Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention | Paper Citation Record

Observation ac5394c4-e452-4d4d-8ef3-685cb5bcac70 · outbound

This paper cites Line: Out-of-distribution detection by leveraging important neurons.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Line: Out-of-distribution detection by leveraging important neurons

Reference 1

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Observation 3f0b6854-d2e0-41c5-a1e4-a750bef1e909 · outbound

This paper cites Building Normalizing Flows with Stochastic Interpolants.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Building Normalizing Flows with Stochastic Interpolants

Reference 2

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This paper cites On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning

Reference 3

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Learning imbalanced datasets with label- distribution-aware margin loss

Reference 4

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This paper cites Adversarial reciprocal points learning for open set recognition.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Adversarial reciprocal points learning for open set recognition

Reference 5

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This paper cites Atom: Robustifying out-of-distribution detection using outlier mining.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Atom: Robustifying out-of-distribution detection using outlier mining

Reference 6

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Observation e89a5f8d-25f6-4352-aa08-50026f6edee0 · outbound

This paper cites Describing textures in the wild.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Describing textures in the wild

Reference 7

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Extremely Simple Activation Shaping for Out-of-Distribution Detection

Reference 8

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

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Observation 386fbee7-0abe-4ec0-b313-a3c93f9461e5 · outbound

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention VOS: Learning What You Don't Know by Virtual Outlier Synthesis

Reference 10

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This paper cites How Does Unlabeled Data Provably Help Out-of-Distribution Detection?.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention How Does Unlabeled Data Provably Help Out-of-Distribution Detection?

Reference 11

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Observation c8478316-57e0-426d-bc1a-665a00355523 · outbound

This paper cites Is out-of-distribution detection learnable? Advances in Neural Information Processing Systems , 35: 37199–37213, 2022.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Is out-of-distribution detection learnable? Advances in Neural Information Processing Systems , 35: 37199–37213, 2022

Reference 12

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This paper cites Explaining and Harnessing Adversarial Examples.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Explaining and Harnessing Adversarial Examples

Reference 13

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This paper cites Deep residual learning for image recognition.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Deep residual learning for image recognition

Reference 14

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 15

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This paper cites Densely connected convolutional net- works.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Densely connected convolutional net- works

Reference 16

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention On the impor- tance of gradients for detecting distributional shifts in the wild

Reference 17

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Observation d1597540-2fd7-4728-ab4b-9bb41d93a0c6 · outbound

This paper cites an unresolved cited work.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Unresolved cited work

Reference 19

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Learning multiple layers of features from tiny images

Reference 20

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Observation 8b081a7a-5eb1-43f4-b26f-a144f3ca898f · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Imagenet classification with deep convolutional neural net- works

Reference 21

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This paper cites Simple and scalable predictive uncertainty estima- tion using deep ensembles.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Simple and scalable predictive uncertainty estima- tion using deep ensembles

Reference 22

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Observation bc0a1e38-25ec-42c7-b5e6-93f77a6d4686 · outbound

This paper cites Tiny imagenet visual recognition challenge.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Tiny imagenet visual recognition challenge

Reference 23

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention A simple unified framework for detecting out-of-distribution samples and adversarial attacks

Reference 24

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks

Reference 25

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This paper cites Clustering with bregman divergences: an asymptotic analysis.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Clustering with bregman divergences: an asymptotic analysis

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:35.679649Z

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Energy-based out-of-distribution detection

Reference 27

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Observation a05acaca-f0dc-43c3-88f5-4640a8d24f78 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 28

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Observation f7e858af-87b6-4f42-b2b8-d9488e9a826e · outbound

This paper cites Scanning trojaned models using out-of-distribution samples.Advances in Neural Information Processing Systems , 37:132545– 132582, 2025.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Scanning trojaned models using out-of-distribution samples.Advances in Neural Information Processing Systems , 37:132545– 132582, 2025

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:35.109538Z

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Observation 278822a0-ee55-4b7a-b496-c16a647c028e · outbound

This paper cites Importance estimation for neural net- work pruning.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Importance estimation for neural net- work pruning

