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Paper Citation Record · LEDGER

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning

As of 9 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2506.10575.

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

pith.paper-citation-record.v1
2506.10575 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:29:26.022916Z

measured 57 of 57 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

57 of 57 outbound references displayed

  • verified exact6
  • verified fuzzy29
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 24aece88-8079-4a30-ba7c-32df2a373b82 · outbound

This paper cites Flamingo: a visual language model for few- shot learning.Advances in Neural Information Processing Systems, 35:23716–23736, 2022.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Flamingo: a visual language model for few- shot learning.Advances in Neural Information Processing Systems, 35:23716–23736, 2022

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:33.806086Z

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.

source=pdf_text observed=2026-08-07T04:29:20.912833Z digest=sha256:9abfe63e69afe049993678ffc8a26d40466e9f2269b00f722feba31e4caaa553

Observation 1552687b-5962-46d6-aecc-2cb2e60d956b · outbound

This paper cites Laso: Label-set operations networks for multi-label few-shot learning.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Laso: Label-set operations networks for multi-label few-shot learning

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:33.647913Z

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.

source=pdf_text observed=2026-08-07T04:29:20.985698Z digest=sha256:6664070a5fb1470401abeea7a97c4f588f98060954778806a2acc549f0735454

Observation 5efae362-3a40-4e91-b222-daec85b6a6d3 · outbound

This paper cites Structured semantic transfer for multi-label recognition with partial labels.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Structured semantic transfer for multi-label recognition with partial labels

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-07T04:29:33.518040Z

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.

source=pdf_text observed=2026-08-07T04:29:21.065735Z digest=sha256:0b6797dcfef0f6f7af0371142688ca5579717b793790ad9420d60ce30ca1a629

Observation a6051b62-25ce-4961-a61e-9d26f9b257e2 · outbound

This paper cites Recurrent attentional reinforcement learning for multi-label image recognition.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Recurrent attentional reinforcement learning for multi-label image recognition

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T04:29:33.309046Z

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.

source=pdf_text observed=2026-08-07T04:29:21.140117Z digest=sha256:5e047dd6f38a47ab0d39057a61898c5ed892bff04b770a9c615890d888116885

Observation 048f16a2-88e9-4802-8a94-4b8d63e5d365 · outbound

This paper cites Learning semantic-specific graph representation for multi-label image recognition.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Learning semantic-specific graph representation for multi-label image recognition

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-07T04:29:33.067742Z

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.

source=pdf_text observed=2026-08-07T04:29:21.302799Z digest=sha256:0dd6d2702584567a9da7f6733beeaa5db6d96ab514e00a3676a2a623f731bb9f

Observation 39eed48b-0cdf-4cb1-824d-24101b2bda98 · outbound

This paper cites Multi- label image recognition with graph convolutional networks.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Multi- label image recognition with graph convolutional networks

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:32.749727Z

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.

source=pdf_text observed=2026-08-07T04:29:21.394607Z digest=sha256:829f9e400545ab661920f6317479bc96d49b75e902a2cc37eb04593eead7fac5

Observation 235e497b-5f42-4b70-a15f-61e19b4031f5 · outbound

This paper cites Stargan v2: Diverse image synthesis for multiple domains.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Stargan v2: Diverse image synthesis for multiple domains

Reference 8

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no resolver link, observed 2026-08-07T04:29:21.467483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:21.467483Z digest=sha256:a35eead8d8251fed01b0177ec5dd85682c67535cf2cac14c0f134ec54f67278c

Observation 5945c96b-80b9-4135-8f0b-7f51c38f2fa0 · outbound

This paper cites Nus-wide: a real-world web image database from national university of singapore.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Nus-wide: a real-world web image database from national university of singapore

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:32.482326Z

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.

source=pdf_text observed=2026-08-07T04:29:21.545489Z digest=sha256:e1ea802a6895f4607feefff358e9231d501369b45169c97965304e0e7008558a

Observation e41dbda1-01c0-46d6-9b8d-a374b62d3df8 · outbound

This paper cites Bayesian Prompt Learning for Image-Language Model Generalization.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Bayesian Prompt Learning for Image-Language Model Generalization

