Pith. sign in

Paper Citation Record · LEDGER

Non-Linear Outlier Synthesis for Out-of-Distribution Detection

As of 23 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2411.13619.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.13619 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:51:53.294549Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T00:29:11.066026Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T16:29:57.959480Z

Reference resolution

58 of 58 outbound references displayed

  • verified exact0
  • verified fuzzy42
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f193d2cc-6ec6-4dba-804b-dbb1b34233d9 · outbound

This paper cites Latent space autoregression for novelty detec- tion.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Latent space autoregression for novelty detec- tion

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.986995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.067511Z digest=sha256:4d8227238a7777eb49edb1b915d00a004ccdff2360024f1d093cea0dcbd37f1e

Observation d19fd995-fcaa-4e02-9895-9f6a342d3061 · outbound

This paper cites Detecting semantic anomalies.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Detecting semantic anomalies

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.973868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.072889Z digest=sha256:82c0f997b1d00c914a5140710212f61005ebc0df28b650693b058d916d837fdf

Observation 1b1c90e9-f288-431b-973b-48aae1c39c18 · outbound

This paper cites Gradorth: A simple yet efficient out- of-distribution detection with orthogonal projection of gra- dients.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Gradorth: A simple yet efficient out- of-distribution detection with orthogonal projection of gra- dients

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.961376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.077406Z digest=sha256:23116baa8a498a60954a06016c864433149db78f60aa41e62c71efa0f4cee96f

Observation ef72ea1f-68c6-474e-86d4-0eda081cd378 · outbound

This paper cites Fodfom: Fake outlier data by founda- tion models creates stronger visual out-of-distribution detec- tor.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Fodfom: Fake outlier data by founda- tion models creates stronger visual out-of-distribution detec- tor

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.948712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.081963Z digest=sha256:5f2e00568a716a3c11cdb7f260d3d36779aa457961f5ce6b426579d3f155d4f8

Observation 7734a19f-aedc-46ac-92f4-a1904a22fdd7 · outbound

This paper cites Describing textures in the wild.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Describing textures in the wild

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.086442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.086442Z digest=sha256:b06dcb976be61c0514564c7f47a7d4dd2af0e7cf31213c2e46cd16d67d0ad699

Observation 2598b77d-b597-4000-ba54-9b7ec5ba0869 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Imagenet: A large-scale hierarchical image database

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.927887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.090819Z digest=sha256:4edda8327fe098e37bc7683725f10abbc17f5c6757d021b899cc831a43f944ec

Observation 34df565c-5ffd-492a-819f-7525552337b3 · outbound

This paper cites Learning Confidence for Out-of-Distribution Detection in Neural Networks.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Learning Confidence for Out-of-Distribution Detection in Neural Networks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.095158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.095158Z digest=sha256:392009300433ec67bca812b01fd11c9845dcaf4aa5c84604944f97150f2d3493

Observation 16d5e4d8-979b-4ac7-add4-1df90afb212e · outbound

This paper cites Diffusion models beat gans on image synthesis.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Diffusion models beat gans on image synthesis

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.099767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.099767Z digest=sha256:72117805029850c8d9fc1ad9994221ecf99e8ff200f7463d4c1c427cd7fac762

Observation 96c99662-87f3-422c-8959-a4e29f5f743e · outbound

This paper cites Data invariants to understand unsupervised out-of- distribution detection.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Data invariants to understand unsupervised out-of- distribution detection

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.906913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.103913Z digest=sha256:8894526afc41dd0d779b6f2721550ea1981e47093d8684b57f69cbf59c379b7c

Observation cff3cea3-2065-4f35-9788-2f928ea89ece · outbound

This paper cites Learning non-linear invariants for unsupervised out- of-distribution detection.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Learning non-linear invariants for unsupervised out- of-distribution detection

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.895210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.107638Z digest=sha256:9ecaaa1013276cbab5a1f6170e0cc9ffdbacd0f4c1ade6dedc2aff8609754987

Observation 4798d850-a736-4e03-80be-8a687d532b0c · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection V os: Learning what you don’t know by virtual outlier synthesis

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.883040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.111050Z digest=sha256:db52d3ebd14c28f642217a6d2cffc8a785d9a639908ebd2d32a95dae992d3425

