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Paper Citation Record · LEDGER

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin

As of 17 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2505.02056.

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

pith.paper-citation-record.v1
2505.02056 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:09:12.416404Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

19 of 19 outbound references displayed

  • verified exact1
  • verified fuzzy6
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c135a6b0-a19f-499c-a9fa-fd1384c913e6 · outbound

This paper cites R., Sharma, L., and Babu, R.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin R., Sharma, L., and Babu, R

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-16T04:09:12.936291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation d775cb6f-51ba-4936-8b50-fd651ee989e3 · outbound

This paper cites an unresolved cited work.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-16T04:09:12.855756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:09:12.412642Z digest=sha256:09005649eb8058c61ef6bc7f756631fd81c7ebdc9c3441975a2cb35370d0d675

Observation c3bc825d-a8ce-444f-a518-0d8a43eb951f · outbound

This paper cites Gu, X., Lin, T., Kuo, W., and Cui, Y.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Gu, X., Lin, T., Kuo, W., and Cui, Y

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:12.358395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.358395Z digest=sha256:6122be9a0e9845393c8b23c564d0141ce1f2601dbb2e9c97b961dc0c46c24405

Observation bbef0d2b-425e-4a69-9bf0-19aea711a5ee · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Fine-Grained Visual Classification of Aircraft

Reference 9

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unresolved
no resolver link, observed 2026-08-16T04:09:12.376361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.376361Z digest=sha256:892ac1b58e12da8260dd389ddf2e5a756ba1d83711cfc64b0bfc30b6f1d73de7

Observation abcb659a-a7f7-4619-a5a7-5da956c0844e · outbound

This paper cites Kim, J., Ku, Y ., Kim, J., Cha, J., and Baek, S.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Kim, J., Ku, Y ., Kim, J., Cha, J., and Baek, S

Reference 10

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unresolved
no resolver link, observed 2026-08-16T04:09:12.371750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.371750Z digest=sha256:af40e709d4bdb69d6abb772973f5ff0497496d1ddce1aee9741f742a09d3ca93

Observation cab43c5c-935d-450e-839a-11be4c3913e5 · outbound

This paper cites an unresolved cited work.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Unresolved cited work

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:12.388167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.388167Z digest=sha256:8b17656c349c9e2778993d1b386bf8387d734e9fd1ecc1b0e3d8bf67fca0662d

Observation 536642f2-4429-4453-a60f-2529d29c7a0e · outbound

This paper cites Florence: A New Foundation Model for Computer Vision.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Florence: A New Foundation Model for Computer Vision

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:12.392222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.392222Z digest=sha256:738b4d189e7e00e5682df135ff1c83bb94066d4bc4c27545b63a907592dc1ec9

Observation 4f0bb4d4-8c45-4fd6-874b-f3d6569f2a3b · outbound

This paper cites Learning to Prompt for Vision-Language Models.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Learning to Prompt for Vision-Language Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:12.400739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.400739Z digest=sha256:eccfc1d73d7c7137cd184ae43f1f933e7f990b3c68a759b9791f2b0d1891b2fb

Observation 0418c82b-04de-4fd1-87de-3b2f9f899096 · outbound

This paper cites C., and Liu, Z.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin C., and Liu, Z

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:09:12.869367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:09:12.404799Z digest=sha256:eacfb25cc05f031c28be00336206c7d7665440b244d3418f1cb7461d194ead01

Observation 46f5c891-a6c2-41cd-b729-cfc7ba8a5af2 · outbound

This paper cites Handling Imbalanced Pseudolabels for VLMs with Concept Alignment and Confusion-Aware Calibrated Margin.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Handling Imbalanced Pseudolabels for VLMs with Concept Alignment and Confusion-Aware Calibrated Margin

Reference 17

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unresolved
no resolver link, observed 2026-08-16T04:09:12.408625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.408625Z digest=sha256:cd3c1ef141167fc886f2143c88f48be72dc9612287384615b4532cba91529c6d

Observation a7e69607-d068-40c4-9bfc-4c934a4f720d · outbound

This paper cites Comparison Methods We briefly introduce the baselines in this section.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Comparison Methods We briefly introduce the baselines in this section

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:09:12.841739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:09:12.416404Z digest=sha256:9994ec24ad24a379429f433b57fa39083d0820557a52eca1421446a2368f09c8

Observation 604c34ab-db14-476d-b67e-17784fb4dd48 · outbound

This paper cites Marvelovd: Marrying object recognition and vision-language models for robust open-vocabulary object detection.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Marvelovd: Marrying object recognition and vision-language models for robust open-vocabulary object detection

Reference 2011

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:09:12.883458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:09:12.384369Z digest=sha256:bfa83b1c5123a3c7c9a82f8965d9830a24568f124ec09aec7b53f77c4af2be86

Observation 58119c50-7937-4fa5-b4d2-07ef817177f3 · outbound

This paper cites CLIP-Adapter: Better Vision-Language Models with Feature Adapters.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin CLIP-Adapter: Better Vision-Language Models with Feature Adapters

Reference 2014

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unresolved
no resolver link, observed 2026-08-16T04:09:12.353691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.353691Z digest=sha256:02731f6a38eed0bbe5f1fcfee28551060c9e3ab843663700dc10aef0181b24e9

Observation 243366ba-e873-4628-9a46-9db37ec1dae7 · outbound

This paper cites Describing textures in the wild.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Describing textures in the wild

Reference 2017

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:09:12.922037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:09:12.348501Z digest=sha256:9544146c87153d070eacb021fe4a5bd9482dc8204008c9c1aed49a122a40413d

Observation 530e4183-ba3e-4995-a3a1-465d5ecfbb05 · outbound

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

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin The caltech-ucsd birds-200-2011 dataset

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:12.380684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.380684Z digest=sha256:675f82bf87c4df51b95c7ade347d637b8f3f857bf7e91159b81bc93bab152ee2

Observation 2266a9f3-00e5-40e7-bf73-d955c0543e79 · outbound

This paper cites Unsupervised Prompt Learning for Vision-Language Models.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Unsupervised Prompt Learning for Vision-Language Models

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:12.363338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.363338Z digest=sha256:b9fa0542a0efe1852309d8654e3956ec485319103e2c956724f75c878a9afaf8

Observation 7123ad45-4d58-4392-a778-c9aa7356ea6a · outbound

This paper cites Unified Vision and Language Prompt Learning.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin Unified Vision and Language Prompt Learning

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:12.396220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:09:12.396220Z digest=sha256:2ddd5636bc6e1dca58273d197aab8071db5ed4e47b3129480295a714852762c8

Observation 2982255e-d846-4caf-b792-e2ef837301f6 · outbound

This paper cites U., Rasheed, H.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin U., Rasheed, H

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:09:12.907668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:09:12.367696Z digest=sha256:b53c6adfc1e685325509948c07dad7e59e6cb09429964f1fadcd15520d380e48

Observation efb836b1-3228-4e42-94cd-0b1bf3c3f959 · outbound

This paper cites 2024.02258.

Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin 2024.02258

Reference 2024

Resolution
verified exact
raw_fallback, observed 2026-08-16T04:09:12.826756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:09:12.344175Z digest=sha256:ce2f4395920a773a567d27cb69874aa51bae0e4727c695d092ab001ca530c407

Pith citing papers

No inbound Pith citation observations are available.