Paper Citation Record · LEDGER

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models

As of 13 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2412.04925.

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

pith.paper-citation-record.v1
2412.04925 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

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measured 54 of 54 standing notices

One-hop event checks from named stored sources.

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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 2026-08-05T23:17:07.129873Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T23:17:14.107540Z

Reference resolution

53 of 53 outbound references displayed

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External citation measurements

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Outbound references

Observation 4c5b4d78-05bb-4f8d-8e85-d7712913ad91 · outbound

This paper cites Align your prompts: Test-time prompting with distribution align- ment for zero-shot generalization.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Align your prompts: Test-time prompting with distribution align- ment for zero-shot generalization

Reference 1

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Observation b2902c41-149b-49dd-98f0-bd1bbefbfa9e · outbound

This paper cites GPT-4 Technical Report.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models GPT-4 Technical Report

Reference 2

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Observation 80eeed1b-cf06-4f42-b6ea-ae009043a8e2 · outbound

This paper cites Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications

Reference 3

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Observation ca24263d-8675-43ff-82de-a98b1c9b3f3a · outbound

This paper cites A simple zero-shot prompt weight- ing technique to improve prompt ensembling in text-image models.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models A simple zero-shot prompt weight- ing technique to improve prompt ensembling in text-image models

Reference 4

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Observation da327fa6-341a-4f96-9a91-8ee4acdb729c · outbound

This paper cites The claude 3 model family: Opus, sonnet, haiku.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models The claude 3 model family: Opus, sonnet, haiku

Reference 5

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Observation 1a2a3f33-eca4-4358-bf0e-5ba964716db2 · outbound

This paper cites Food-101–mining discriminative components with random forests.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Food-101–mining discriminative components with random forests

Reference 6

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Observation e9fe905d-878b-4379-9e73-7fbd6f20a818 · outbound

This paper cites Describing textures in the wild.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Describing textures in the wild

Reference 7

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Observation 1e8b5e83-95f6-403e-ada3-d857740eaf90 · outbound

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

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Imagenet: A large-scale hierarchical image database

Reference 8

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Observation 5a4bb9ad-65fb-4ca6-8656-9476b39037a1 · outbound

This paper cites The pascal visual object classes (voc) challenge.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models The pascal visual object classes (voc) challenge

Reference 9

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Observation a53f1f22-d858-43fa-904d-7ca2e97a269e · outbound

This paper cites Learning gener- ative visual models from few training examples: An incre- mental bayesian approach tested on 101 object categories.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Learning gener- ative visual models from few training examples: An incre- mental bayesian approach tested on 101 object categories

Reference 10

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Observation c26a6f22-698e-4ed1-bb14-ac4c2237c743 · outbound

This paper cites Diverse data augmentation with diffusions for effective test-time prompt tuning.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Diverse data augmentation with diffusions for effective test-time prompt tuning

Reference 11

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Observation fff3beca-f4e4-4365-9308-895dff970a34 · outbound

This paper cites DALL-E for Detection: Language-driven Compositional Image Synthesis for Object Detection.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models DALL-E for Detection: Language-driven Compositional Image Synthesis for Object Detection

Reference 12

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This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 13

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Observation 1527240c-bd24-48e6-b9ad-ebf0fd7f3a00 · outbound

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

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models The many faces of robust- ness: A critical analysis of out-of-distribution generalization

Reference 14

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Observation 69fc188b-2479-4894-8279-7369303355be · outbound

This paper cites Natural adversarial examples.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Natural adversarial examples

Reference 15

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Observation bf38910c-e154-4ac9-856a-4783f4587cc1 · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 16

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Observation b438fe9b-4536-4a48-bac2-0e0a8b23ec8b · outbound

This paper cites Scaling up visual and vision-language representa- tion learning with noisy text supervision.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 17

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

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models 3d object representations for fine-grained categorization

Reference 18

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Observation e9adbf54-455a-49da-b1af-a28ab3479a6a · outbound

This paper cites Language-driven Semantic Segmentation.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Language-driven Semantic Segmentation

Reference 19

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Observation bb0cc363-aafb-48cb-aea9-e032e54de51e · outbound

This paper cites Swapprompt: Test-time prompt adaptation for vision- language models.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Swapprompt: Test-time prompt adaptation for vision- language models

Reference 20

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Observation 71129108-89ea-4964-88a8-6285381b467b · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Fine-Grained Visual Classification of Aircraft

Reference 21

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This paper cites A survey on bias and fairness in machine learning.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models A survey on bias and fairness in machine learning

Reference 22

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This paper cites Visual classification via description from large language models.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Visual classification via description from large language models

Reference 23

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Observation b4c50720-05cb-4b0c-a58d-0618a84e0baf · outbound

