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Paper Citation Record · LEDGER

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey

As of 18 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2505.02448.

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

pith.paper-citation-record.v1
2505.02448 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:54:39.613296Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T10:14:07.784331Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

  • verified exact3
  • verified fuzzy29
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8cf4cf30-f162-4296-8930-53b95762ee4e · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Id- like prompt learning for few-shot out-of-distribution de- tection

Reference 1

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Source-reported events for the cited work

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Observation 6a1ab2bc-3b3e-4fd1-969e-462ca4e4a26e · outbound

This paper cites Tagfog: Textual anchor guidance and fake outlier generation for visual out-of- distribution detection.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Tagfog: Textual anchor guidance and fake outlier generation for visual out-of- distribution detection

Reference 4

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Source-reported events for the cited work

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Observation 2dbe4438-fd82-42f4-b443-3d390c987123 · outbound

This paper cites To- wards accurate open-set recognition via background-class regularization.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey To- wards accurate open-set recognition via background-class regularization

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 74162ff4-4bfd-4033-abc6-dbb29d679e8e · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Exploring the limits of out-of-distribution detection

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b16d293e-1d73-44aa-aed4-1dd21bee2f06 · outbound

This paper cites Out-of-distribution Detection in Medical Image Analysis: A survey.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Out-of-distribution Detection in Medical Image Analysis: A survey

Reference 11

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 389d4463-7489-4c5a-835b-adf8ec2794cf · outbound

This paper cites Mos: To- wards scaling out-of-distribution detection for large se- mantic space.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Mos: To- wards scaling out-of-distribution detection for large se- mantic space

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5cf80529-62f0-4111-8891-89b4835e27eb · outbound

This paper cites A survey of safety and trust- worthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey A survey of safety and trust- worthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4aee85b3-4f2d-465d-91e3-0f58d04dff8b · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Neg- ative label guided ood detection with pretrained vision- language models

Reference 14

Resolution
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Source-reported events for the cited work

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Observation a9850cda-3445-4297-999d-0476188179da · outbound

This paper cites Gallop: Learning global and local prompts for vision-language models.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Gallop: Learning global and local prompts for vision-language models

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 954adde5-a40c-4b2a-912e-36b3d7f7669e · outbound

This paper cites Concept matching with agent for out-of-distribution detection.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Concept matching with agent for out-of-distribution detection

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a069b134-2092-40a6-881e-f0b362d3f4c5 · outbound

This paper cites SeTAR: Out-of-Distribution Detection with Selective Low-Rank Approximation.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey SeTAR: Out-of-Distribution Detection with Selective Low-Rank Approximation

Reference 17

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 91ab6448-97fd-4484-9bf9-8c319f3f9c75 · outbound

This paper cites Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation ca3d0b68-bc7e-4829-ba27-30d36da28187 · outbound

This paper cites Tag: Text prompt augmentation for zero-shot out-of- distribution detection.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Tag: Text prompt augmentation for zero-shot out-of- distribution detection

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9a1eaa87-fc73-44db-b628-ad4639b3fc58 · outbound

This paper cites Energy-based out-of-distribution detec- tion.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Energy-based out-of-distribution detec- tion

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:54:39.918899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T00:54:39.534222Z digest=sha256:ac22474da9df2020e74356fe5e956a37486c749edde2349849ee155b5e11c751

Observation 2b6cd8b2-06b7-481f-ab1b-75800e35a13b · outbound

This paper cites Category-extensible out-of-distribution detection via hierarchical context descriptions.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Category-extensible out-of-distribution detection via hierarchical context descriptions

Reference 21

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T00:54:39.538451Z digest=sha256:55fd88af066127d52d8e0b205be941ba0696eb8cbcaf781c1a1beb1c6535b5b1

Observation 4c492528-989b-44a4-be0e-364da5b72b14 · outbound

This paper cites Novelty detection in learning systems.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Novelty detection in learning systems

Reference 22

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 48e2dd20-e4cb-4622-a601-c59e2aa61a8d · outbound

This paper cites GL-MCM: Global and Local Maximum Concept Matching for Zero-Shot Out-of-Distribution Detection.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey GL-MCM: Global and Local Maximum Concept Matching for Zero-Shot Out-of-Distribution Detection

Reference 23

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6d1e1fdc-3641-4f4a-8151-7502b69beb0c · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Out-of- distribution detection with negative prompts

