Paper Citation Record · LEDGER

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning

As of 17 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 1 inbound Pith citation observation for arXiv:2505.11758.

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

pith.paper-citation-record.v1
2505.11758 v2

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

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measured 64 of 64 standing notices

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T23:12:11.283075Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-06-29T23:14:01.245096Z

Reference resolution

63 of 63 outbound references displayed

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External citation measurements

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Outbound references

Observation 85011f59-eb41-44df-8916-427b2d9bae0c · outbound

This paper cites Ntua: Noise-tolerant unsupervised adapter for robust few-shot image classification.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Ntua: Noise-tolerant unsupervised adapter for robust few-shot image classification

Reference 1

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This paper cites Deltaaug: Cross-modal hard negative synthesis for vision–language mod- els.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Deltaaug: Cross-modal hard negative synthesis for vision–language mod- els

Reference 2

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This paper cites Dualadapter: Dual-path adapters for positive and negative prompting in vlms.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Dualadapter: Dual-path adapters for positive and negative prompting in vlms

Reference 3

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This paper cites Hard negative enhancement module for cross-modal contrastive training.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Hard negative enhancement module for cross-modal contrastive training

Reference 4

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Observation 54f15fd5-b0ca-4a99-a87e-b5f47eab172d · outbound

This paper cites Schane: Supervised contrastive hard negative learning for few-shot vi- sion–language adaptation.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Schane: Supervised contrastive hard negative learning for few-shot vi- sion–language adaptation

Reference 5

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Observation 994db96b-b9bd-4721-b7e2-14cf11fab542 · outbound

This paper cites Anonymous.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Anonymous

Reference 6

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Observation 13b92ff2-321e-4c4e-aaaa-e71a316a4913 · outbound

This paper cites Food-101 - mining discrimi- native components with random forests.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Food-101 - mining discrimi- native components with random forests

Reference 7

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Observation dc4e3172-4b3a-4568-979a-84b643a4213f · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning A simple framework for contrastive learning of visual representations

Reference 8

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This paper cites Meta- baseline: Exploring simple meta-learning for few-shot learning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Meta- baseline: Exploring simple meta-learning for few-shot learning

Reference 9

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Observation 29d2d1da-4b8c-4078-8eb6-1f4dcbf405a1 · outbound

This paper cites Describing textures in the wild.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Describing textures in the wild

Reference 10

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Observation ff042a1b-8ec5-4e88-a58b-922e63bfd9f1 · outbound

This paper cites Li, and Li Fei-Fei.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Li, and Li Fei-Fei

Reference 11

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Observation 56230f6c-99c7-4e77-b3c8-b4f000d9c1e5 · outbound

This paper cites Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object cate- gories.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object cate- gories

Reference 12

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Observation 407d02fa-291e-4e27-8a83-87ce5326fc0f · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Model-agnostic meta-learning for fast adaptation of deep networks

Reference 13

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Observation 9580eea2-4ff2-40f7-8a53-8de00831b322 · outbound

This paper cites CLIP-Adapter: Better Vision-Language Models with Feature Adapters.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning CLIP-Adapter: Better Vision-Language Models with Feature Adapters

Reference 14

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This paper cites Fmvp: Fine-grained meta-visual prompt- ing for remote sensing few-shot classification.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Fmvp: Fine-grained meta-visual prompt- ing for remote sensing few-shot classification

Reference 15

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Observation ba3d93d0-1dab-4ebb-8237-6ec06e4eff0a · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Momentum contrast for unsupervised visual representation learning

Reference 16

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Observation 4a9c6fc4-ea60-44ea-9b8c-20bc77c6b219 · outbound

This paper cites Dengel, and Damian Borth.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Dengel, and Damian Borth

Reference 17

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This paper cites Natural adversarial examples.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Natural adversarial examples

Reference 18

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

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning The many faces of robustness: A critical analysis of out-of-distribution generalization

Reference 19

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Observation 832a134c-4bac-400f-8011-8660840f1671 · outbound

This paper cites Learning from com- plementary labels.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Learning from com- plementary labels

Reference 20

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This paper cites Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig

Reference 21

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Observation 366836af-2aeb-4f59-a02d-35c80d6324db · outbound

This paper cites Boosting Meta-Training with Base Class Information for Few-Shot Learning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Boosting Meta-Training with Base Class Information for Few-Shot Learning

Reference 22

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This paper cites 3d object representations for fine-grained categorization.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning 3d object representations for fine-grained categorization

Reference 23

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This paper cites Cdn4: Cross-domain nearest-neighbor networks for few-shot learning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Cdn4: Cross-domain nearest-neighbor networks for few-shot learning

Reference 24

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This paper cites Boosting few-shot learning via attentive feature regularization.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Boosting few-shot learning via attentive feature regularization

Reference 25

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Observation 9fe3a892-8f7c-4ed1-b07d-c0133ed37ab3 · outbound

This paper cites GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph

Reference 26

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This paper cites Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm

Reference 27

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This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C

Reference 28

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This paper cites Transductive propagation net- work for few-shot learning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Transductive propagation net- work for few-shot learning

Reference 29

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This paper cites Fine-Grained Visual Classification of Aircraft.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Fine-Grained Visual Classification of Aircraft