This paper cites Task Bias in Vision-Language Models.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Task Bias in Vision-Language Models

Reference 24

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This paper cites Meta-prompting for automating zero-shot visual recognition with llms.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Meta-prompting for automating zero-shot visual recognition with llms

Reference 25

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$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Computational homology

Reference 26

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

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Automated flower classification over a large number of classes

Reference 27

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This paper cites The neglected tails in vision-language models.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models The neglected tails in vision-language models

Reference 28

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$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Cats and dogs

Reference 29

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This paper cites What does a platypus look like? generating customized prompts for zero-shot image classification.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models What does a platypus look like? generating customized prompts for zero-shot image classification

Reference 30

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This paper cites Online zero-shot classification with clip.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Online zero-shot classification with clip

Reference 31

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Observation c82159ec-9bf6-46f0-93ba-5b415beda87a · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Learn- ing transferable visual models from natural language super- vision

Reference 32

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Observation 5754c06b-88ab-4360-8ba5-831f33b89612 · outbound

This paper cites Zero-shot text-to-image generation.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Zero-shot text-to-image generation

Reference 33

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This paper cites Do imagenet classifiers generalize to im- agenet? In International Conference on Machine Learning, pages 5389–5400.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Do imagenet classifiers generalize to im- agenet? In International Conference on Machine Learning, pages 5389–5400

Reference 34

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Observation d9dddf58-a335-4d98-bdfa-1f926a050dfb · outbound

This paper cites Waffling around for performance: Visual classification with random words and broad concepts.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Waffling around for performance: Visual classification with random words and broad concepts

Reference 35

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This paper cites LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs

Reference 36

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This paper cites Laion-5b: An open large-scale dataset for train- ing next generation image-text models.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Laion-5b: An open large-scale dataset for train- ing next generation image-text models

Reference 37

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This paper cites Test- time prompt tuning for zero-shot generalization in vision- language models.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Test- time prompt tuning for zero-shot generalization in vision- language models

Reference 38

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Observation 58486a4f-d598-4cc8-a9d1-414c7ac6003a · outbound

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

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 39

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This paper cites Just Shift It: Test-Time Prototype Shifting for Zero-Shot Generalization with Vision-Language Models.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Just Shift It: Test-Time Prototype Shifting for Zero-Shot Generalization with Vision-Language Models

Reference 40

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This paper cites Eigenfaces for recogni- tion.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Eigenfaces for recogni- tion

Reference 41

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This paper cites Learning robust global representations by penalizing local predictive power.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Learning robust global representations by penalizing local predictive power

Reference 42

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This paper cites Topological data analysis.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Topological data analysis

Reference 43

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

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Sun database: Large-scale scene recognition from abbey to zoo

Reference 44

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This paper cites Alip: Adaptive language-image pre-training with synthetic cap- tion.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Alip: Adaptive language-image pre-training with synthetic cap- tion

Reference 45

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Observation 6d771f7b-a3ed-4201-b26d-fb90cdbbcad4 · outbound

This paper cites On the test-time zero- shot generalization of vision-language models: Do we really need prompt learning? In CVPR, pages 23783–23793, 2024.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models On the test-time zero- shot generalization of vision-language models: Do we really need prompt learning? In CVPR, pages 23783–23793, 2024

Reference 46

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Observation a6d647a7-b077-4206-8abd-263db31f8e2d · outbound

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

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Lit: Zero-shot transfer with locked-image text tuning

Reference 47

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Observation 895b82f3-2a3b-41c5-a627-ea281d9769c3 · outbound

This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 48

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This paper cites Semantic under- standing of scenes through the ade20k dataset.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Semantic under- standing of scenes through the ade20k dataset

Reference 49

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Observation 296f95f7-5701-4a5f-bee5-2865cd8537b1 · outbound

This paper cites Extract free dense labels from clip.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Extract free dense labels from clip

Reference 50

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This paper cites Progressive point to set metric learning for semi-supervised few-shot classification.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Progressive point to set metric learning for semi-supervised few-shot classification

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:13:44.345730Z

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This paper cites Persistent homology: An introduction and a new text representation for natural language processing.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Persistent homology: An introduction and a new text representation for natural language processing

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:13:44.335999Z

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Observation a18c0b6b-75fc-4114-b700-d3886203c85a · outbound

This paper cites an unresolved cited work.

$S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models Unresolved cited work

Reference 53

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Pith citing papers

Observation f57f3c35-c529-4f4c-a1ad-ecf8c384a91e · inbound

Adapting Vision-Language Models Without Labels: A Comprehensive Survey cites this paper.

Adapting Vision-Language Models Without Labels: A Comprehensive Survey $S^3$: Synonymous Semantic Space for Improving Zero-Shot Generalization of Vision-Language Models

Reference 191

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