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:29:27.519841Z

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.

source=pdf_text observed=2026-08-07T04:29:21.628262Z digest=sha256:c2f43e37a4574ba3a0e08e8205917878c5e1ba3610f0ce56c371b4af57494b2f

Observation 422915f3-7be1-4344-8f8b-0645292626ed · outbound

This paper cites Learning a deep convnet for multi-label classification with partial labels.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Learning a deep convnet for multi-label classification with partial labels

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-07T04:29:32.223302Z

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.

source=pdf_text observed=2026-08-07T04:29:21.708820Z digest=sha256:b9ff660365b3d1fdfed7a17f80ce0e2a3037299ab4af5b0b7e87240f13aa6759

Observation 1dea58b2-387b-4247-b1cb-07baa7981e5a · outbound

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

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning The pascal visual object classes (voc) challenge

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:32.110623Z

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.

source=pdf_text observed=2026-08-07T04:29:21.758256Z digest=sha256:656f6b50393ec17744387adee9ec55041ff918e70c67f296b694bf6bc757b803

Observation df16fc1f-6483-4425-bf26-883dbb59b702 · outbound

This paper cites Learning federated visual prompt in null space for mri reconstruction.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Learning federated visual prompt in null space for mri reconstruction

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:31.979476Z

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.

source=pdf_text observed=2026-08-07T04:29:21.841049Z digest=sha256:0a4bde09e6c52dfeea6ae249bfdf22294d050aa18eb2b57e51ad42c849354902

Observation c93a5f1e-5710-4697-bdcc-ae4a8987fc02 · outbound

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

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Diverse data augmentation with diffusions for effective test-time prompt tuning

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:31.848906Z

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.

source=pdf_text observed=2026-08-07T04:29:21.916666Z digest=sha256:87a4b4d564f94f50c77d7a8c3fb35191d3febb675b3c192f0ed51c8125b3cc70

Observation 1cc7885b-241b-46f2-bae0-8af644ddc3e6 · outbound

This paper cites Deep Convolutional Ranking for Multilabel Image Annotation.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Deep Convolutional Ranking for Multilabel Image Annotation

Reference 15

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no resolver link, observed 2026-08-07T04:29:22.002407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:22.002407Z digest=sha256:064f573ae502ff1df74d1f55719cd102caaa9e4e7d0c5ae9c2ba73b15b79cc25

Observation 925ea13d-e7ed-4268-9490-fc6d23eebb5b · outbound

This paper cites Gener- ative adversarial networks.Communications of the ACM, 63(11):139–144, 2020.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Gener- ative adversarial networks.Communications of the ACM, 63(11):139–144, 2020

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:31.670788Z

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.

source=pdf_text observed=2026-08-07T04:29:22.076053Z digest=sha256:8e52c26fb6b9a80bde11b2e1f94c434997d694d5058898603fd26deaeaeae393

Observation a135c362-b34c-441a-b0e1-d298e75e8688 · outbound

This paper cites I Can't Believe There's No Images! Learning Visual Tasks Using only Language Supervision.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning I Can't Believe There's No Images! Learning Visual Tasks Using only Language Supervision

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:29:27.334748Z

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.

source=pdf_text observed=2026-08-07T04:29:22.172146Z digest=sha256:5e49ad32f0f6864e337cbf861e665f2ee0e6e9ce30844a5abafb58cfa0503e58

Observation 43de6bae-3c0d-4fa4-8064-fc9267afba04 · outbound

This paper cites Texts as Images in Prompt Tuning for Multi-Label Image Recognition.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Texts as Images in Prompt Tuning for Multi-Label Image Recognition

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:29:27.005782Z

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.

source=pdf_text observed=2026-08-07T04:29:22.246265Z digest=sha256:89e5995433c206b398b26a6ab20fac71aaac478422418c0ce8c470d43a096f3d

Observation 54d438c6-cdf6-4d65-82f8-29d6c4fc8afe · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Imagen Video: High Definition Video Generation with Diffusion Models

Reference 19

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no resolver link, observed 2026-08-07T04:29:22.304194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:22.304194Z digest=sha256:f94c51ff440cfe048ce92d8a485cac47c08214d405ccaa8c33309962e01c0ebe