Reference 25

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation dcf8db89-25b8-41b8-a23d-c86b6a82e97a · outbound

This paper cites On the powerful- ness of textual outlier exposure for visual ood detec- tion.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey On the powerful- ness of textual outlier exposure for visual ood detec- tion

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0127aab2-44d1-4ecc-9644-706776e57c00 · outbound

This paper cites Learning transferable visual models from nat- ural language supervision.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Learning transferable visual models from nat- ural language supervision

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 70d71f98-8632-4230-beab-e3a63458bef1 · outbound

This paper cites Likelihood ratios for out-of- distribution detection.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Likelihood ratios for out-of- distribution detection

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7849960c-4402-49fd-9acd-461556d80a14 · outbound

This paper cites Lifelong learning systems: overview and extension of different ty- pologies.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Lifelong learning systems: overview and extension of different ty- pologies

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:54:39.828623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a82f31a7-5c8e-454c-a9a3-ea641a255dc2 · outbound

This paper cites CLIP-driven Outliers Synthesis for few-shot OOD detection.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey CLIP-driven Outliers Synthesis for few-shot OOD detection

Reference 33

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3f9dc388-f97b-44e9-8d56-d58f558bf586 · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Clipn for zero-shot ood detection: Teaching clip to say no

Reference 34

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 17fabbf3-f33c-4611-83d4-7e029feb9407 · outbound

This paper cites Likelihood regret: An out-of-distribution detection score for variational auto-encoder.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Likelihood regret: An out-of-distribution detection score for variational auto-encoder

Reference 35

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation fe9eba89-0cbd-40c8-9088-5ffce6ec29f9 · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Openood: Benchmarking generalized out-of-distribution detection

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation abfda242-fa85-4ef1-bd49-cccaabad4bd0 · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Generalized out-of-distribution detec- tion: A survey

Reference 37

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 41148527-10c7-4e6f-b7ef-0645ace04c35 · outbound

This paper cites AdaNeg: Adaptive Negative Proxy Guided OOD Detection with Vision-Language Models.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey AdaNeg: Adaptive Negative Proxy Guided OOD Detection with Vision-Language Models

Reference 38

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0a494b42-1096-4df6-b249-e36d1c9c92bd · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Learning to prompt for vision-language models

Reference 39

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7139cd8c-57ce-493f-a889-c7e7f2308477 · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Out-of-distribution detection with deep near- est neighbors

Reference 2012

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:54:39.804231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4205a9f0-406c-4618-8c0a-2b34ad80aa7b · outbound

This paper cites Toward open set recognition.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Toward open set recognition

Reference 2013

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 58fe1517-7198-4aef-9bd0-2db54c5ef09d · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 2015

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2b164dd9-6f9c-4116-83e1-2c1c670c2dcf · outbound

This paper cites Pretrained transformers improve out-of- distribution robustness.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Pretrained transformers improve out-of- distribution robustness

Reference 2016

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:54:40.016242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 1ad22839-08de-4914-9405-fef13a02c47d · outbound

This paper cites Imagenet large scale visual recogni- tion challenge.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Imagenet large scale visual recogni- tion challenge

Reference 2019

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Envisioning outlier exposure by large language models for out-of-distribution detection

Reference 2020

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Observation f23136ee-31df-446e-a575-3d3b9aba75e2 · outbound

This paper cites Delving deep into rectifiers: Surpass- ing human-level performance on imagenet classification.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Delving deep into rectifiers: Surpass- ing human-level performance on imagenet classification

Reference 2021

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Observation b559c9d4-7420-4bd0-a78b-ada7995e7346 · outbound

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

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Zero-shot out-of-distribution detection based on the pre-trained model clip

Reference 2022

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Observation 6d258ac2-2582-49ee-b722-d653728793dc · outbound

This paper cites Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey

Reference 2023

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Observation ba6d2e5b-3f4c-4aa2-8fa7-8a1db83e5f22 · outbound

This paper cites Certifiably adversarially robust detection of out-of-distribution data.

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey Certifiably adversarially robust detection of out-of-distribution data

Reference 2024

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Pith citing papers

Observation e7fa1ec4-c1b4-45dc-a1e2-6c75f4e7f925 · inbound

$\Delta \mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization cites this paper.

$\Delta \mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey

Reference 12

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