Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection | Paper Citation Record

Observation cf9abb15-6ede-4a93-b900-dfe52dbf2608 · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 1

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Observation 188da8e2-0827-4085-9829-d84e98fb749a · outbound

This paper cites Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks

Reference 2

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Energy-based out-of- distribution detection,

Reference 3

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Observation 2207667a-918b-40c4-9b1d-d63cf739d21e · outbound

This paper cites On the importance of gradi- ents for detecting distributional shifts in the wild,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection On the importance of gradi- ents for detecting distributional shifts in the wild,

Reference 4

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Vim: Out-of- distribution with virtual-logit matching,

Reference 5

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Observation e17fa9e2-ffba-4c7a-989f-813dbadc06a5 · outbound

This paper cites Out-of-distribution de- tection with deep nearest neighbors,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Out-of-distribution de- tection with deep nearest neighbors,

Reference 6

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Observation 55aa44ff-f4b2-41d3-bfbf-040a5324e93e · outbound

This paper cites VOS: Learning What You Don't Know by Virtual Outlier Synthesis.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection VOS: Learning What You Don't Know by Virtual Outlier Synthesis

Reference 7

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Observation 90f3f5e7-765a-4874-9dcf-d6124773699b · outbound

This paper cites Dice: Leveraging sparsification for out- of-distribution detection,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Dice: Leveraging sparsification for out- of-distribution detection,

Reference 8

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Observation 17811ade-7d80-4470-bdeb-ed04fc958a00 · outbound

This paper cites React: Out-of-distribution detec- tion with rectified activations,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection React: Out-of-distribution detec- tion with rectified activations,

Reference 9

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Observation 2dc6cb87-62fc-4177-9931-958444a7ecef · outbound

This paper cites Zero-shot out-of-distribution detection based on the pre-trained model clip,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Zero-shot out-of-distribution detection based on the pre-trained model clip,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.231265Z

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Observation 7d17151a-0bcf-487a-b0d2-6d01ed0cd072 · outbound

This paper cites Delving into out-of-distribution detection with vision-language repre- sentations,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Delving into out-of-distribution detection with vision-language repre- sentations,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.224477Z

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Observation c1fd30d2-a45d-4131-80f9-6385e4fa1782 · outbound

This paper cites Learning to prompt for vision-language models,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Learning to prompt for vision-language models,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.216529Z

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Observation 08d38643-6ae9-407a-870e-6c14633ef0a0 · outbound

This paper cites Conditional prompt learning for vision-language models,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Conditional prompt learning for vision-language models,

Reference 13

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Observation 87477dcb-3171-4eab-9d19-f826e9259aaa · outbound

This paper cites Non-Parametric Outlier Synthesis.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Non-Parametric Outlier Synthesis

Reference 14

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Observation 36cb76b6-1b19-4851-8d71-79e1a861396c · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Clipn for zero-shot ood detection: Teaching clip to say no,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.198739Z

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Observation 0640e19b-52e1-4f94-8668-18aa9634244c · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Out-of-distribution detection with negative prompts,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.190143Z

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Observation 295e75e1-5113-4fef-bd10-4f44600c75d0 · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Locoop: Few-shot out-of-distribution detection via prompt learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.182148Z

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Observation 7ffff836-eacd-4598-aac4-f43e03250826 · outbound

This paper cites Negative Label Guided OOD Detection with Pretrained Vision-Language Models.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Negative Label Guided OOD Detection with Pretrained Vision-Language Models

Reference 18

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Observation 5440a562-9cdc-4d19-9534-3e47cd73d75a · outbound

This paper cites Hierarchical visual categories modeling: A joint representation learning and density estimation frame- work for out-of-distribution detection,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Hierarchical visual categories modeling: A joint representation learning and density estimation frame- work for out-of-distribution detection,

Reference 19

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Observation 3a255ac3-e8fe-4f2f-9032-95359867ee82 · outbound

This paper cites TagOOD: A Novel Approach to Out-of-Distribution Detection via Vision-Language Representations and Class Center Learning.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection TagOOD: A Novel Approach to Out-of-Distribution Detection via Vision-Language Representations and Class Center Learning

Reference 20

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This paper cites Wordnet: a lexical database for english,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Wordnet: a lexical database for english,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.166064Z