Observation a50fd070-da19-4667-9097-2bb243cc5866 · outbound

This paper cites Dream the impossible: Outlier imagination with diffusion models.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Dream the impossible: Outlier imagination with diffusion models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.114729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.114729Z digest=sha256:40fa5792021c09ef28d101ef8b6d5e528addc0e62b96ed77e6e113991c9917b7

Observation 7e04ec82-6da4-4dda-9358-dc4f5b5331d5 · outbound

This paper cites Ex- ploring the limits of out-of-distribution detection.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Ex- ploring the limits of out-of-distribution detection

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.864091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.118729Z digest=sha256:0be67e9310cd880b1c7177554947eda45bb68a631f898a75def987f97dafb95d

Observation 40cb9d44-8be4-46ae-ba12-a045c0216a9f · outbound

This paper cites Transfusion–a transparency-based diffusion model for anomaly detection.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Transfusion–a transparency-based diffusion model for anomaly detection

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.851990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.122593Z digest=sha256:40c73372a20efe76369bb74e1b65b1b9a90e81cd85b3c91887de2f87b6f1d092

Observation 39e920dc-ca8f-4e65-92f9-2c8ba5a7d096 · outbound

This paper cites An image is worth one word: Personalizing text-to-image gen- eration using textual inversion.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection An image is worth one word: Personalizing text-to-image gen- eration using textual inversion

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.840500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.126769Z digest=sha256:d8714addb62ce06dce906f0485d7d09dcac568c16b17bd267493bf5978b4b851

Observation f58eea9e-369c-4294-9230-a7c5d1e44ece · outbound

This paper cites Hierarchical vaes know what they don’t know.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Hierarchical vaes know what they don’t know

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.826839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.130502Z digest=sha256:0ff77733c6db1f48bddff5f44bbbac7a98bd02a71600cbac56331835783147c4

Observation f5697bec-a8fa-48cd-be0d-e39b1ca5d49e · outbound

This paper cites A baseline for detect- ing misclassified and out-of-distribution examples in neural networks.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection A baseline for detect- ing misclassified and out-of-distribution examples in neural networks

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.812606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.134696Z digest=sha256:08e2205c2d22aee8b13620550d49c0249f054be5357724f5890b0baa01987931

Observation e9d4b0fa-cd45-48ef-986b-9fe5eb3b8388 · outbound

This paper cites Deep anomaly detection with outlier exposure.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Deep anomaly detection with outlier exposure

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.798439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.138465Z digest=sha256:fe1345d11b9bf772ad6bf4d5cae7c53938b6d64df39f2ba9718d5ff11cf429f9

Observation f91d29a5-322b-4bc9-af40-fdecf8144588 · outbound

This paper cites Using self-supervised learning can improve model robustness and uncertainty.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Using self-supervised learning can improve model robustness and uncertainty

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.784643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.142066Z digest=sha256:cc935a4585427eb278fa8f9f64a1cdbb88142208a2a03e63fab2f484fd7bded8

Observation a1fff900-746b-4981-b382-b4af5d3673ea · outbound

This paper cites Scal- ing out-of-distribution detection for real-world settings.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Scal- ing out-of-distribution detection for real-world settings

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.770473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.145512Z digest=sha256:6601a17193f1da1e08a75782abd3927275ee4f7021682ece6f09c4f9cbad8298

Observation 6d269d32-2283-452e-b7ca-224e4495befa · outbound

This paper cites Generalized odin: Detecting out-of-distribution image with- out learning from out-of-distribution data.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Generalized odin: Detecting out-of-distribution image with- out learning from out-of-distribution data

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.756983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.149250Z digest=sha256:e566ceab3cd765aba1d5ff67fbc6540ab40afb8d3f6c008092ef61d943cdb338

Observation 2c2f4cf1-f07e-4f93-919a-5d05b82db196 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Mos: Towards scaling out-of- distribution detection for large semantic space

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.744196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.152884Z digest=sha256:1bf7d45ecda8ce1efc108ec1f0aa85c7d12bfb20a8d6a98679031a96fdf05998

Observation a7529142-ae31-46cf-b0be-5b12d0796634 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection On the impor- tance of gradients for detecting distributional shifts in the wild

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.156441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.156441Z digest=sha256:5511a78ac50926d781dc6870f421265b27273ce397586c163f4f3866330931bf

Observation c8f45deb-2fb1-41df-b61e-9149e3023496 · outbound

This paper cites Why is the Mahalanobis Distance Effective for Anomaly Detection?.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Why is the Mahalanobis Distance Effective for Anomaly Detection?