Observation cac53a72-af1a-4bcd-8974-9ffe1b0e1fef · outbound

This paper cites Learning Prompt with Distribution-Based Feature Replay for Few-Shot Class-Incremental Learning.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Learning Prompt with Distribution-Based Feature Replay for Few-Shot Class-Incremental Learning

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:22.377613Z digest=sha256:74f556ed172d97109e624a49980a3a642d390e5c05f600b0bb2ef55a6450ce4b

Observation 759e43e3-18a9-41aa-9f15-c2db223297a5 · outbound

This paper cites Class concept rep- resentation from contextual texts for training-free multi-label recognition.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Class concept rep- resentation from contextual texts for training-free multi-label recognition

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:31.536598Z

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.

source=pdf_text observed=2026-08-07T04:29:22.437023Z digest=sha256:268f360657e702a6268169301687d152f56484c3ae6dd0d82d966ea964522eb2

Observation 151bea06-1562-4acc-b5f9-115f8abc2da4 · outbound

This paper cites Enhancing clip conceptual embedding through knowl- edge distillation, 2024.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Enhancing clip conceptual embedding through knowl- edge distillation, 2024

Reference 22

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raw_fallback, observed 2026-08-07T04:29:31.301209Z

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.

source=pdf_text observed=2026-08-07T04:29:22.529549Z digest=sha256:b23b82a7e1bc3660eb80b0c0c21f409a8c8d1b1e066acfa86899ca544f98414f

Observation 99c04b5b-f88f-4d51-95c0-fcaf71f40039 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Adam: A Method for Stochastic Optimization

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:22.608769Z digest=sha256:f5abe9d7783a6c35dba9a4fc1737c0b0f8b947caf54f4d31d4b8e652b13fe3ce

Observation 52dbb060-3b2b-477f-a02b-be5cbc2d169c · outbound

This paper cites Auto-Encoding Variational Bayes.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Auto-Encoding Variational Bayes

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:22.693267Z digest=sha256:d4cb59c8937a3c293c8cb63a2a582ee66b64abecdf4da34c79ba493f19aba0df

Observation d2f91786-85d5-485a-b6e4-ee057a6ffe95 · outbound

This paper cites Openimages: A public dataset for large-scale multi-label and multi-class image classification.Dataset available from https://github.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Openimages: A public dataset for large-scale multi-label and multi-class image classification.Dataset available from https://github

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-07T04:29:30.991687Z

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.

source=pdf_text observed=2026-08-07T04:29:22.787514Z digest=sha256:37d72a70db2ba51eee7fc318f1e4b07be521bc523e15b59e5f065357ff09c9a7

Observation 9325cba4-ff10-48d2-a049-c1ef4caf4611 · outbound

This paper cites Microsoft coco: Common objects in context.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Microsoft coco: Common objects in context

Reference 26

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no resolver link, observed 2026-08-07T04:29:22.866684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:22.866684Z digest=sha256:08828cb806ba76dee5398d46f563902131f05ff857e6453b0bf6c0f9825ade4b

Observation 8f654f19-4017-4f3f-9870-981ca8d86a5f · outbound

This paper cites Compositional visual generation with composable diffusion models.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Compositional visual generation with composable diffusion models

Reference 27

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no resolver link, observed 2026-08-07T04:29:22.937312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:22.937312Z digest=sha256:9b06f5770c7f6b0a39f21f526ec4717b83be58f4cf9ca73b018f1bdac84809a6

Observation 174fc98a-68c0-4902-95e4-34ca7f7c42b2 · outbound

This paper cites Multi-label image classification via knowledge distillation from weakly-supervised detection.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Multi-label image classification via knowledge distillation from weakly-supervised detection

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:30.851628Z

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.

source=pdf_text observed=2026-08-07T04:29:22.992006Z digest=sha256:59a238b2c0b9834925ce99b1c396aae54faa421a258f9a703de34f533aff0580

Observation 940ac585-f768-4090-b721-ff3dd2c0cd50 · outbound

This paper cites Decoupled Weight Decay Regularization.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Decoupled Weight Decay Regularization