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Observation c879c597-8bd8-4148-99bb-cd47c346e383 · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Learning transferable visual models from natural language supervision,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.159263Z

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Observation 41dc0851-4139-4280-9f8a-f0e0dccb8174 · outbound

This paper cites Visual instruction tun- ing,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Visual instruction tun- ing,

Reference 23

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This paper cites Qwen Technical Report.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Qwen Technical Report

Reference 24

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,

Reference 25

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Observation a59495d0-bd17-4842-bd1c-73c8e02a1874 · outbound

This paper cites Gpt-4 technical report,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Gpt-4 technical report,

Reference 26

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Observation 452e1b4c-3945-40ff-9350-564ac90e5295 · outbound

This paper cites Available: https://cdn.openai.com/papers/gpt- 4.pdf 1.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Available: https://cdn.openai.com/papers/gpt- 4.pdf 1

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.129214Z

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Observation c2156ed3-97e5-4fa7-a411-1db3ca2d408d · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection High-resolution image synthesis with latent diffusion models,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.122130Z

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Observation ab2ca178-37ae-4f1e-9066-3e2b9c032e63 · outbound

This paper cites SDXL: Improving latent diffusion models for high-resolution im- age synthesis,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection SDXL: Improving latent diffusion models for high-resolution im- age synthesis,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.114379Z

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Observation 3e7b8943-0a7f-480d-95f2-a5a341da0abf · outbound

This paper cites Auto-Encoding Variational Bayes.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Auto-Encoding Variational Bayes

Reference 30

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This paper cites Deep residual learning for image recognition,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Deep residual learning for image recognition,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.103736Z

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This paper cites U-net: Con- volutional networks for biomedical image segmenta- tion,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection U-net: Con- volutional networks for biomedical image segmenta- tion,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.095335Z

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Observation abd796b8-547a-4d07-92f9-e5a812026da9 · outbound

This paper cites an unresolved cited work.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Unresolved cited work

Reference 33

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This paper cites Content-based unrestricted adversarial at- tack,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Content-based unrestricted adversarial at- tack,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.079985Z

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Observation eb63a126-14e6-463a-8206-b927a2486564 · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Mos: Towards scaling out-of- distribution detection for large semantic space,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.071874Z

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Observation 35fdad93-372d-46ad-a575-4e2a7b1c27c5 · outbound

This paper cites Imagenet large scale visual recognition challenge,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Imagenet large scale visual recognition challenge,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.063574Z

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Observation 6c62a6de-f2b1-45da-87c5-b51d9e3996e7 · outbound

This paper cites The inat- uralist species classification and detection dataset,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection The inat- uralist species classification and detection dataset,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.054501Z

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Observation 4fc7d802-50f1-4143-aeca-075762ccf0ff · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Sun database: Large-scale scene recognition from abbey to zoo,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.045512Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d1710722-4aa1-4d2e-935e-34aeb77df5bb · outbound

This paper cites Places: A 10 million image database for scene recognition,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Places: A 10 million image database for scene recognition,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.037008Z

Source-reported events for the cited work

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Observation 0544d393-ed7a-416d-8b1a-f84be94cc820 · outbound

This paper cites Describing textures in the wild,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Describing textures in the wild,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.028619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f62797d3-ff32-4b19-8160-2097ac03e9f2 · outbound

This paper cites Openood: Benchmarking generalized out-of-distribution detection,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Openood: Benchmarking generalized out-of-distribution detection,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.021248Z

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Observation 5a52233f-a769-458c-b683-e1c5f016c098 · outbound

This paper cites OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection

Reference 42

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Observation 7b65e78d-5463-4d5f-96dd-339df81e7386 · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Open-set recognition: A good closed-set classifier is all you need,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.013205Z

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Observation 7363c3f6-118b-4e4a-a5ba-40dfbb79b22c · outbound

This paper cites In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation

Reference 44

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Observation ed647e26-0d2e-41ef-835b-54090828a275 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:59.005125Z

Source-reported events for the cited work

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Observation b554bbb1-1ec8-4283-ad57-306b1c2cea82 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 46

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This paper cites Densely connected convolutional networks,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Densely connected convolutional networks,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.996704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f823966b-bc76-468f-b6d8-01016349d43a · outbound

