Paper Citation Record · LEDGER

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning

As of 10 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:2507.21494.

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

pith.paper-citation-record.v1
2507.21494 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

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measured 63 of 63 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 2026-06-29T12:35:51.321835Z

measured 0 of 1 external citation measurements

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Source: arxiv_reference, observed 2026-06-29T12:43:25.934000Z

Reference resolution

62 of 62 outbound references displayed

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External citation measurements

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Outbound references

Observation 9455adc5-0ed7-4b6f-96d5-0957b228e4a2 · outbound

This paper cites Dusen- berry, Xiuye Gu, Yin Cui, Dustin Tran, Jeremiah Zhe Liu, and Balaji Lakshminarayanan.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Dusen- berry, Xiuye Gu, Yin Cui, Dustin Tran, Jeremiah Zhe Liu, and Balaji Lakshminarayanan

Reference 1

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This paper cites Adaptive test-time personalization for federated learning.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Adaptive test-time personalization for federated learning

Reference 2

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Recogni- tion in terra incognita

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This paper cites Cross- device collaborative test-time adaptation.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Cross- device collaborative test-time adaptation

Reference 4

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This paper cites Marsden, Tobias Raichle, and Bin Yang.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Marsden, Tobias Raichle, and Bin Yang

Reference 5

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 6

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Rockmore

Reference 7

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This paper cites Frustratingly easy test-time adaptation of vision-language models.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Frustratingly easy test-time adaptation of vision-language models

Reference 8

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Observation 9af92280-bb1a-4f4f-94ee-61231298bce9 · outbound

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

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Diverse data augmentation with diffusions for effective test-time prompt tuning

Reference 9

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This paper cites In search of lost domain generalization.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning In search of lost domain generalization

Reference 10

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This paper cites pfedprompt: Learn- ing personalized prompt for vision-language models in fed- erated learning.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning pfedprompt: Learn- ing personalized prompt for vision-language models in fed- erated learning

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This paper cites Promptfl: Let federated participants cooper- atively learn prompts instead of models - federated learning in age of foundation model.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Promptfl: Let federated participants cooper- atively learn prompts instead of models - federated learning in age of foundation model

Reference 12

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This paper cites Deep residual learning for image recognition.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Deep residual learning for image recognition

Reference 13

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Dietterich

Reference 14

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This paper cites Aug- mix: A simple data processing method to improve robustness and uncertainty.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Aug- mix: A simple data processing method to improve robustness and uncertainty

Reference 15

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

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig

Reference 16

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This paper cites Test-time robust personaliza- tion for federated learning.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Test-time robust personaliza- tion for federated learning

Reference 17

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This paper cites Brendan McMahan, Brendan Avent, Aur´elien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Brendan McMahan, Brendan Avent, Aur´elien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A

Reference 18

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

Reference 19

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Observation 152754f3-2a29-4df9-a59f-d1024cd0f0a7 · outbound

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

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Learning multiple layers of features from tiny images

Reference 20

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This paper cites A comprehensive sur- vey on test-time adaptation under distribution shifts.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning A comprehensive sur- vey on test-time adaptation under distribution shifts

Reference 21

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This paper cites Fedclip: Fast generalization and personalization for CLIP in federated learning.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Fedclip: Fast generalization and personalization for CLIP in federated learning

Reference 22

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This paper cites Communication- efficient learning of deep networks from decentralized data.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Communication- efficient learning of deep networks from decentralized data

Reference 23

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This paper cites Federated learning from vision-language foundation models: Theoretical analy- sis and method.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Federated learning from vision-language foundation models: Theoretical analy- sis and method

Reference 24

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This paper cites Federated text-driven prompt generation for vision- language models.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Federated text-driven prompt generation for vision- language models

Reference 25

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This paper cites Learning transferable visual models from natural language supervision.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Learning transferable visual models from natural language supervision

Reference 26

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Ronny Huang, and Tom Goldstein

Reference 28

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Test- time prompt tuning for zero-shot generalization in vision- language models

Reference 29

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This paper cites Just shift it: Test-time prototype shifting for zero-shot general- ization with vision-language models.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Just shift it: Test-time prototype shifting for zero-shot general- ization with vision-language models

Reference 30

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This paper cites Is heterogeneity notorious? taming heterogeneity to handle test-time shift in federated learning.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Is heterogeneity notorious? taming heterogeneity to handle test-time shift in federated learning

Reference 31

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Visualizing data using t-sne

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Ol- shausen, and Trevor Darrell

Reference 33

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Beyond Model Adaptation at Test Time: A Survey

Reference 35

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This paper cites A joint training-calibration framework for test-time personalization with label shift in federated learning.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning A joint training-calibration framework for test-time personalization with label shift in federated learning

