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Paper Citation Record · LEDGER

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition

As of 22 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2607.06185.

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

pith.paper-citation-record.v1
2607.06185 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-08T14:18:26.034732Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

52 of 52 outbound references displayed

  • verified exact1
  • verified fuzzy49
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5f054b01-2446-40c3-9f4c-5d7df7dcf5a1 · outbound

This paper cites Zero-shot sketch-based image retrieval via adaptive relation-aware metric learning.Pattern Recognition, 152:110452, 2024.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Zero-shot sketch-based image retrieval via adaptive relation-aware metric learning.Pattern Recognition, 152:110452, 2024

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 4257dea1-2f34-488d-8647-24340aea0992 · outbound

This paper cites Complementary two-branch transformer for multi-label image retrieval.Pattern Recognition, 168:111806, 2025.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Complementary two-branch transformer for multi-label image retrieval.Pattern Recognition, 168:111806, 2025

Reference 2

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verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.733909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:4c4f513ba1abf0d3ac8094aedfd3d0b713c7c91e61a853e7f0b6a7dd71d7891f

Observation c6bcdfc1-f9b7-4274-93b5-6220fd887b93 · outbound

This paper cites Changes to captions: An attentive network for remote sensing change captioning.IEEE Transactions on Image Processing, 32:6047–6060.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Changes to captions: An attentive network for remote sensing change captioning.IEEE Transactions on Image Processing, 32:6047–6060

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:d454baf8f2b47931a0083a46166e70efcace7e1cf2b8b8f9e482260a2ea65241

Observation 2619a5e9-4986-4e2e-9505-a776128d2e1e · outbound

This paper cites Reparameterizing and dynamically quantizing image features for image generation.Pattern Recognition, 146:109962, 2024.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Reparameterizing and dynamically quantizing image features for image generation.Pattern Recognition, 146:109962, 2024

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.765179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:0ab816e9cd5ada83ceae57c10af73d693f275d02ed1eecbce6717fddf90857a5

Observation 457afc4a-fbff-47e4-b2c5-044ee1daecca · outbound

This paper cites Txt2img-mhn: Remote sensing image generation from text using modern hopfield networks.IEEE Transactions on Image Processing, 32:5737–5750, 2023.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Txt2img-mhn: Remote sensing image generation from text using modern hopfield networks.IEEE Transactions on Image Processing, 32:5737–5750, 2023

Reference 5

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verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.745153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:34a674a2a06ad06e890dbb2ee8ab8595560788eaea92c34021feb66ace8de1a0

Observation 8cab65bd-bc48-470e-8b87-d1954ace260d · outbound

This paper cites Fine grained food image recognition based on swin transformer.Journal of Food Engineering, 380:112134, 2024.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Fine grained food image recognition based on swin transformer.Journal of Food Engineering, 380:112134, 2024

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.756922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:3e7c17b0d310ea54f5b3439b94531fd9bbf67d9409b33e9682fd67a1926432b7

Observation 2a15d086-99f8-459b-a9e6-c9bb8ca40704 · outbound

This paper cites Convolution-enhanced bi-branch adaptive transformer with cross-task interaction for food category and ingredient recognition.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Convolution-enhanced bi-branch adaptive transformer with cross-task interaction for food category and ingredient recognition

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.708646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:e179a6f53feed249754505b5d444bb85b830b83da2da6f0650e46a6d990b39ff

Observation 0e5bf17c-d22f-4446-95e4-6484bf41ee95 · outbound

This paper cites Synthesizing knowledge-enhanced features for real-world zero-shot food detection.IEEE Transactions on Image Processing, 33:1285–1298, 2024.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Synthesizing knowledge-enhanced features for real-world zero-shot food detection.IEEE Transactions on Image Processing, 33:1285–1298, 2024

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.701543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:5ea61f547adaed0766642495905fdbc25d556bb01bfa1c9d4e82c962d7c16fe4

Observation fd9f48da-440a-4d1b-8c27-3b0e0d2205f9 · outbound

This paper cites Food recommendation towards personalized wellbeing.Trends in Food Science & Technology, 156:104877, 2025.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Food recommendation towards personalized wellbeing.Trends in Food Science & Technology, 156:104877, 2025

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.804563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:c8192f0bfb4bc756705a095e2d37267d6519c34633ce6ec2cc40c760169155bd

Observation 760a09ca-7194-4ac9-8175-0c6f8a660621 · outbound

This paper cites Large scale visual food recognition.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(8):9932–9949.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Large scale visual food recognition.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(8):9932–9949

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.720127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:ee30a0160dc0823f274520550e69d37ebb1639f1b6b0996f7e3f2e3a4e03a841