Reference 29

Resolution
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no resolver link, observed 2026-08-07T04:29:23.154171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:23.154171Z digest=sha256:dd10c5b443d0a80b132a28d4d51380d23407d13be850dd75624353d95aac378b

Observation 60b3b8b3-01c9-4ce7-8665-67607d9997c3 · outbound

This paper cites T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models

Reference 30

Resolution
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no resolver link, observed 2026-08-07T04:29:23.300405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:23.300405Z digest=sha256:b23d14c58064bd5ff18dd3dd6e3798df2c4993418cc496ee831cd24ff5b75a27

Observation e145ff17-4e59-44aa-8190-0fecda34f588 · outbound

This paper cites Discriminative region-based multi- label zero-shot learning.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Discriminative region-based multi- label zero-shot learning

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:30.640677Z

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.

source=pdf_text observed=2026-08-07T04:29:23.497066Z digest=sha256:1c21ca88bb57065e8a64b6c2d73c8ad635a38891c9af1f3fbadb8ca0d0f77554

Observation 4bd800af-6817-439b-aa85-83e068109af3 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 32

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no resolver link, observed 2026-08-07T04:29:23.648601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:23.648601Z digest=sha256:f1de8a961d314751d40f33a8dceb9e7dd898d063c57054004db1a62712e76745

Observation 09055feb-c934-45bb-b5b2-a5b9304eaafe · outbound

This paper cites Text-Only Training for Image Captioning using Noise-Injected CLIP.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Text-Only Training for Image Captioning using Noise-Injected CLIP

Reference 33

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no resolver link, observed 2026-08-07T04:29:23.701411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:23.701411Z digest=sha256:069dbad42efee9c4021e09272c1d37796635981723d9e8ccabd99cdb5432035c

Observation 9c55f7d6-eb43-4fbc-9bec-9eddc3062d8f · outbound

This paper cites Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023

Reference 34

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no resolver link, observed 2026-08-07T04:29:23.757452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:23.757452Z digest=sha256:dca436bdad39bced6157f3283ed2171f24e206dee6eaa8c5247d92e9aebf2005

Observation ad348d85-18e1-4a2d-8f9e-f92ce3949f50 · outbound

This paper cites Semantic-aware representation blending for multi-label image recognition with partial labels.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Semantic-aware representation blending for multi-label image recognition with partial labels

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:30.451465Z

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.

source=pdf_text observed=2026-08-07T04:29:23.827478Z digest=sha256:f8ba8d4a531fd8903b11e1bb90988d3f6e784fa0c854ed49a89626cee8f20154

Observation c98aeb9a-3e22-4866-98ec-8e79f405e115 · outbound

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

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Learning transferable visual models from natural language supervision

Reference 36

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unresolved
no resolver link, observed 2026-08-07T04:29:23.905795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:23.905795Z digest=sha256:2ddb039c24e94c10ff49cd49eb0318aa3f8a81fff287d694938328e7459496e7

Observation 93cbaf98-1dac-440e-8fe9-4168ea114428 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 37

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no resolver link, observed 2026-08-07T04:29:23.971618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:23.971618Z digest=sha256:de25daa6773d02c6688bf4d1bfa0949980d775f8934e7343f09a8c837dd677c6

Observation 67c2f28a-8042-4ba4-83f8-7b31737b9bfc · outbound

This paper cites Rethinking Prompting Strategies for Multi-Label Recognition with Partial Annotations.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Rethinking Prompting Strategies for Multi-Label Recognition with Partial Annotations

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:29:26.741089Z

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.

source=pdf_text observed=2026-08-07T04:29:24.067977Z digest=sha256:dde5eab34563526d2bb7cb2f5daa12c2819234d1b0314cc1c6d83a1bab777174

Observation 3e5370b9-3067-4406-b06a-7fa346309749 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning High-resolution image synthesis with latent diffusion models

Reference 39

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unresolved
no resolver link, observed 2026-08-07T04:29:24.140777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:24.140777Z digest=sha256:15a1e31b80630474bfdefa1b792e90b0522aa1c82f57fdc3dde051666ced4514