Reference 36

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This paper cites Fair federated learning with biased vision- language models.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Fair federated learning with biased vision- language models

Reference 37

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Sycara, and Yaqi Xie

Reference 38

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Robust test- time adaptation for zero-shot prompt tuning

Reference 39

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Historical test-time prompt tuning for vision foundation models

Reference 40

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This paper cites Enabling collaborative test- time adaptation in dynamic environment via federated learn- ing.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Enabling collaborative test- time adaptation in dynamic environment via federated learn- ing

Reference 41

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning MEMO: test time robustness via adaptation and augmentation

Reference 42

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Tip- adapter: Training-free adaption of CLIP for few-shot classi- fication

Reference 43

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Boostadapter: Improving vision- language test-time adaptation via regional bootstrapping

Reference 44

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Adanpc: Ex- ploring non-parametric classifier for test-time adaptation

Reference 45

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This paper cites Dual memory networks: A ver- satile adaptation approach for vision-language models.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Dual memory networks: A ver- satile adaptation approach for vision-language models

Reference 46

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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Conditional prompt learning for vision-language models

Reference 47

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

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Learning to prompt for vision-language models

Reference 48

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2c5b1e5b-d331-41a0-b74d-78d288ad6493 · outbound

This paper cites an unresolved cited work.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-06T12:49:38.966670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f82d452a-277e-4239-894e-f85326bc932b · outbound

This paper cites Remark C.2.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Remark C.2

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:49:38.951935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dcdd7129-282b-4abd-a848-68d3b7408104 · outbound

This paper cites Let pρ := V ol(G(+µ, h(m∗.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Let pρ := V ol(G(+µ, h(m∗

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:49:38.936815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b9b794a8-e1b1-4dfc-8128-68bea6153cc8 · outbound

This paper cites an unresolved cited work.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

Reference 55

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T12:49:38.921950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 13abccfc-d507-4ef9-9a2a-19da4cf02cdd · outbound

This paper cites Since 0 < pρ < 1, and 1[fi∈R(h(m∗ 1 −ρ′wpre))] ∼ Bern(pρ), then for any κ ∈ [k], as n → ∞, Pr[∥m1,κ − m∗ 1∥ > ρ] = Pr[ m1,κ /∈ G(0) ∩ B(m∗ 1, ρ)] ≤ Pr[m1,κ /∈ G(h(m∗.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Since 0 < pρ < 1, and 1[fi∈R(h(m∗ 1 −ρ′wpre))] ∼ Bern(pρ), then for any κ ∈ [k], as n → ∞, Pr[∥m1,κ − m∗ 1∥ > ρ] = Pr[ m1,κ /∈ G(0) ∩ B(m∗ 1, ρ)] ≤ Pr[m1,κ /∈ G(h(m∗

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:49:38.905659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 11c65ffb-60fd-4cb1-a151-f372264bbfda · outbound

This paper cites an unresolved cited work.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-06T12:49:38.888225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 096dbf15-577a-4f93-beeb-bc17cc1123cd · outbound

This paper cites an unresolved cited work.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-06T12:49:38.871493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4c3da4bd-97f6-44e6-b829-9f3362e75fcd · outbound

This paper cites This implies that m1,κ P → m∗ 1 for every κ ∈ [k].

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning This implies that m1,κ P → m∗ 1 for every κ ∈ [k]

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:49:38.856090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 47b4af91-652e-4c0f-9f61-5697a34452b7 · outbound

This paper cites So this is proved.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning So this is proved

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:49:38.839450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 53652b9f-9475-4976-8670-34b28fd52bd8 · outbound

This paper cites an unresolved cited work.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-06T12:49:38.823637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b25fc061-ff09-439d-87a4-af8cf14b8385 · outbound

This paper cites itap of a {class}.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning itap of a {class}

Reference 62

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T12:49:38.806805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 76b0df00-448c-47f2-bdfb-78dfc6abe9ea · outbound

This paper cites an unresolved cited work.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

Reference 2021

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T12:49:39.662256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 20070230-42bd-4bcf-9053-7c4a710a95a6 · outbound

This paper cites an unresolved cited work.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning Unresolved cited work

Reference 2024

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T12:49:39.436163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2fe36549-a14f-42d5-9e1d-5c71f22d7cfb · outbound

This paper cites 1, 2, 3, 6, 7, 25, 26.

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning 1, 2, 3, 6, 7, 25, 26

Reference 8763

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:49:39.309920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 36a75d85-dcb9-4b9f-9650-beced2d319eb · inbound

FedMPT: Federated Multi-label Prompt Tuning of Vision-Language Models cites this paper.

FedMPT: Federated Multi-label Prompt Tuning of Vision-Language Models Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:43:25.936003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.