Observation ba2339bd-0f9a-44fe-8cd1-35132eea04eb · outbound

This paper cites Instance-level few-shot learning with class hierarchy mining.IEEE Transactions on Image Processing, 32:2374–2385, 2023.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Instance-level few-shot learning with class hierarchy mining.IEEE Transactions on Image Processing, 32:2374–2385, 2023

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.731885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:5c030f0f21cb513c7998c769696d5bc4218286ac2b77e1f9788ae388a6ddfa8d

Observation ec300e6a-f8b0-47bc-abbb-3e228c2e1453 · outbound

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

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Learning transferable visual models from natural language supervision

Reference 12

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verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.713043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:6ef1f0d22d46677c445671dce307cc2411139381e5dda2ba6cb1dc8faef6e3aa

Observation 357c78c1-2237-413a-bb6f-645cf057a416 · outbound

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

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Learning to prompt for vision-language models.International Journal of Computer Vision, 130(9):2337–2348, 2022

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.703943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:fa48c872ebe6fb80b7a624abb1ea94822345cced73911088f90b10d3d0ffeea8

Observation b80f3659-15af-4c29-993e-2ad629acaaaf · outbound

This paper cites Conditional prompt learning for vision-language models.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Conditional prompt learning for vision-language models

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.808991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:79f80b18042032b48f6cf702ae476b46a16adf8930f2c8f47497b804ec3aa9b9

Observation c5b61138-780c-4961-93b4-9ed13c01ac5b · outbound

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

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Scaling up visual and vision-language representation learning with noisy text supervision

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:8511f42e02a315e5f33018385b713e72eac2ce1aa88881bd54d7d70672d586c9

Observation 39edc55c-b16c-496a-a4e8-a2a8d3518546 · outbound

This paper cites Blip: Bootstrapping language-image pre- training for unified vision-language understanding and generation.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Blip: Bootstrapping language-image pre- training for unified vision-language understanding and generation

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:dd6743464e30de79020ebc2d6761dd9509b30f0a90edb332fbb52e8a964f2de3

Observation 3be98d7b-a8cd-4b75-8772-11e8ff4d572d · outbound

This paper cites Effective conditioned and composed image retrieval combining clip-based features.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Effective conditioned and composed image retrieval combining clip-based features

Reference 17

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raw_fallback, observed 2026-07-08T14:25:02.729902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:5105494d2c81165f1832236499eab1d86fb15f50c7705795991006a999837b93

Observation dbb08f34-6117-49e2-8a5b-6b87f42b3ace · outbound

This paper cites Clip for all things zero-shot sketch-based image retrieval, fine-grained or not.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Clip for all things zero-shot sketch-based image retrieval, fine-grained or not

Reference 18

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raw_fallback, observed 2026-07-08T14:25:02.761072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:8632ea1795958affc148cd25cd76f7d4e2b7a1769ef84b8cc14603e77e25badb

Observation 35c1f510-3ba8-4218-8af8-e3c46500e141 · outbound

This paper cites Cris: Clip-driven referring image segmentation.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Cris: Clip-driven referring image segmentation

Reference 19

Resolution
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raw_fallback, observed 2026-07-08T14:25:02.763079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:7417b4358c80e290cf2069b41f11e3d7fe0745d37b732eea1351ffba7b7396ae

Observation ebc3f107-5f7b-4f43-9328-4c4bceb27e7d · outbound

This paper cites Image segmentation using text and image prompts.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Image segmentation using text and image prompts

Reference 20

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verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.693933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:595f0dfcf3e8d44c80e06c0433ea835595626629b8de3ad398efa1cfff765995

Observation 5af87730-fc17-4f9d-8d47-e5fb51277c6f · outbound

This paper cites an unresolved cited work.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-07-08T14:25:02.696427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:11433cc7afa8de60eb5a1fdd23f4bc670984fe6f790c7a23ee62ac01d7594c17

Observation 554e929e-f92c-4534-9c7d-5f60a82419cc · outbound

This paper cites Maple: Multi-modal prompt learning.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Maple: Multi-modal prompt learning

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.773208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:6a8bfd28b76b458ffdde809b63295744f44eea4d1359bd3c2b5aea7f13a2ce84

Observation 270522b3-e5ac-49e4-84ef-d31d12945800 · outbound

This paper cites Self-regulating prompts: Foundational model adaptation without forgetting.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Self-regulating prompts: Foundational model adaptation without forgetting

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.686924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:52da5cdf795028c3475afca59b7b5f5b8bb842815ad9a00b89e0bd19c1da4772

Observation 0a195ef6-56c2-471d-9a5c-6b837849538f · outbound

This paper cites Dgprompt: Dual-guidance prompts generation for vision-language models.Neural Networks, page 107472, 2025.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Dgprompt: Dual-guidance prompts generation for vision-language models.Neural Networks, page 107472, 2025

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.690988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:b9ad2c17795fe6e2963ab33d1b01db90d727fe5716a8c1cc61b09a23a01090ad

Observation 1214e3ef-99e2-416c-94e6-36fec492cc85 · outbound

This paper cites Prompt distribution learning.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Prompt distribution learning

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.770597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:60634dfe2b0d063a6c9b8cdf38dbf00ca34e77d48a8b9379fc9bd3d272e0b960

Observation 4dde492b-c5b0-4e74-be96-f7c94f65f08e · outbound

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

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Visual-language prompt tuning with knowledge- guided context optimization

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.711039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:58ab0d053681ebe2384cf69664b6b3313fdabfb5b4da46f90c0eb98b52d66123

Observation a8e48d72-6fcf-4e7f-bcfd-f40597b12b3c · outbound

This paper cites Tcp: Textual-based class-aware prompt tuning for visual-language model.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Tcp: Textual-based class-aware prompt tuning for visual-language model

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.747689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:5a726cf8bacafaaf42e18a360aa916d4d66664c3600d5da1e928c2e0cbf857aa

Observation a8113e8f-ea49-4745-899f-d6c2ec448aa4 · outbound

This paper cites Bayesian test-time adaptation for vision-language models.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Bayesian test-time adaptation for vision-language models

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.736706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:5e0c739f83a7bb30d53f479f0ab616a24c11daec8f61d663ef5c5f62643ecc01

Observation 846f8cc3-598c-4f7c-84c4-274d24a36295 · outbound

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

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition An image is worth 16x16 words: Transformers for image recognition at scale

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.775277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:1fe0e4c2d24747adfb160ed7b08b1e0772c6359918a5877d1f2d90f67facfb86

Observation 3c412cbb-1321-4ef8-a713-af04d478f521 · outbound

This paper cites Deep residual learning for image recognition.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Deep residual learning for image recognition

Reference 30

Resolution
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raw_fallback, observed 2026-07-08T14:25:02.777486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:c936c8a48ab530aba77a400c90278c42a83f0467b88253ed492d35be0f136b61

Observation ff4fd1c5-8ed6-4cce-91a5-7f9ad1a0216e · outbound

This paper cites Long-clip: Unlocking the long-text capability of clip.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Long-clip: Unlocking the long-text capability of clip

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.798454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:609e95193f06dcd9ab51fd86586050f50ad09fc6a0348df1ec142697004ed4c3

Observation 2deaf816-289c-471d-8307-5091649cbce7 · outbound

This paper cites Extensions of lipschitz mappings into a hilbert space.Contemporary mathematics, 26(189-206):1.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Extensions of lipschitz mappings into a hilbert space.Contemporary mathematics, 26(189-206):1

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.768099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:ba12cc94e0c44bd3fe3f0d94ddcd0cdfb22ff31ab9bda1695c583ad4df05f92c

Observation aaa8efd3-27d5-45b5-b5a4-75ab60e08c38 · outbound

This paper cites A short proof of the marchenko–pastur theorem.Comptes Rendus Mathematique, 354(3):319–322, 2016.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition A short proof of the marchenko–pastur theorem.Comptes Rendus Mathematique, 354(3):319–322, 2016

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.800648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:46aeeb806697bb8077189af2e3907ba95ef1e87bb9f6dfaa479a26c8ecdadc7a

Observation e5480c41-cef2-4463-8bca-9bae5d8e43e7 · outbound

This paper cites A new dataset of dog breed images and a benchmark for finegrained classification.Computational Visual Media, 6:477–487, 2020.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition A new dataset of dog breed images and a benchmark for finegrained classification.Computational Visual Media, 6:477–487, 2020

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.742468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:0b0fadc6e06f10bf37aeab33847131abf1916e79bbc7209b88aaf7ebae002e5b

Observation b239ff54-d106-4862-8476-b2975bd19fb5 · outbound

This paper cites Cats and dogs.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Cats and dogs

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.706123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:87a9e0283b20145806ae2f40c1d8786b52c5f2bb9e2767b222a05fca87a82d0b

Observation 4157ee8b-cafe-4175-97dc-03803059fbaf · outbound

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

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Automated flower classification over a large number of classes

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.750211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:8bff3381a6c8e0f5a56264c8f5b729b55534cf1c42191d08fb179deb871d4eee

Observation 338b57ee-4c07-49c7-b897-24a6ee23249d · outbound

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

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition 3d object representations for fine-grained categorization

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.788095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:a0b7ca247085aba06b265a44fc6434b41194823b88f1225a87179c306fa3dc8e

Observation 0a3fbc71-fbe6-4122-bdf4-7cef068129da · outbound

This paper cites Webly supervised fine-grained recognition: Benchmark datasets and an approach.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Webly supervised fine-grained recognition: Benchmark datasets and an approach

