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Paper Citation Record · LEDGER

C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2403.14119.

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

pith.paper-citation-record.v1
2403.14119 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:31:23.615948Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T22:44:01.410628Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 75a2b736-9166-4320-a545-def1890bf03d · inbound

LoRA-TTT: Low-Rank Test-Time Training for Vision-Language Models cites this paper.

LoRA-TTT: Low-Rank Test-Time Training for Vision-Language Models C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-09T13:31:23.615948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:31:23.615948Z digest=sha256:a46e5c142342834e2837b28b5e0fcc608823401ddb881c856150f4a8e88d96e3

Observation a63adae7-2697-41d5-b8ca-70c8752b2ccf · inbound

ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization cites this paper.

ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T05:14:45.017306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:14:45.017306Z digest=sha256:96d9a4b94b409b871b019633d2c23cdb7ee676e35df545b0430c11d1757b9881

Observation 6ac0b187-647e-46e8-b655-194cd86c9b57 · inbound

Generalizing vision-language models to novel domains: A comprehensive survey cites this paper.

Generalizing vision-language models to novel domains: A comprehensive survey C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 124

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:48.615527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:20:48.615527Z digest=sha256:eaa5676f7fa6ccbcebd97b14663ba188a7d0cad1e3ba13cfa37c9300282d4f6a

Observation ebb8c3d3-a1fc-47a2-8eda-d5e41a93b1cb · inbound

Free on the Fly: Enhancing Flexibility in Test-Time Adaptation with Online EM cites this paper.

Free on the Fly: Enhancing Flexibility in Test-Time Adaptation with Online EM C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T18:56:35.094314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:56:35.094314Z digest=sha256:6774a4d4e1d6f8e8d36bf0d41101b488cab1216c7a5386f7fc0f9353b0927c6b

Observation 200ee217-6049-461d-97c3-20ac5323b43e · inbound

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text cites this paper.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T10:10:57.611080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:10:57.611080Z digest=sha256:2ed9a226276a6e9cea5d83d85caf4321a0332854021cc67c7502991e971f921a

Observation 2e942e99-aea2-4464-acd8-0b8b17909cda · inbound

Multi-Cache Enhanced Prototype Learning for Test-Time Generalization of Vision-Language Models cites this paper.

Multi-Cache Enhanced Prototype Learning for Test-Time Generalization of Vision-Language Models C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-06T05:46:32.255963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:46:32.255963Z digest=sha256:3b4cf63d07a1c49b2d6816e492c81cdb67e477a0164c986135ed2e1bec270162

Observation fa6c2eb5-7d1c-4baa-a6c3-02c826cf6337 · inbound

Measurement Plasticity: Sensor-Level Adaptation for Vision-Language Models cites this paper.

Measurement Plasticity: Sensor-Level Adaptation for Vision-Language Models C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-03T16:41:31.842583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:41:31.842583Z digest=sha256:0598d5de7d6c644186bfd307464cce2d0e671ce0c216732dd1a7a6f68a5f95ba

Observation 23d0bd22-ed79-47ba-9210-38acfef8df9b · inbound

Learning Inference Concurrency in DynamicGate MLP Structural and Mathematical Justification cites this paper.

Learning Inference Concurrency in DynamicGate MLP Structural and Mathematical Justification C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-10T14:20:30.149013Z

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=2026-05-10T14:18:24.015399Z digest=sha256:d6e0a6d31f96ebe89682fde469ee633c31ff3a14ebcee083e50564faf280d9ca

Observation ff0c1d7e-2a00-4cd0-bcfb-a25e739f6598 · inbound

Seeking Consensus: Geometric-Semantic On-the-Fly Recalibration for Open-Vocabulary Remote Sensing Semantic Segmentation cites this paper.

Seeking Consensus: Geometric-Semantic On-the-Fly Recalibration for Open-Vocabulary Remote Sensing Semantic Segmentation C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:46:26.706146Z

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=2026-05-07T13:46:58.151230Z digest=sha256:60dda5975915e22d3507dd8f1d448ebfb26a2e941bfcbdaa25fc7d6b805338ed

Observation 3bcdf39f-1618-4bd3-9f97-ef5a261c12d5 · inbound

Closed-Loop Bidirectional Prompting for Adversarial Robustness of Vision Language Models cites this paper.

Closed-Loop Bidirectional Prompting for Adversarial Robustness of Vision Language Models C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:44:01.412074Z

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=2026-06-29T22:40:26.803098Z digest=sha256:5aa38624285f9c26beeeea8af6556784fcd3874ddffe3b0d1fa1d304c928bd62