Paper Citation Record · LEDGER

Modality Alignment Meets Federated Broadcasting

As of 21 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 2 inbound Pith citation observations for arXiv:2411.15837.

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

pith.paper-citation-record.v1
2411.15837 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:57:39.062543Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T06:02:22.454550Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T05:30:25.627907Z

Reference resolution

59 of 59 outbound references displayed

verified exact0
verified fuzzy52
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fb110c3c-b4ad-460f-a0bd-d6e9ecf2eb27 · outbound

This paper cites Feder- ated learning based on dynamic regularization.

Modality Alignment Meets Federated Broadcasting Feder- ated learning based on dynamic regularization

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.922836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e90aeb01-84cd-4bfa-8695-3fdd226e306c · outbound

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

Modality Alignment Meets Federated Broadcasting Food-101–mining discriminative components with random forests

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.908132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dcdefc91-1c75-42a2-b15c-8fbd710662e4 · outbound

This paper cites Differentially pri- vate secure multi-party computation for federated learning in financial applications.

Modality Alignment Meets Federated Broadcasting Differentially pri- vate secure multi-party computation for federated learning in financial applications

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.893395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 64129642-f038-45f5-981e-873cddf0926e · outbound

This paper cites Plot: Prompt learning with optimal transport for vision-language models.

Modality Alignment Meets Federated Broadcasting Plot: Prompt learning with optimal transport for vision-language models

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.878838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ddce4ad4-89d6-4ba8-ab63-1576b4beb3fc · outbound

This paper cites Exploiting shared representations for personal- ized federated learning.

Modality Alignment Meets Federated Broadcasting Exploiting shared representations for personal- ized federated learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.861829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0b2aeeda-254a-435e-986a-823f855f78bd · outbound

This paper cites Har- monizing generalization and personalization in federated prompt learning.

Modality Alignment Meets Federated Broadcasting Har- monizing generalization and personalization in federated prompt learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T13:57:38.830577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5505e49e-a9b8-42b7-9042-f42b08b40b11 · outbound

This paper cites Unlocking the potential of prompt-tuning in bridging gener- alized and personalized federated learning.

Modality Alignment Meets Federated Broadcasting Unlocking the potential of prompt-tuning in bridging gener- alized and personalized federated learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.837199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b6335961-0fb0-4e81-85f9-22bb91766adf · outbound

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

Modality Alignment Meets Federated Broadcasting An image is worth 16x16 words: Transformers for image recognition at scale

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.821200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a8b99972-2b50-47b3-8daf-2664bec6cb3b · outbound

This paper cites Clip-adapter: Better vision-language models with feature adapters.

Modality Alignment Meets Federated Broadcasting Clip-adapter: Better vision-language models with feature adapters

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T13:57:38.844269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19364d53-69f0-431b-836d-f1ff931f2c17 · outbound

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

Modality Alignment Meets Federated Broadcasting Promptfl: Let federated participants cooper- atively learn prompts instead of models-federated learning in age of foundation model

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.796188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 98ec8311-50ef-42fd-b528-7a7a8ed46dbf · outbound

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

Modality Alignment Meets Federated Broadcasting Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.780980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e24d999f-7d7a-4b27-bcb5-e82024ebcd2e · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Modality Alignment Meets Federated Broadcasting Lora: Low-rank adaptation of large language models

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.766144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d36759f5-cd16-47d3-8927-cd60ea49708d · outbound

This paper cites Diversity-aware meta visual prompting.

Modality Alignment Meets Federated Broadcasting Diversity-aware meta visual prompting

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T13:57:38.861509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ee30112-2865-4a76-8367-71f7b84511db · outbound

This paper cites Generaliz- able heterogeneous federated cross-correlation and instance similarity learning.

Modality Alignment Meets Federated Broadcasting Generaliz- able heterogeneous federated cross-correlation and instance similarity learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.742307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 88a70675-1e05-453f-9b13-cc6051adc4aa · outbound

This paper cites Re- thinking federated learning with domain shift: A prototype view.