Reference 30

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This paper cites Provable guarantees for un- derstanding out-of-distribution detection.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Provable guarantees for un- derstanding out-of-distribution detection

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:34.475426Z

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This paper cites Gradients as Features for Deep Representation Learning.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Gradients as Features for Deep Representation Learning

Reference 32

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Reading digits in natural images with unsupervised feature learning

Reference 33

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This paper cites ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection

Reference 34

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention SSD: A Unified Framework for Self-Supervised Outlier Detection

Reference 35

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Dice: Leveraging sparsification for out-of-distribution detection

Reference 36

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Observation acfa309f-1b73-46ad-8b77-200afe0d2d5e · outbound

This paper cites React: Out-of- distribution detection with rectified activations.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention React: Out-of- distribution detection with rectified activations

Reference 37

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Observation d5ac4a3e-7606-4fd8-b103-fea639ef9685 · outbound

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Out- of-distribution detection with deep nearest neighbors

Reference 38

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Observation 1595ee43-98b9-4617-8e4e-91364cc198f3 · outbound

This paper cites Pure: Prompt evolution with graph ode for out-of-distribution fluid dynamics mod- eling.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Pure: Prompt evolution with graph ode for out-of-distribution fluid dynamics mod- eling

Reference 39

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Observation ea201a73-14ef-42a5-8d44-e14f722ce9bb · outbound

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

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Sun database: Large-scale scene recognition from abbey to zoo

Reference 40

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This paper cites TurkerGaze: Crowdsourcing Saliency with Webcam based Eye Tracking.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention TurkerGaze: Crowdsourcing Saliency with Webcam based Eye Tracking

Reference 41

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Observation c1f0087f-b68e-4fe1-90c8-a09f5b40ff58 · outbound

This paper cites Generalized out-of-distribution detection: A survey.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Generalized out-of-distribution detection: A survey

Reference 42

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This paper cites LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 43

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This paper cites logit mass.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention logit mass

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:33.557868Z

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Observation 2128b56a-ece3-4757-9c14-f45ef8f63429 · outbound

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Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Unresolved cited work

Reference 45

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Observation e39ebeca-24b1-4739-b034-439ed561692f · outbound

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Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Unresolved cited work

Reference 46

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Observation e3269db5-62f4-4e79-a82c-9b8b463de6d3 · outbound

This paper cites Hence the total is Ω(Forward>L) + Ω(Backward >L) + O(d).

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Hence the total is Ω(Forward>L) + Ω(Backward >L) + O(d)

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:32.978904Z

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Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Unresolved cited work

Reference 48

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This paper cites parameter-like.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention parameter-like

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:32.592249Z

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Observation be4b6aa6-3b07-44e6-a2f3-6df4c351075a · outbound

This paper cites , λd) with λi > 0.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention , λd) with λi > 0

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:32.402685Z

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Observation e4b6f0cb-a7e1-4ecd-9716-2b01d02a496c · outbound

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Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Unresolved cited work

Reference 51

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Observation ad7731fa-806a-4be0-b025-ffd27473c80d · outbound

This paper cites Then the solution that minimizes L(F + ∆F) subject to the Fisher constraint is given bynulli- fying or scaling the top-k coordinates of F with largest |gi|/√λi.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Then the solution that minimizes L(F + ∆F) subject to the Fisher constraint is given bynulli- fying or scaling the top-k coordinates of F with largest |gi|/√λi

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:32.047148Z

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Observation e82ca67e-254b-463e-9632-bc4de482e790 · outbound

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Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Unresolved cited work

Reference 53

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Observation 06c24587-adbb-42f0-903a-4105c0333ce3 · outbound

This paper cites Fisher distance.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Fisher distance

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:31.789736Z

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Observation 25b04067-45da-41a5-871e-c84189eed6e0 · outbound

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Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Unresolved cited work

Reference 55

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a7ace620-8045-4c69-a469-9101b77cd778 · outbound

This paper cites Block2 + Penultimate.

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention Block2 + Penultimate

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:02:31.532411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers