Paper Citation Record · LEDGER

Efficient Test-Time Prompt Tuning for Vision-Language Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2408.05775.

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

pith.paper-citation-record.v1
2408.05775 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:46:32.312024Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T21:31:52.173688Z

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 4aaabf6c-4248-4f81-8be1-6f8ea632a24b · 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 Efficient Test-Time Prompt Tuning for Vision-Language Models

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T05:46:32.312024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb154edf-ddc6-4ac1-b02b-c7e1d3ebfe1a · inbound

Adapting Vision-Language Models Without Labels: A Comprehensive Survey cites this paper.

Adapting Vision-Language Models Without Labels: A Comprehensive Survey Efficient Test-Time Prompt Tuning for Vision-Language Models

Reference 154

Resolution: unresolved; no resolver link, observed 2026-08-05T23:17:06.962571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae1a233a-76b0-4f27-baf7-e907078da5bf · inbound

Clustering-based aggregate value regression cites this paper.

Clustering-based aggregate value regression Efficient Test-Time Prompt Tuning for Vision-Language Models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-05T17:52:18.399067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eee1ec8f-ec14-487b-bf47-f6ab98aad07e · inbound

Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment cites this paper.

Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment Efficient Test-Time Prompt Tuning for Vision-Language Models

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-18T21:31:52.177429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 709f75db-4cb7-449f-bfb0-935a8e449a20 · inbound

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

Learning Inference Concurrency in DynamicGate MLP Structural and Mathematical Justification Efficient Test-Time Prompt Tuning for Vision-Language Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:20:30.159217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cda51fc6-5124-4c65-a9fa-560c0ae9441e · inbound

Improving Calibration in Test-Time Prompt Tuning for Vision-Language Models via Data-Free Flatness-Aware Prompt Pretraining cites this paper.

Improving Calibration in Test-Time Prompt Tuning for Vision-Language Models via Data-Free Flatness-Aware Prompt Pretraining Efficient Test-Time Prompt Tuning for Vision-Language Models

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:31:29.059802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 61f157e6-e6d3-4fe4-b6fc-60edb040f7d0 · inbound

VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding cites this paper.

VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding Efficient Test-Time Prompt Tuning for Vision-Language Models

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-02T00:44:49.808035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.