Observation 6e4f146f-2784-4af2-8e8a-503d755e9b84 · outbound

This paper cites DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation

Reference 40

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unresolved
no resolver link, observed 2026-08-07T04:29:24.201454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:24.201454Z digest=sha256:1cfbb037045038bc925791ff5b01d6a31134e393d546cf4dd8bf9f04053a49f8

Observation 4f3c9b3c-79d2-489f-ab99-da2bca4e214d · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.Advances in Neural Information Processing Systems, 35:36479–36494, 2022.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Photorealistic text-to-image diffusion models with deep language understanding.Advances in Neural Information Processing Systems, 35:36479–36494, 2022

Reference 41

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no resolver link, observed 2026-08-07T04:29:24.328312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:24.328312Z digest=sha256:e6aebc26cf5f4d8e1c46024b7a29090913b926fdc279aa7ecb23d3f9db571262

Observation b82ffa68-b37d-4f30-be73-b103de74c0ae · outbound

This paper cites Meta-learning for multi-label few-shot classification.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Meta-learning for multi-label few-shot classification

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:30.155597Z

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.

source=pdf_text observed=2026-08-07T04:29:24.397782Z digest=sha256:cb54c7475f4d8f9ed036b049c443c462a1eef9f3e1aaea04943ddd6105a2a2a6

Observation 92e242d5-05a3-4554-919b-970c885771cd · outbound

This paper cites D2c: Diffusion-decoding models for few-shot conditional generation.Advances in Neural Information Processing Systems, 34:12533–12548, 2021.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning D2c: Diffusion-decoding models for few-shot conditional generation.Advances in Neural Information Processing Systems, 34:12533–12548, 2021

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:29.964146Z

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.

source=pdf_text observed=2026-08-07T04:29:24.456552Z digest=sha256:31559644a49e05261c24fd2e2ddbd7e4116d48bf673f67bca143ebdeb8e10ff2

Observation 2bce9440-2692-46ef-9e32-e27523688dcd · outbound

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

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:29:26.503407Z

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.

source=pdf_text observed=2026-08-07T04:29:24.565152Z digest=sha256:e6b17e5bbe277596fb83ab4cf03805595ed3b3bcfe1cdcba88b34fb2a9a7e725

Observation 6fdb1315-0afe-44f3-9465-a167a5c433b5 · outbound

This paper cites Vl-adapter: Parameter- efficient transfer learning for vision-and-language tasks.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Vl-adapter: Parameter- efficient transfer learning for vision-and-language tasks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:29.756867Z

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.

source=pdf_text observed=2026-08-07T04:29:24.669507Z digest=sha256:ab718f5f2344e8fbf52abcaf3c8acea0a7fd347814e40e01c943abcb3774b44e

Observation af3ca6be-ea1e-4188-859c-f811ac3a0582 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning LLaMA: Open and Efficient Foundation Language Models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T04:29:24.742090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:24.742090Z digest=sha256:9377934feb135bfbda89331350889a176d3862751cf38cd2cc9b9643c3eef0ee

Observation 69079c93-4405-4a67-b3dd-facb53320b39 · outbound

This paper cites Schwing, and Heng Ji.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Schwing, and Heng Ji

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:29.467747Z

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.

source=pdf_text observed=2026-08-07T04:29:24.822899Z digest=sha256:413cf0f79121e2fee7acf19a40e1fc084225cf0dd0b87958e7367ecd2c445cd0

Observation 22bd1813-84d4-49b2-b047-f7026cd06b86 · outbound

This paper cites Cnn-rnn: A unified framework for multi-label image classification.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Cnn-rnn: A unified framework for multi-label image classification

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:29.250117Z

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.

source=pdf_text observed=2026-08-07T04:29:24.906797Z digest=sha256:eb8705f1064a4bc7f81427a99361f8727115ac275e19d067959bcf2e9c103456

Observation 174fdf45-c604-41ac-b7e2-25289eee0a40 · outbound

This paper cites Beyond object proposals: Random crop pooling for multi-label image recognition.IEEE Transactions on Image Processing, 25(12):5678–5688, 2016.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Beyond object proposals: Random crop pooling for multi-label image recognition.IEEE Transactions on Image Processing, 25(12):5678–5688, 2016

