211-5aa80da619c4 · outbound

This paper cites Energy-based out-of-distribution detection.Advances in neural information processing systems, 33:21464–21475.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Energy-based out-of-distribution detection.Advances in neural information processing systems, 33:21464–21475

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.922190Z

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 19545852-e4c0-4ba2-87a2-23466fefb0af · outbound

This paper cites Gen: Pushing the limits of softmax-based out-of-distribution detection.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Gen: Pushing the limits of softmax-based out-of-distribution detection

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.779272Z

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 2781a692-a23b-4264-aab3-347d7dc42ee6 · outbound

This paper cites Wordnet: a lexical database for english.Communications of the ACM, 38(11): 39–41.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Wordnet: a lexical database for english.Communications of the ACM, 38(11): 39–41

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.970199Z

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 dab65aa5-9c95-43a7-8417-4e8e7d5fd608 · outbound

This paper cites Delving into out-of- distribution detection with vision-language representations.Advances in neural information processing systems, 35:35087–35102.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Delving into out-of- distribution detection with vision-language representations.Advances in neural information processing systems, 35:35087–35102

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.805735Z

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 bf0f81e6-4231-4fd3-a796-911fc980f158 · outbound

This paper cites How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:43.604444Z

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 d2cb0aa6-5bbc-4ad8-848c-01c172286571 · outbound

This paper cites Cross the gap: Exposing the intra-modal misalignment in clip via modality inversion.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Cross the gap: Exposing the intra-modal misalignment in clip via modality inversion

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.748158Z

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 a4ff1b55-347c-4bd2-8204-270d8d7b298b · outbound

This paper cites Locoop: Few-shot out-of-distribution detection via prompt learning.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Locoop: Few-shot out-of-distribution detection via prompt learning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.783108Z

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 b8e2e1ba-e073-403e-a604-e82658492879 · outbound

This paper cites Reading digits in natural images with unsupervised feature learning.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Reading digits in natural images with unsupervised feature learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.824848Z

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 5144acee-b7e3-40f4-9fb7-f6031e1f1057 · outbound

This paper cites Out- of-distribution detection with negative prompts.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Out- of-distribution detection with negative prompts

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.767396Z

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 8af0d169-94f5-42ab-987c-f976f6d4ac1d · outbound

This paper cites Learning transferable visual models from natural language supervision.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Learning transferable visual models from natural language supervision

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.801825Z

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 6c856f31-a61c-48c8-8aca-74c2aaa17b28 · outbound

This paper cites Do imagenet classifiers generalize to imagenet? InInternational conference on machine learning, pages 5389–5400.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Do imagenet classifiers generalize to imagenet? InInternational conference on machine learning, pages 5389–5400

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.794369Z

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 54f922ed-8ebf-4de6-92d1-041fd12463fb · outbound

This paper cites Out-of-domain detection based on generative adversarial network.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Out-of-domain detection based on generative adversarial network

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.751708Z

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 1afa5d9f-598b-49eb-8b35-caf2400c535c · outbound

This paper cites SSD: A Unified Framework for Self-Supervised Outlier Detection.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection SSD: A Unified Framework for Self-Supervised Outlier Detection

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:43.592640Z

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 8eb2b240-2a3f-456a-bbca-52c49b51e3d4 · outbound

This paper cites React: Out-of-distribution detection with rectified activations.Advances in Neural Information Processing Systems, 34:144–157.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection React: Out-of-distribution detection with rectified activations.Advances in Neural Information Processing Systems, 34:144–157

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.790344Z

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 d160da40-4553-4e0f-984e-e85514ead361 · outbound

This paper cites Out-of-distribution detection with deep nearest neighbors.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Out-of-distribution detection with deep nearest neighbors

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.721790Z

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 22b35e5d-18bc-4489-b221-4d62d9d7140c · outbound

This paper cites The inaturalist species classification and detection dataset.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection The inaturalist species classification and detection dataset

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.744327Z

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 79bc533e-c647-4cb2-8cb4-d117f28bacbf · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Attention is all you need.Advances in neural information processing systems, 30

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.763101Z

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 4e71e4a2-c29c-42ac-9a46-a3af07c3b72a · outbound

This paper cites BIMCV COVID-19+: a large annotated dataset of RX and CT images from COVID-19 patients.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection BIMCV COVID-19+: a large annotated dataset of RX and CT images from COVID-19 patients

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:43.647801Z

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 e23aecbb-34f3-4428-bad1-3d0b327cb8eb · outbound

This paper cites Open-set recognition: A good closed-set classifier is all you need.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Open-set recognition: A good closed-set classifier is all you need