This paper cites Aggre- gated residual transformations for deep neural networks,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Aggre- gated residual transformations for deep neural networks,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.988171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 02d1ae8b-e4b8-47ba-b118-d1c9450048c1 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Pytorch: An imperative style, high-performance deep learning library,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.979309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 352a7348-fa7d-4dbd-96d7-e43222faafd2 · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Gen: Pushing the limits of softmax-based out-of-distribution detection,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.970723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e3096930-bd40-4443-bb5a-ca48fcd65424 · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:56.359563Z

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Observation 3d8616f1-7ebd-451a-b8e6-f0ca02eb46c2 · outbound

This paper cites A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:56.414074Z

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Observation 887b8824-afba-4739-b035-564625101390 · outbound

This paper cites Extremely Simple Activation Shaping for Out-of-Distribution Detection.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Extremely Simple Activation Shaping for Out-of-Distribution Detection

Reference 53

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Observation adc90ba7-f64c-43b1-95ef-3c37cc9735e7 · outbound

This paper cites Natural adversarial examples,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Natural adversarial examples,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.961911Z

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Observation 2f119868-66a8-4e01-bce9-21d61071eee5 · outbound

This paper cites A simple unified frame- work for detecting out-of-distribution samples and adversar- ial attacks,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection A simple unified frame- work for detecting out-of-distribution samples and adversar- ial attacks,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.952998Z

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Observation dbf6493f-b6c7-4c90-9e1c-07c26bbc3668 · outbound

This paper cites Contrastive Training for Improved Out-of-Distribution Detection.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Contrastive Training for Improved Out-of-Distribution Detection

Reference 56

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Observation 7b5e77ba-fa0f-4f83-8990-bc8dc0bf431e · outbound

This paper cites A boundary based out-of-distribution classifier for generalized zero-shot learn- ing,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection A boundary based out-of-distribution classifier for generalized zero-shot learn- ing,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.944661Z

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Observation e263e5fa-8f7f-49c3-9b72-1e8eb95e4891 · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Out-of-distribution detection using union of 1-dimensional subspaces,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.936065Z

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Observation 44c341a3-e457-487f-8f1a-fa7597fd7884 · outbound

This paper cites Un- certainty estimation using a single deep deterministic neural network,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Un- certainty estimation using a single deep deterministic neural network,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.927519Z

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Observation 3800114e-0f8c-4d2f-9f0f-2c4eeb3f233d · outbound

This paper cites Feature Space Singularity for Out-of-Distribution Detection.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Feature Space Singularity for Out-of-Distribution Detection

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:42:57.752985Z

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Observation 3cc2724e-f7ee-470c-bf26-ff564338cbed · outbound

This paper cites Exploring the limits of out-of-distribution detection,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Exploring the limits of out-of-distribution detection,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.919263Z

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Observation 750559d0-7c72-48d4-84d0-b6ab28495fb6 · outbound

This paper cites Visual instruction tuning,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Visual instruction tuning,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.910965Z

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Observation dc9e15ae-57b1-4e61-a7b6-f0e57f3e3ad1 · outbound

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

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Lapt: Label-driven automated prompt tuning for ood detection with vision- language models,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.839551Z

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Observation ed5d0856-f01d-4162-a4d7-d380eea978a3 · outbound

This paper cites Dream the impossi- ble: Outlier imagination with diffusion models,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Dream the impossi- ble: Outlier imagination with diffusion models,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.691032Z

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Observation 70b55591-7b60-4c5d-907a-24f6964f1430 · outbound

This paper cites Conjugated semantic pool im- proves ood detection with pre-trained vision-language mod- els,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Conjugated semantic pool im- proves ood detection with pre-trained vision-language mod- els,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.500816Z

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Observation dde5ecae-00a7-42cb-803e-524e15783d35 · outbound

This paper cites Adaneg: Adaptive negative proxy guided OOD detection with vision-language models,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Adaneg: Adaptive negative proxy guided OOD detection with vision-language models,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.417011Z

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Observation ade941f8-716d-4bfd-b1ae-52fd883b85fd · outbound

This paper cites Is out- of-distribution detection learnable?.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Is out- of-distribution detection learnable?

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.319562Z

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Observation 6e131da6-0473-460e-a55b-e9789ac3f492 · outbound

This paper cites Out-of-distribution detection learning with unreli- able out-of-distribution sources,.

Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection Out-of-distribution detection learning with unreli- able out-of-distribution sources,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:58.239512Z

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