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.159843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.159843Z digest=sha256:c21dd939f77c32264c08bc5d7f93d6f641c3937341f55c6740436063f46fc9c6

Observation ebaeb67e-c9fc-42d4-9b63-8a9a57caac8a · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Learning multiple layers of features from tiny images

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.163932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.163932Z digest=sha256:7b845b0a00b4c55729acab7e5ae78a6d580d8d8225f387020143fbe4c1bb17f6

Observation bc3bfbf1-4dc2-4833-aa7c-c6cf9d690231 · outbound

This paper cites Training confidence-calibrated classifiers for detecting out- of-distribution samples.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Training confidence-calibrated classifiers for detecting out- of-distribution samples

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.713838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.167611Z digest=sha256:2e0c4466e1641dcea5aa9ac8d45658a4f37154f10c4175c042554935816f9f4c

Observation 9ff38574-c495-46f2-96ec-e70dbaa8c2b5 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection A simple unified framework for detecting out-of-distribution samples and adversarial attacks

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.700172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.171165Z digest=sha256:701e17d535b7a761178a3bec891ca5fd7ce05d46c5a0ec049fb82d8b1afe9f9d

Observation ac5c38ac-06df-4e74-888e-22f733c80843 · outbound

This paper cites Cutpaste: Self-supervised learning for anomaly de- tection and localization.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Cutpaste: Self-supervised learning for anomaly de- tection and localization

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.174625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.174625Z digest=sha256:3965c16970734b44f5237b64abf953d57add2821deae9c24aca2f2959316f591

Observation be4bbe12-7401-4af1-81bf-57bc98ae9d1a · outbound

This paper cites Enhanc- ing the reliability of out-of-distribution image detection in 9 neural networks.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Enhanc- ing the reliability of out-of-distribution image detection in 9 neural networks

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.677409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.178671Z digest=sha256:bdd6eef8b597c4b10fece9b6d10dbb7e2d776e5fb5e1dc5df455288b9603c8f1

Observation f5fab3d8-f880-4006-957d-678a16491a5c · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Energy-based out-of-distribution detection

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.665040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.182507Z digest=sha256:1078f4ce2d2da80698c97248e43c87972064b6442fc10a2306adc38aab90efc5

Observation 6f7db462-42b2-488b-b6ad-25eee4ee59a3 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Gen: Pushing the limits of softmax-based out-of-distribution de- tection

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.653271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.189832Z digest=sha256:4b7442bcb3430d30c74958a6e0cec1f25275db92b2755a86af0f79966e6d92b6

Observation b29080b0-97ed-4486-88f5-0dfee7364e26 · outbound

This paper cites Do Deep Generative Models Know What They Don't Know?.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Do Deep Generative Models Know What They Don't Know?

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.194096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.194096Z digest=sha256:25a9a01a13ffa749f101bb98fe9edb261292f1d81421d6a42a9dbb5964707f43

Observation 2fbd41c6-632d-45d7-90c1-bcf1a415889e · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Reading digits in natural images with unsupervised feature learning

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.641847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.198273Z digest=sha256:def82b5872f6e1529bc6c0045295b7aedc9eb9812ca2e4dd0585f6d17a4f0385

Observation 27f529f8-3ae1-4b1f-9125-9a0260a0ac75 · outbound

This paper cites Outlier exposure with confidence control for out-of-distribution detection.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Outlier exposure with confidence control for out-of-distribution detection

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.628835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.201903Z digest=sha256:a799164f174bc22f571148978169dcee556ab015926abda4521f3b8e93b39a07

Observation 61d87244-6f94-4464-9585-e4a6c33b67ee · outbound

This paper cites Mean-shifted contrastive loss for anomaly detection.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Mean-shifted contrastive loss for anomaly detection

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.616193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.205524Z digest=sha256:ce0b00bfb60d4694b00000c9baa52d2560b9a96b87955ca6a691be68d150d150

Observation 686c1674-e1f3-49ee-af80-de667932b9bc · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.209376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.209376Z digest=sha256:318a44841bfea68a363a27743550cc392dae8089204c206f0835127b9ac3d722