Modality Alignment Meets Federated Broadcasting Re- thinking federated learning with domain shift: A prototype view

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.727769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9d48f65c-34d4-4bee-8889-66e0559263c1 · outbound

This paper cites Vi- sual prompt tuning.

Modality Alignment Meets Federated Broadcasting Vi- sual prompt tuning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.713347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2b1c0692-957e-4e2e-9f09-86f6db0ddb26 · outbound

This paper cites End-to-end privacy pre- serving deep learning on multi-institutional medical imag- ing.

Modality Alignment Meets Federated Broadcasting End-to-end privacy pre- serving deep learning on multi-institutional medical imag- ing

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.698314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ff422a49-367a-4816-ae6b-e05072b5d983 · outbound

This paper cites Scaffold: Stochastic controlled averaging for feder- ated learning.

Modality Alignment Meets Federated Broadcasting Scaffold: Stochastic controlled averaging for feder- ated learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.683661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eb7bba81-eb74-49f9-ba88-93c560fb1444 · outbound

This paper cites Maple: Multi-modal prompt learning.

Modality Alignment Meets Federated Broadcasting Maple: Multi-modal prompt learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.668152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d9c2bc6c-abda-4ffb-b72c-f160efb28116 · outbound

This paper cites Continuous multivariate distributions, Volume 1: Models and applications.

Modality Alignment Meets Federated Broadcasting Continuous multivariate distributions, Volume 1: Models and applications

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.653708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 90746845-684e-4a85-acb9-200f5cac13da · outbound

This paper cites Learning multiple layers of features from tiny images, 2009.

Modality Alignment Meets Federated Broadcasting Learning multiple layers of features from tiny images, 2009

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.638668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 84e67403-5fb0-4890-8123-22389b692738 · outbound

This paper cites Evolv- ing parameterized prompt memory for continual learning.

Modality Alignment Meets Federated Broadcasting Evolv- ing parameterized prompt memory for continual learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.624110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0ebf69a4-733e-4818-b12e-8a224f7ae9a0 · outbound

This paper cites Visual prompt based personalized feder- ated learning, 2023.

Modality Alignment Meets Federated Broadcasting Visual prompt based personalized feder- ated learning, 2023

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.608356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4b1b833b-cda5-43f4-a702-d8d78970a054 · outbound

This paper cites Global and local prompts cooperation via optimal transport for fed- erated learning.

Modality Alignment Meets Federated Broadcasting Global and local prompts cooperation via optimal transport for fed- erated learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.593199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e202bad1-fc26-4c6c-9573-ee9546f6874a · outbound

This paper cites Model- contrastive federated learning.

Modality Alignment Meets Federated Broadcasting Model- contrastive federated learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.578065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a225d325-f168-432b-b77b-68d19b4c0250 · outbound

This paper cites Federated optimiza- tion in heterogeneous networks.

Modality Alignment Meets Federated Broadcasting Federated optimiza- tion in heterogeneous networks

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.563279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e20e72a4-6e69-4e62-828b-540d610fd8d9 · outbound

This paper cites Federated learning for open banking.

Modality Alignment Meets Federated Broadcasting Federated learning for open banking

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.549071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 68573e59-ef2c-406a-b513-3e6a0af532c3 · outbound

This paper cites Prompt distribution learning.

Modality Alignment Meets Federated Broadcasting Prompt distribution learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T13:57:38.927952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3541d12e-8b7f-4cba-8632-f8c4888804f8 · outbound

This paper cites Layer-wised model aggregation for personalized federated learning.

Modality Alignment Meets Federated Broadcasting Layer-wised model aggregation for personalized federated learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.525261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f7573371-3364-4f29-9387-dd1265a5aff4 · outbound

This paper cites Fedhpl: Efficient heterogeneous federated learning with prompt tuning and logit distillation,.

Modality Alignment Meets Federated Broadcasting Fedhpl: Efficient heterogeneous federated learning with prompt tuning and logit distillation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.510459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c692bd0-2e2c-4d67-b6d0-8c66cf5f1322 · outbound

This paper cites Language models are few-shot learners.