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:29.090608Z

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.

source=pdf_text observed=2026-08-07T04:29:25.011815Z digest=sha256:103c450fde72b2753dc0c784cf0172747a4b5d1bd906884831f0685b2a66326f

Observation dce809da-2730-4619-affa-4980c9be33dd · outbound

This paper cites Multi-label classification with label graph superimposing.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Multi-label classification with label graph superimposing

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:28.742045Z

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.

source=pdf_text observed=2026-08-07T04:29:25.068637Z digest=sha256:a15803c2f927621e7ff5c089a388f6b81ed0830d4052ee7bdd57d96130a46c2e

Observation 48618230-4984-4bd0-acf7-75eadd39a688 · outbound

This paper cites Multi-label image recognition by recurrently discovering attentional regions.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Multi-label image recognition by recurrently discovering attentional regions

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:28.509634Z

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.

source=pdf_text observed=2026-08-07T04:29:25.215372Z digest=sha256:97e21a75a4d97f119cfe26847481dd089a5e9afc0fbdabce5599ac9d56f93ef1

Observation fb074065-6d3a-4991-9b4d-40e4d1514758 · outbound

This paper cites TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable Prompt.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable Prompt

Reference 52

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no resolver link, observed 2026-08-07T04:29:25.323228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:25.323228Z digest=sha256:5a24782a770a9f47a1b3bf21cb07b1338d6ee294bafaafdcaaeda5716847a323

Observation dbdbd1f7-a38c-4168-9111-1df0ebb44a80 · outbound

This paper cites Orderless recurrent models for multi-label classification.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Orderless recurrent models for multi-label classification

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:28.291057Z

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.

source=pdf_text observed=2026-08-07T04:29:25.508076Z digest=sha256:61f5f41e2fba05af72a01f41c7f1f71fc1ced9c6c3faa2fe6f984972a964329c

Observation 7ca2c462-991a-4087-9e94-b6d750d30dbb · outbound

This paper cites Tip-adapter: Training-free adaption of clip for few-shot classification.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Tip-adapter: Training-free adaption of clip for few-shot classification

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:28.026308Z

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.

source=pdf_text observed=2026-08-07T04:29:25.657227Z digest=sha256:9001effd24afedac4507e133a66028f6f43946b78929a94c93b0ca664a4693a4

Observation 34f917ba-feac-407e-b5f9-f4cd954240b7 · outbound

This paper cites Transformer-based dual relation graph for multi-label image recognition.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Transformer-based dual relation graph for multi-label image recognition

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:29:27.754042Z

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.

source=pdf_text observed=2026-08-07T04:29:25.787028Z digest=sha256:6d1a962045954fa14a6c67d3c9d14a508cd9aabe4205e7d6f907772bb0d0d38f

Observation 786f5b84-e50e-41b7-84be-a94a0819c3be · outbound

This paper cites Con- ditional prompt learning for vision-language models.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Con- ditional prompt learning for vision-language models

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T04:29:25.856436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:25.856436Z digest=sha256:09810f4d53b37b78d4ebb27a87b04dafdb7eaa6ddb3ed288f3480d04900c669a

Observation 2320c6c6-4efe-499d-b709-e6fc9b5d7e67 · outbound

This paper cites Learning to prompt for vision-language models.International Journal of Computer Vision, 130(9):2337–2348, 2022.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Learning to prompt for vision-language models.International Journal of Computer Vision, 130(9):2337–2348, 2022

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T04:29:25.936192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:29:25.936192Z digest=sha256:50bd16d549ae7ba76fb4d0d0d0dc8be5349b2aa137aef0c9833b4f72442e4d15

Observation c164c584-c577-4927-b2c5-dd84080dafe2 · outbound

This paper cites Prompt-aligned Gradient for Prompt Tuning.

Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Prompt-aligned Gradient for Prompt Tuning

Reference 58

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:29:26.267957Z

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.

source=pdf_text observed=2026-08-07T04:29:26.022916Z digest=sha256:0da2fc9858e4d7785e3e5799dd9ea7a63c33b39e91f02c4a963cd18fe2b28569

Pith citing papers

No inbound Pith citation observations are available.