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.752440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:8481c1ab66110e0b127f32a525f149bafa37dc9891e85d80ad5739f6c1d33204

Observation 040dc5e9-876e-40d8-8ccb-dac6f68452be · outbound

This paper cites Novel dataset for fine-grained image categorization.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Novel dataset for fine-grained image categorization

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.714993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:9981b595818bddc8a8b8b2f31810769980783efb0c9defb28348d83f7097edf8

Observation e1048885-7b5b-48a8-90f5-a15f5332079d · outbound

This paper cites an unresolved cited work.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-07-08T14:25:02.722854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:358f1ded5f3541730337c178c0ca35f6e988819a8e88407c187d6847e81ceafe

Observation 7f7b42c4-4c04-498e-9499-b78ac6376642 · outbound

This paper cites Vegfru: A domain-specific dataset for fine-grained visual categorization.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Vegfru: A domain-specific dataset for fine-grained visual categorization

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.717846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:2f549fd70fa80b382c143bd774ea94aa5c211d7dba1fd35f05c5151fc6db18e4

Observation 4b900c35-f052-492b-885c-a9e2cbeb83a2 · outbound

This paper cites The caltech-ucsd birds-200-2011 dataset.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition The caltech-ucsd birds-200-2011 dataset

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.725340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:449452314c52fc97664d53b61f2ef051af3c3aae8ac75ea540f7930dc68026ab

Observation a5fd430f-d530-45c1-9cf3-48da24703349 · outbound

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

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Food-101–mining discriminative components with random forests

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.790757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:a18bae71a87f6dc2b277b4c34f60c981fac44925175f9c0ce3a6e276c2c8574b

Observation 14e37b16-97cf-4de7-8120-73d186426ce5 · outbound

This paper cites Deep-based ingredient recognition for cooking recipe retrieval.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Deep-based ingredient recognition for cooking recipe retrieval

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.782345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:919bcdd3adc5dc5a0ccdb8860fb9df911ec089906c1303a76329268a3be75f15

Observation 34169aeb-c088-4d19-8626-52462a2e8e79 · outbound

This paper cites Ingredient-guided cascaded multi-attention network for food recognition.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Ingredient-guided cascaded multi-attention network for food recognition

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.727864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:2732777341b9bf6d413c1ce66678bc2ae42cd3c9cd04c7b2f78ecd3c64d73ff2

Observation f382d94b-2ba0-40bd-9d7e-ba71bf8a0ef8 · outbound

This paper cites Isia food-500: A dataset for large-scale food recognition via stacked global-local attention network.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Isia food-500: A dataset for large-scale food recognition via stacked global-local attention network

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.779786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:6bf46c9c56af07c8e66e5444fb21638b5e181e91f226f08d1345046250e6dff6

Observation 189848be-6a95-4b27-b490-9dde6306de03 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Fine-Grained Visual Classification of Aircraft

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-07-08T14:25:02.446980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:ea76713efb066112fc3a90b1f03dc00bf39938d126ea9214990a8e0799a39bb2

Observation f3ebdea0-49b9-4a08-9e4f-b80ee2da92f2 · outbound

This paper cites Learning to prompt with text only supervision for vision-language models.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Learning to prompt with text only supervision for vision-language models

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.793349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:955d25370a7f3b5a4e1f60ab3029a65a70db0fe726ecccd8960e51883cba9e75

Observation d60c7baa-4c33-4239-9e11-cb9e5b536ba2 · outbound

This paper cites Advancing textual prompt learning with anchored attributes.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Advancing textual prompt learning with anchored attributes

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.806514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:08f51570c138655776aec6b12ac6dabf2d07129004b24584c63cdcbdb49c2d41

Observation 5a6b2106-d663-431a-aaaa-5a588a737876 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.795986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:443bcef7d20e9a042f4420d74053dcd7bcfb560032bc8b7c1ecb03a968609dd9

Observation bb278ed3-4a3d-48d1-9d98-7ee7668426c2 · outbound

This paper cites Visual prompt tuning.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Visual prompt tuning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.802529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:caea28bde1a1256ceb9f68f1adb36bdca286508b0c3f2a2983bc30e628f11909

Observation 02ae27a1-5690-42fc-a5e1-298765e2267c · outbound

This paper cites Dualprompt: Complementary prompting for rehearsal-free continual learning.

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition Dualprompt: Complementary prompting for rehearsal-free continual learning

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T14:25:02.785403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-08T14:18:26.034732Z digest=sha256:20753ed98df5942103d18924039937c0b8a7866ad6b7da1942a124ff5a001045

Pith citing papers

No inbound Pith citation observations are available.