Paper Citation Record · LEDGER

Provably Improving Generalization of Few-Shot Models with Synthetic Data

As of 9 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2505.24190.

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

pith.paper-citation-record.v1
2505.24190 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:38:44.710965Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

49 of 49 outbound references displayed

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verified fuzzy37
unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ef47d2e-7bb7-4d9e-b961-a733c5b804a6 · outbound

This paper cites write newline.

Provably Improving Generalization of Few-Shot Models with Synthetic Data write newline

Reference 1

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Source-reported events for the cited work

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Observation 0d92e3f9-dd1f-4b63-9772-3f444c798074 · outbound

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

Provably Improving Generalization of Few-Shot Models with Synthetic Data Food-101 -- mining discriminative components with random forests

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:55.957819Z

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Observation fba6b71f-ffa1-49a3-bc7d-6828bd56498a · outbound

This paper cites Describing textures in the wild.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Describing textures in the wild

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:55.687904Z

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Observation 7e0e4ab5-53ab-4b90-92dc-1bd5928f22d2 · outbound

This paper cites Diversified in-domain synthesis with efficient fine-tuning for few-shot classification.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Diversified in-domain synthesis with efficient fine-tuning for few-shot classification

Reference 4

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Source-reported events for the cited work

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Observation 0619013c-5500-47b8-9466-766befc06566 · outbound

This paper cites The Faiss library.

Provably Improving Generalization of Few-Shot Models with Synthetic Data The Faiss library

Reference 5

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Observation 0d82d332-af70-4e88-a2ba-11b9d93e4cb2 · outbound

This paper cites and Liu, Y.

Provably Improving Generalization of Few-Shot Models with Synthetic Data and Liu, Y

Reference 6

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Observation d4872a4b-57e0-4544-adbc-5dd0e1543016 · outbound

This paper cites IS SYNTHETIC DATA FROM GENERATIVE MODELS READY FOR IMAGE RECOGNITION ? In The Eleventh International Conference on Learning Representations, 2023.

Provably Improving Generalization of Few-Shot Models with Synthetic Data IS SYNTHETIC DATA FROM GENERATIVE MODELS READY FOR IMAGE RECOGNITION ? In The Eleventh International Conference on Learning Representations, 2023

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:55.169037Z

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Observation 83589c48-aa80-49f8-a103-cd3c6ec6e8c3 · outbound

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

Provably Improving Generalization of Few-Shot Models with Synthetic Data Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 8

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Observation 486dc2ff-c54b-469f-8dad-1b300920635d · outbound

This paper cites J., yelong shen, Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W.

Provably Improving Generalization of Few-Shot Models with Synthetic Data J., yelong shen, Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W

Reference 9

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Source-reported events for the cited work

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Observation 982d4c98-a630-48df-b8e8-3c6382d6039b · outbound

This paper cites E., Gozeten, H.

Provably Improving Generalization of Few-Shot Models with Synthetic Data E., Gozeten, H

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:54.624762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d7ba4ad0-9f1e-4e1f-9da0-af848934237c · outbound

This paper cites Visual prompt tuning.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Visual prompt tuning

Reference 11

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Source-reported events for the cited work

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Observation 586b4980-1100-4aba-b3a6-725bf7571e2c · outbound

This paper cites U., Wasim, S.

Provably Improving Generalization of Few-Shot Models with Synthetic Data U., Wasim, S

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:54.326148Z

Source-reported events for the cited work

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Observation d1ecf1f7-36fe-419f-9aec-6de55c776458 · outbound

This paper cites M., Bader, J., Alaniz, S., Schmid, C., and Akata, Z.

Provably Improving Generalization of Few-Shot Models with Synthetic Data M., Bader, J., Alaniz, S., Schmid, C., and Akata, Z

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:54.000764Z

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Observation d7f3d25d-b659-440a-961b-d6f6724211ae · outbound

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

Provably Improving Generalization of Few-Shot Models with Synthetic Data 3d object representations for fine-grained categorization

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:53.707842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 701d8848-cba1-4110-96d9-b356ebb0e47a · outbound

This paper cites Image Captions are Natural Prompts for Text-to-Image Models.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Image Captions are Natural Prompts for Text-to-Image Models

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:38:45.376913Z

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Observation 28abff24-e21d-4eca-b7e9-c04fea3d3b8e · outbound