Observation 95e79ff8-42b7-43f8-878a-53fd465615e1 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models, 2021.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection High-resolution image syn- thesis with latent diffusion models, 2021

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.213664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.213664Z digest=sha256:1b25496d6376f94294db4758159dce4914c00826e2bba6e6f98b531f716d2d8a

Observation f50f3867-584b-4169-8871-fa6bd1855205 · outbound

This paper cites Detecting out-of-distribution examples with gram matrices.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Detecting out-of-distribution examples with gram matrices

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.594679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.217403Z digest=sha256:8a6fdb3a12917c5113dc6e85d5de7c7cf7e113695d34d02207ae87eb63dea425

Observation edf33a1b-5dfb-4fdc-bae9-08abbb7cb7b1 · outbound

This paper cites Understanding anomaly detection with deep invert- ible networks through hierarchies of distributions and fea- tures.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Understanding anomaly detection with deep invert- ible networks through hierarchies of distributions and fea- tures

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.581768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.221105Z digest=sha256:8703f43d3540f982a1093e490a97945c5c62d31354640ba16d03cc1a79cc3f5c

Observation bbeed7ed-9ebf-4efe-a38f-5194c7cd3911 · outbound

This paper cites Natural synthetic anomalies for self-supervised anomaly detection and localization.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Natural synthetic anomalies for self-supervised anomaly detection and localization

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.224971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.224971Z digest=sha256:4483bef02e0f3e65cc07f3fac0aa813f58bf553fc0dd2f9e6872748761dfdcbf

Observation 65b29c36-2589-4c32-bbb8-d79313db092f · outbound

This paper cites Ssd: A unified framework for self-supervised outlier detection.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Ssd: A unified framework for self-supervised outlier detection

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.562800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.229128Z digest=sha256:9fcd0af4618a5a2a402d7c2f58725bea0353c3c69efe535bc90ca7109c64921d

Observation e5ac22cc-f950-408f-b71e-be96b7182e55 · outbound

This paper cites Input complexity and out-of- distribution detection with likelihood-based generative mod- els.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Input complexity and out-of- distribution detection with likelihood-based generative mod- els

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.551838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.232917Z digest=sha256:8a7039f94d76057bb106e94e4b15ce27650785e18a5bbcb53e4dfc9cd747f043

Observation a6b772be-6080-4be5-ad4e-c5570fc5f448 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Dice: Leveraging sparsification for out-of-distribution detection

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.540871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.236831Z digest=sha256:d687221823e8e3f77a0663546e96f5265a645083d67113fb78736437ebabb5cc

Observation a3637d57-980e-4356-9c87-80d1f49ae7e7 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection React: Out-of- distribution detection with rectified activations

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.529832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.240567Z digest=sha256:1527125857a12d121cf138f74c39be674f3d88f19cde18cdd7565aa115e0f8d9

Observation 1106850d-8241-4088-9c6d-6f6f82799133 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Out-of- distribution detection with deep nearest neighbors

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.518309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.244334Z digest=sha256:46385720c55cfa0e11501a7afc87bfc8954224a6b40bfe9ef10f4fd16323578e

Observation 35be1739-47f9-4bc2-ae91-193a7eae9a14 · outbound

This paper cites Detecting outliers with poisson image interpolation.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Detecting outliers with poisson image interpolation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.505725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.248095Z digest=sha256:e44814da0189f54308e6b26b924139e7f61fdc9f34ac6dd1d876ff6d6710e453

Observation 7e770fcb-dc72-404c-a439-7e073aa63e68 · outbound

This paper cites Non- parametric outlier synthesis.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Non- parametric outlier synthesis

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.494415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.251854Z digest=sha256:27b6469019a911512cf9598a51f9357128b5a5f50cc338f2a5e9377eb1113bdd

Observation 9b858d6d-a174-45cc-884e-af5980907ce4 · outbound

This paper cites Self-guided generation of minority samples using diffusion models.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Self-guided generation of minority samples using diffusion models

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.481807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.255512Z digest=sha256:58266271cfd32bee0cea00d894f28d379330849e5edf016de3ac8fd4695f863e