Reference 30

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This paper cites Automated flower classification over a large number of classes.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Automated flower classification over a large number of classes

Reference 31

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This paper cites Parkhi, Andrea Vedaldi, Andrew Zisserman, and C.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Parkhi, Andrea Vedaldi, Andrew Zisserman, and C

Reference 32

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This paper cites Featwalk: Combining global and local con- sistency for few-shot learning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Featwalk: Combining global and local con- sistency for few-shot learning

Reference 33

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This paper cites Learning transferable visual models from natural lan- guage supervision.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Learning transferable visual models from natural lan- guage supervision

Reference 34

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This paper cites Do im- agenet classifiers generalize to imagenet? In International Conference on Machine Learning, 2019.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Do im- agenet classifiers generalize to imagenet? In International Conference on Machine Learning, 2019

Reference 35

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Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Girshick, and Ali Farhadi

Reference 36

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This paper cites Bernstein, Alexander C.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Bernstein, Alexander C

Reference 37

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This paper cites Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models

Reference 38

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This paper cites Unrolling em for transductive few-shot learn- ing.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Unrolling em for transductive few-shot learn- ing

Reference 39

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This paper cites Prototypical networks for few-shot learning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Prototypical networks for few-shot learning

Reference 40

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This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 41

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This paper cites DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations

Reference 42

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Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Argue: Attribute-guided prompt tuning for vision-language models

Reference 43

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This paper cites SuS-X: Training-Free Name-Only Transfer of Vision-Language Models.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning SuS-X: Training-Free Name-Only Transfer of Vision-Language Models

Reference 44

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This paper cites Matching net- works for one-shot learning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Matching net- works for one-shot learning

Reference 45

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This paper cites Xing, and Zachary Chase Lipton.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Xing, and Zachary Chase Lipton

Reference 46

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This paper cites Enhancing Fine-Grained Vision-Language Pretraining with Negative Augmented Samples.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Enhancing Fine-Grained Vision-Language Pretraining with Negative Augmented Samples

Reference 47

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Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Ehinger, Aude Oliva, and Antonio Torralba

Reference 48

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This paper cites Coca: Contrastive captioners are image-text foundation models.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Coca: Contrastive captioners are image-text foundation models

Reference 49

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Observation 66a02fde-974c-4f5f-ba61-2a1dc291416f · outbound

This paper cites Task residual for tun- ing vision-language models.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Task residual for tun- ing vision-language models

Reference 50

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This paper cites Learning with Biased Complementary Labels.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Learning with Biased Complementary Labels

Reference 51

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This paper cites Lit: Zero-shot transfer with locked-image text tuning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Lit: Zero-shot transfer with locked-image text tuning

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:55.127998Z

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Observation cbc77704-e5db-4881-a63e-17f9f2ff047c · outbound

This paper cites Enhancing Vision-Language Few-Shot Adaptation with Negative Learning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Enhancing Vision-Language Few-Shot Adaptation with Negative Learning

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:53:54.900031Z

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Observation a4867fa1-b5ff-4851-9e01-d97e04892fd5 · outbound

This paper cites Sycara, and Yaqi Xie.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Sycara, and Yaqi Xie

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:55.116183Z

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Observation 4e4ed0f3-8421-4176-a863-79869ff634a0 · outbound

This paper cites Deepemd: Few-shot image classification with differentiable earth mover’s distance and structured classifiers.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Deepemd: Few-shot image classification with differentiable earth mover’s distance and structured classifiers

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:55.103490Z

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Observation 89b62175-1d3f-4397-9100-44eac1f94271 · outbound

This paper cites Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:53:54.882610Z

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Observation fb00ab91-6db2-49f9-9e50-ea1037bf4ca2 · outbound

This paper cites Concept-Guided Prompt Learning for Generalization in Vision-Language Models.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Concept-Guided Prompt Learning for Generalization in Vision-Language Models

Reference 57

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Observation 327dc7a5-7f04-42e9-a996-90ca539e8af6 · outbound

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

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Learning to prompt for vision-language models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:55.091184Z

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Observation bd72210b-0140-4640-a371-e481a53c2e84 · outbound

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

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Conditional prompt learning for vision-language models

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:55.077752Z

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Observation 37eabada-3328-4eb4-9e99-760169de4088 · outbound

This paper cites Prompt- aligned gradient for prompt tuning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Prompt- aligned gradient for prompt tuning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:55.064741Z

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Observation 5171b4ea-34e3-4e63-aeca-ba9064bad681 · outbound

This paper cites Prompt-aligned gradient for prompt tuning.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Prompt-aligned gradient for prompt tuning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:55.051679Z

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Observation 03fe5964-0c23-4ae8-9b85-9623e08b47ed · outbound

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Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Unresolved cited work

Reference 2010

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:53:55.162552Z

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Observation dde2ef45-67bc-4af3-a0c5-049d9cb0fa3d · outbound

This paper cites an unresolved cited work.

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning Unresolved cited work

Reference 2014

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:53:55.537703Z

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Pith citing papers

Observation 92bccb65-bcb3-4d6a-91d8-4503f20c1e87 · inbound

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning cites this paper.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-06-29T23:14:01.246428Z

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