Modality Alignment Meets Federated Broadcasting Language models are few-shot learners

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.495919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5872d292-c67c-4e9e-8d01-5af50b26c439 · outbound

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

Modality Alignment Meets Federated Broadcasting Communication- efficient learning of deep networks from decentralized data

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.481381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7585e391-1038-4e15-bbc5-7d9a18a34b3b · outbound

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

Modality Alignment Meets Federated Broadcasting Automated flower classification over a large number of classes

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.466529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b38e59a2-5758-45e7-8377-4644d3598cff · outbound

This paper cites Fedbabu: Toward enhanced representation for federated image classi- fication.

Modality Alignment Meets Federated Broadcasting Fedbabu: Toward enhanced representation for federated image classi- fication

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.452048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 22640a28-ae1c-4be6-998a-c8521baff042 · outbound

This paper cites Cats and dogs.

Modality Alignment Meets Federated Broadcasting Cats and dogs

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.438116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4c21d47a-de2d-4ece-b9a0-c5dc7825e379 · outbound

This paper cites Pytorch: An im- perative style, high-performance deep learning library.

Modality Alignment Meets Federated Broadcasting Pytorch: An im- perative style, high-performance deep learning library

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.423801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 82324b52-10ed-48bc-983a-06737716d263 · outbound

This paper cites Re- thinking architecture design for tackling data heterogeneity in federated learning.

Modality Alignment Meets Federated Broadcasting Re- thinking architecture design for tackling data heterogeneity in federated learning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.409234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d7148012-5be1-4783-933b-460ea16e4ddb · outbound

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

Modality Alignment Meets Federated Broadcasting Learn- ing transferable visual models from natural language super- vision

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.395067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e3392011-7539-4c7a-b6f2-4a6d353b42af · outbound

This paper cites Consistency-guided prompt learning for vision-language models.

Modality Alignment Meets Federated Broadcasting Consistency-guided prompt learning for vision-language models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.380231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bba9c9aa-042f-4174-b980-53f6578e7e87 · outbound

This paper cites Coda-prompt: Contin- ual decomposed attention-based prompting for rehearsal-free continual learning.

Modality Alignment Meets Federated Broadcasting Coda-prompt: Contin- ual decomposed attention-based prompting for rehearsal-free continual learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.364051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b00ad77a-7c55-4845-aeea-f3d332acfbe5 · outbound

This paper cites Federated learning from pre-trained models: A contrastive learning approach.

Modality Alignment Meets Federated Broadcasting Federated learning from pre-trained models: A contrastive learning approach

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.349951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f55198f0-1ff3-46da-b417-47691d6f2022 · outbound

This paper cites Fusefl: One-shot federated learning through the lens of causality with progressive model fusion.Advances in Neural Information Processing Systems, 2024.

Modality Alignment Meets Federated Broadcasting Fusefl: One-shot federated learning through the lens of causality with progressive model fusion.Advances in Neural Information Processing Systems, 2024

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.336133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e0113337-7a5a-4190-9f2e-e1681d0f34ce · outbound

This paper cites Gomez, Łukasz Kaiser, and Illia Polosukhin.

Modality Alignment Meets Federated Broadcasting Gomez, Łukasz Kaiser, and Illia Polosukhin

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.322349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b4e1f1c9-5dcc-4a83-ae4e-c97f09d0f588 · outbound

This paper cites Taming cross-domain representation variance in feder- ated prototype learning with heterogeneous data domains.

Modality Alignment Meets Federated Broadcasting Taming cross-domain representation variance in feder- ated prototype learning with heterogeneous data domains

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.308282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 38343b07-f692-4f48-a918-687094b7ad35 · outbound

This paper cites FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations.

Modality Alignment Meets Federated Broadcasting FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T13:57:38.999702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1761d052-1363-446c-a7dc-bcead1b78153 · outbound

This paper cites Communication-efficient federated learning via knowledge distillation.

Modality Alignment Meets Federated Broadcasting Communication-efficient federated learning via knowledge distillation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.294066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 34526b84-a8e4-4356-b1a0-7a0093bd4e9f · outbound

This paper cites Personalized federated learning with feature alignment and classifier col- laboration.