This paper cites Caltech 101, Apr 2022.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Caltech 101, Apr 2022

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:53.403157Z

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Observation 88e937cb-9512-4f5a-a868-5319d771850b · outbound

This paper cites Promptkd: Unsupervised prompt distillation for vision-language models.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Promptkd: Unsupervised prompt distillation for vision-language models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:53.153119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1f36f446-e6cf-4ed5-99e0-6116627bed8d · outbound

This paper cites Gendataagent: On-the-fly dataset augmentation with synthetic data.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Gendataagent: On-the-fly dataset augmentation with synthetic data

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:52.915750Z

Source-reported events for the cited work

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Observation 5934d3e2-1bf7-43b8-ade4-d65f54fd668a · outbound

This paper cites and Hutter, F.

Provably Improving Generalization of Few-Shot Models with Synthetic Data and Hutter, F

Reference 19

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Source-reported events for the cited work

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Observation 6d526937-4aaa-4abd-8a5e-4d5d3df4f252 · outbound

This paper cites Fine-grained visual classification of aircraft, 2013.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Fine-grained visual classification of aircraft, 2013

Reference 20

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Observation 0f4c2c33-4478-41db-a927-973e5bd3dd53 · outbound

This paper cites and Zisserman, A.

Provably Improving Generalization of Few-Shot Models with Synthetic Data and Zisserman, A

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:52.427198Z

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Observation 1fdf3f1a-1950-405e-8302-e0c05b15dcb9 · outbound

This paper cites M., Vedaldi, A., Zisserman, A., and Jawahar, C.

Provably Improving Generalization of Few-Shot Models with Synthetic Data M., Vedaldi, A., Zisserman, A., and Jawahar, C

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:52.207969Z

Source-reported events for the cited work

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Observation 57ed9e1b-0f6e-4cf8-a0ec-c108b296229d · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Learning Transferable Visual Models From Natural Language Supervision

Reference 23

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Observation d2fe40c1-eeff-4161-a7aa-02a46d2fa4d3 · outbound

This paper cites A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets.

Provably Improving Generalization of Few-Shot Models with Synthetic Data A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:38:45.070438Z

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Observation bfd40357-cc50-4f1f-bc99-b277cb036e45 · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

Provably Improving Generalization of Few-Shot Models with Synthetic Data High-Resolution Image Synthesis with Latent Diffusion Models

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 090df595-1e02-4937-9a12-ade297409cd6 · outbound

This paper cites C., and Fei-Fei, L.

Provably Improving Generalization of Few-Shot Models with Synthetic Data C., and Fei-Fei, L

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:51.627721Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8fc76dc8-41f3-4261-b7e5-7e6a0f2ed5d9 · outbound

This paper cites B., Karteek, A., Larlus, D., and Kalantidis, Y.

Provably Improving Generalization of Few-Shot Models with Synthetic Data B., Karteek, A., Larlus, D., and Kalantidis, Y

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:51.351438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3d65c60b-e97c-4026-9911-1f1ef04ae4e2 · outbound

This paper cites D 4m: Dataset distillation via disentangled diffusion model.

Provably Improving Generalization of Few-Shot Models with Synthetic Data D 4m: Dataset distillation via disentangled diffusion model

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:51.094854Z

Source-reported events for the cited work

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Observation ee6b1229-ee2e-4fd9-915f-449b4443b9cb · outbound

This paper cites Gentle local robustness implies generalization.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Gentle local robustness implies generalization

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 85b6af2f-2d59-405c-8fdc-5620fce9b9e8 · outbound

This paper cites A bag-of-prototypes representation for dataset-level applications.

Provably Improving Generalization of Few-Shot Models with Synthetic Data A bag-of-prototypes representation for dataset-level applications

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:50.560648Z

Source-reported events for the cited work

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Observation 61368063-f4d8-4c55-94ab-33c0ae84be38 · outbound

This paper cites Synthetic data, real errors: how (not) to publish and use synthetic data.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Synthetic data, real errors: how (not) to publish and use synthetic data

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:50.317735Z

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Observation 8c8a49ed-263b-41ee-a7d8-503f5e1ffebc · outbound

This paper cites Prototype-based dataset comparison.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Prototype-based dataset comparison

Reference 32

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 85fabc79-c844-4b11-b8c5-2090d6a77d9f · outbound

This paper cites Cafe: Learning to condense dataset by aligning features.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Cafe: Learning to condense dataset by aligning features

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:49.670771Z

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Observation e0582476-735c-424d-adb6-9742b8a27f2b · outbound

This paper cites Dataset Distillation.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Dataset Distillation

Reference 34

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Observation bd598b02-f0ce-4146-b4ac-4c96e6002b5a · outbound

This paper cites A., Oliva, A., and Torralba, A.