Observation 6c42d902-0f90-47ce-b60a-0cb24fa46cc4 · outbound

This paper cites The inaturalist species classification and de- tection dataset.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection The inaturalist species classification and de- tection dataset

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.470283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.258960Z digest=sha256:cd2da5af4c1c6c2935bbc090f206f2c5e14fc3fde926e7af754e3fc3c19b9f14

Observation 76bcc2f7-57f8-4e05-81e4-f3f399c6abe5 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Vim: Out-of-distribution with virtual-logit matching

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.458476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.262741Z digest=sha256:0b9771e10d65b17156b480f96d056e54c114bbaf5c2367f073d4afff9ea0e977

Observation eea58561-310d-4ea6-ad6a-e3332f3139f1 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Contrastive Training for Improved Out-of-Distribution Detection

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.266743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.266743Z digest=sha256:a6c35ef5f1344b15f69de67faa06f7b372c40db8328f5616c11b5881fa8c1ae1

Observation c7ae899d-54f6-49c3-8fac-7bd59a39ab34 · outbound

This paper cites Datasetdm: Synthesizing data with perception annota- tions using diffusion models.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Datasetdm: Synthesizing data with perception annota- tions using diffusion models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.271335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.271335Z digest=sha256:d9aa979f20d9c2ecf39a5e65239ab212d94cc41f410aa0f2e4b8c67f723ded98

Observation dd1fcbdb-e0ef-4210-a0e0-f463444b2f12 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Sun database: Large-scale scene recognition from abbey to zoo

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.439940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.275263Z digest=sha256:c3fc98515ad96b8f6ff798a889d1fe1969b23644e20e823295042f6914d42300

Observation d260d4e2-9e61-4753-8311-d774a2a7635d · outbound

This paper cites Do we really need to learn representations from in-domain data for outlier de- tection? ICML 2021 Workshop on Uncertainty & Robustness in Deep Learning, 2021.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Do we really need to learn representations from in-domain data for outlier de- tection? ICML 2021 Workshop on Uncertainty & Robustness in Deep Learning, 2021

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.428633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.278918Z digest=sha256:2fb21874bf658721a6386d0bb3031d4739070cb8d412b025d1a090d00a494061

Observation ec38aa4e-459e-4f5b-be80-f0df32f4cdb9 · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection TurkerGaze: Crowdsourcing Saliency with Webcam based Eye Tracking

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.282763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.282763Z digest=sha256:4ed1a39d0083a024937ed7e817aa89f87a1fd660ac44fba96549f55cc1ae3b93

Observation 9af2e442-8b0b-4114-8ff9-861e02e2597c · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-12T16:51:53.286869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:51:53.286869Z digest=sha256:65484b0e37d4a201b828a437df227e92235ebe2f6edb323297732345fc66dd7e

Observation e52dedbb-f14d-456f-8fae-b819da6f3d4e · outbound

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

Non-Linear Outlier Synthesis for Out-of-Distribution Detection Places: A 10 million image database for scene recognition

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.417436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.290879Z digest=sha256:afc8c13d73db80954287c13beecdeff03e137ff5c64b2dea3a9cf681662dac7e

Observation d7443d71-ef14-427d-be93-a181a0a22493 · outbound

This paper cites The ID datasets are CIFAR-100 and ImageNet-100, which we briefly describe below: CIFAR-100 [25] contains 50’000 training images and 10’000 testing images belonging to 100 classes.

Non-Linear Outlier Synthesis for Out-of-Distribution Detection The ID datasets are CIFAR-100 and ImageNet-100, which we briefly describe below: CIFAR-100 [25] contains 50’000 training images and 10’000 testing images belonging to 100 classes

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:51:53.405525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T16:51:53.294549Z digest=sha256:f317b860ccb8ce4dec9227dcf1968a9cb2c2208cd32e142607a3010d82b4b966

Pith citing papers

Observation acf58db5-079a-4b62-9cda-9ba352e3fadb · inbound

Modality-Aware Out-of-Distribution Detection for Multi-Modal Action Recognition cites this paper.

Modality-Aware Out-of-Distribution Detection for Multi-Modal Action Recognition Non-Linear Outlier Synthesis for Out-of-Distribution Detection

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:29:57.961192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-26T00:29:11.066026Z digest=sha256:370726c917438e2d22e0347d6090efa507f687e4cf72af6aec369fa002768976