Modality Alignment Meets Federated Broadcasting Personalized federated learning with feature alignment and classifier col- laboration

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.279474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c9b0292f-befb-4233-8684-5334948dc548 · outbound

This paper cites Efficient model personalization in federated learning via client-specific prompt generation.

Modality Alignment Meets Federated Broadcasting Efficient model personalization in federated learning via client-specific prompt generation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.264992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c2c4e0ac-b30b-45e9-ab6a-19cd235584ea · outbound

This paper cites Fedfed: Feature distilla- 10 tion against data heterogeneity in federated learning.

Modality Alignment Meets Federated Broadcasting Fedfed: Feature distilla- 10 tion against data heterogeneity in federated learning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.250407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e794cbc9-576b-45f8-99d9-a0d135d53731 · outbound

This paper cites Visual- language prompt tuning with knowledge-guided context op- timization.

Modality Alignment Meets Federated Broadcasting Visual- language prompt tuning with knowledge-guided context op- timization

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.235162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0797e1b8-3e97-4470-80de-abf530635c6d · outbound

This paper cites Heterogeneous federated learning: State-of-the-art and research challenges.

Modality Alignment Meets Federated Broadcasting Heterogeneous federated learning: State-of-the-art and research challenges

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.219580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 086f874c-8c1a-4683-bfe6-6d1b0d1b8d24 · outbound

This paper cites Task residual for tuning vision-language models.

Modality Alignment Meets Federated Broadcasting Task residual for tuning vision-language models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.204918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9834f591-70ce-4935-bbec-13c8ca2be486 · outbound

This paper cites Low-rank few-shot adaptation of vision-language models.

Modality Alignment Meets Federated Broadcasting Low-rank few-shot adaptation of vision-language models

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.190574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a7b42362-bf38-41d9-8f91-7456b586ac92 · outbound

This paper cites Fedtgp: Trainable global prototypes with adaptive-margin-enhanced contrastive learning for data and model heterogeneity in fed- erated learning.

Modality Alignment Meets Federated Broadcasting Fedtgp: Trainable global prototypes with adaptive-margin-enhanced contrastive learning for data and model heterogeneity in fed- erated learning

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.176119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 316802a1-5f46-4923-8d1a-5f4bfce5ae18 · outbound

This paper cites Tip-adapter: Training-free clip-adapter for better vision- language modeling.

Modality Alignment Meets Federated Broadcasting Tip-adapter: Training-free clip-adapter for better vision- language modeling

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.161481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dbea8e2f-7069-46c2-98a5-7a3b8749efcc · outbound

This paper cites Conditional prompt learning for vision-language mod- els.

Modality Alignment Meets Federated Broadcasting Conditional prompt learning for vision-language mod- els

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T13:57:39.047189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c9351f9-a37b-411e-a317-d5250253bf38 · outbound

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

Modality Alignment Meets Federated Broadcasting Learning to prompt for vision-language models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T13:57:39.052366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8260e189-a283-4b8e-be29-134b75bba5f7 · outbound

This paper cites Impact of the Number of Uploaded Im- age Features.

Modality Alignment Meets Federated Broadcasting Impact of the Number of Uploaded Im- age Features

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.115117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d8656d79-d8d0-4b61-9492-4e3f023dd020 · outbound

This paper cites bird” in the CIFAR10 dataset, the text description in ST style is “a photo of a bird.

Modality Alignment Meets Federated Broadcasting bird” in the CIFAR10 dataset, the text description in ST style is “a photo of a bird

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:57:39.129778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 6666644f-c5d9-4aef-ba4e-f308c35804b5 · inbound

Linguistics-Vision Monotonic Consistent Network for Sign Language Production cites this paper.

Linguistics-Vision Monotonic Consistent Network for Sign Language Production Modality Alignment Meets Federated Broadcasting

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T06:02:22.454550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcbbad25-b899-43b5-b1fa-3c061c526337 · inbound

Efficient Vision Language Model Fine-tuning for Text-based Person Anomaly Search cites this paper.

Efficient Vision Language Model Fine-tuning for Text-based Person Anomaly Search Modality Alignment Meets Federated Broadcasting

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-09T05:30:25.633831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.