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.739865Z

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 c1b774c7-78c8-436b-9b7a-8723de8d0601 · outbound

This paper cites Learning robust global repre- sentations by penalizing local predictive power.Advances in neural information processing systems, 32.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Learning robust global repre- sentations by penalizing local predictive power.Advances in neural information processing systems, 32

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.820446Z

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 e230eef8-0933-4c6f-b9e8-061c509051ed · outbound

This paper cites Vim: Out-of-distribution with virtual-logit matching.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Vim: Out-of-distribution with virtual-logit matching

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.729673Z

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 a73f35ac-87f8-451c-bfa1-c845bf981d21 · outbound

This paper cites Application of uncertainty to out-of- distribution detection for autonomous driving perception safety.IEEE Transactions on Intelli- gent Transportation Systems.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Application of uncertainty to out-of- distribution detection for autonomous driving perception safety.IEEE Transactions on Intelli- gent Transportation Systems

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.725923Z

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 3b37972e-774c-405a-ba7f-66d4e63ad021 · outbound

This paper cites Sun database: Large-scale scene recognition from abbey to zoo.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Sun database: Large-scale scene recognition from abbey to zoo

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.786807Z

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 ab686ab6-678d-48ea-9242-9cc026cfc9e8 · outbound

This paper cites Scaling for training time and post-hoc out-of-distribution detection enhancement.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Scaling for training time and post-hoc out-of-distribution detection enhancement

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.736459Z

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 296b680d-e8fa-4838-a9dd-dc1b1e3394ed · outbound

This paper cites Mind the Way You Select Negative Texts: Pursuing the Distance Consistency in OOD Detection with VLMs.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Mind the Way You Select Negative Texts: Pursuing the Distance Consistency in OOD Detection with VLMs

Reference 55

Resolution: verified exact; local_arxiv, observed 2026-05-12T06:41:43.618245Z

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 bdef3c6c-71ab-4e34-90e9-2eea1a39189e · outbound

This paper cites Oodd: Test-time out-of-distribution detection with dynamic dictionary.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Oodd: Test-time out-of-distribution detection with dynamic dictionary

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.809432Z

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 8f984303-addb-49ef-946d-ac95231a914c · outbound

This paper cites Out-of-distribution detection using union of 1-dimensional subspaces.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Out-of-distribution detection using union of 1-dimensional subspaces

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.759568Z

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 43f1f44c-d0c2-4263-b8c0-6edbc386c23c · outbound

This paper cites Openood v1.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Openood v1

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.797641Z

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 b6bd2d7d-cd32-4ece-85c9-756f1752e27b · outbound

This paper cites Adaneg: Adaptive negative proxy guided ood detection with vision-language models.Advances in Neural Information Processing Systems, 37:38744–38768.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Adaneg: Adaptive negative proxy guided ood detection with vision-language models.Advances in Neural Information Processing Systems, 37:38744–38768

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.904882Z

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 76b3bbb8-0e36-489a-a919-36fe949e7787 · outbound

This paper cites Lapt: Label-driven automated prompt tuning for ood detection with vision-language models.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Lapt: Label-driven automated prompt tuning for ood detection with vision-language models

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.893338Z

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 53c4c63e-4192-4ee0-a1ce-f86cff599c63 · outbound

This paper cites Activation matters: Test-time activated negative labels for ood detection with vision-language models.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Activation matters: Test-time activated negative labels for ood detection with vision-language models

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:43.639994Z

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 adbd2914-e70d-4c74-b45b-1cc81af4e010 · outbound

This paper cites Places: A 10 million image database for scene recognition.IEEE transactions on pattern analysis and machine intelligence, 40(6):1452–1464.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Places: A 10 million image database for scene recognition.IEEE transactions on pattern analysis and machine intelligence, 40(6):1452–1464

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T17:01:43.812868Z

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 f31f223f-26f6-47ce-9c3b-f314bc303c0b · outbound

This paper cites Ants: Adaptive negative textual space shaping for ood detection via test-time mllm understanding and reasoning.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection Ants: Adaptive negative textual space shaping for ood detection via test-time mllm understanding and reasoning

Reference 63

Resolution: malformed identifier; arxiv_id, observed 2026-05-12T06:41:43.656604Z

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 c69c5995-7852-4999-b10c-2379fc10a7b3 · outbound

This paper cites On CIFAR-10, our method also achieves the best performance.

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection On CIFAR-10, our method also achieves the best performance

Reference 64

Resolution: malformed identifier; raw_fallback, observed 2026-05-12T17:01:43.828555Z

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.

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