Provably Improving Generalization of Few-Shot Models with Synthetic Data A., Oliva, A., and Torralba, A

Reference 35

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Observation b5f187cb-cea2-45ab-8e48-62fe40605d0a · outbound

This paper cites Robust classification with convolutional prototype learning.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Robust classification with convolutional prototype learning

Reference 36

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Observation c0d260da-38ac-46fc-8d66-273f8dc816e4 · outbound

This paper cites Mma: Multi-modal adapter for vision-language models.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Mma: Multi-modal adapter for vision-language models

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:49.038420Z

Source-reported events for the cited work

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Observation 5ea0b9d8-18fc-4488-b0cc-d119d902fc40 · outbound

This paper cites TCP: textual-based class-aware prompt tuning for visual-language model.

Provably Improving Generalization of Few-Shot Models with Synthetic Data TCP: textual-based class-aware prompt tuning for visual-language model

Reference 38

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5ab43f1e-7572-4334-8261-f9e1f362d50b · outbound

This paper cites Mmrl: Multi-modal representation learning for vision-language models.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Mmrl: Multi-modal representation learning for vision-language models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:48.452094Z

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Observation af289633-80da-4be5-bc0c-1995e5de4065 · outbound

This paper cites Real-fake: Effective training data synthesis through distribution matching.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Real-fake: Effective training data synthesis through distribution matching

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:48.142625Z

Source-reported events for the cited work

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Observation 7684245d-7f98-47bc-8190-88c2b416260c · outbound

This paper cites J., Yoo, Y., and Choe, J.

Provably Improving Generalization of Few-Shot Models with Synthetic Data J., Yoo, Y., and Choe, J

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:47.858365Z

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Observation 964bdd0e-7606-47be-a8f3-fbc9611aca71 · outbound

This paper cites N., and Lopez-Paz, D.

Provably Improving Generalization of Few-Shot Models with Synthetic Data N., and Lopez-Paz, D

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:47.557526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b2de58a3-9042-4cd2-9722-563739afa64f · outbound

This paper cites Prompt, generate, then cache: Cascade of foundation models makes strong few-shot learners.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Prompt, generate, then cache: Cascade of foundation models makes strong few-shot learners

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:47.261360Z

Source-reported events for the cited work

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Observation 7ab56058-6f06-45cc-9436-5857f3bf07b6 · outbound

This paper cites and Bilen, H.

Provably Improving Generalization of Few-Shot Models with Synthetic Data and Bilen, H

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:47.007055Z

Source-reported events for the cited work

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Observation 6deed9bc-a7e6-41c7-aa5b-4094ebdeba87 · outbound

This paper cites and Bilen, H.

Provably Improving Generalization of Few-Shot Models with Synthetic Data and Bilen, H

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:46.704367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c251ae38-6d1d-4e0c-9c4e-e65a5ddea0d3 · outbound

This paper cites Improved distribution matching for dataset condensation.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Improved distribution matching for dataset condensation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:46.344725Z

Source-reported events for the cited work

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Observation 86fb7041-06b3-472e-998b-cb8ab0145dff · outbound

This paper cites Toward understanding generative data augmentation.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Toward understanding generative data augmentation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:45.988822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a8e2e808-8f7b-4ae2-aaa3-b1501f8292be · outbound

This paper cites Large language models are good prompt learners for low-shot image classification.

Provably Improving Generalization of Few-Shot Models with Synthetic Data Large language models are good prompt learners for low-shot image classification

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:45.698899Z

Source-reported events for the cited work

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Observation e1c6bb0e-f82d-4e88-a66f-bedf03c0d46f · outbound

This paper cites C., and Liu, Z.

Provably Improving Generalization of Few-Shot Models with Synthetic Data C., and Liu, Z

Reference 49

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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.