Pith. sign in

Paper Citation Record · LEDGER

5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2408.08345.

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

pith.paper-citation-record.v1
2408.08345 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:31:38.174949Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T10:37:15.121693Z

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 414801b4-1b33-4a8e-aa52-01cc86835035 · inbound

Parameter-Efficient Fine-Tuning for Foundation Models cites this paper.

Parameter-Efficient Fine-Tuning for Foundation Models 5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks

Reference 198

Resolution
unresolved
no resolver link, observed 2026-08-10T15:38:03.464856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:38:03.464856Z digest=sha256:eac584e55c4c24b77d480984a3132a999a12ded7edf62ea9d01bcf1fa6ad636f

Observation d2f565ab-0eca-4f0f-b8ce-fc68d1e9d696 · inbound

SAM-Based Building Change Detection with Distribution-Aware Fourier Adaptation and Edge-Constrained Warping cites this paper.

SAM-Based Building Change Detection with Distribution-Aware Fourier Adaptation and Edge-Constrained Warping 5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-16T12:31:38.174949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:31:38.174949Z digest=sha256:2d01811547e0826573480b2933b43be496f05fb6d62ef4744b16c92adf0deb78

Observation ea0054bc-c713-4749-a73a-4d038a3b65ab · inbound

DAPE: Dual-Stage Parameter-Efficient Fine-Tuning for Consistent Video Editing with Diffusion Models cites this paper.

DAPE: Dual-Stage Parameter-Efficient Fine-Tuning for Consistent Video Editing with Diffusion Models 5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-15T22:30:42.615841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:30:42.615841Z digest=sha256:0b54497e8ced9d81ed3466f3fd211e2e276ac7df887af2a89785b3cc72324142

Observation f853e7d2-ded4-45b9-bc21-be75e1a55a5f · inbound

GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation cites this paper.

GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation 5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T11:17:59.404572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:17:59.404572Z digest=sha256:7cdf91b6998ab232b2613a2b71a3de552f96e0cc05cc62ad2a0f272fa454ff6f

Observation a74ac488-29a3-4207-8431-7f4cf383607d · inbound

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis cites this paper.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis 5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-19T10:37:15.123356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-19T10:34:28.875334Z digest=sha256:339aed7c12fbdb6f00749591457b792079a751d3f754460af7952c5dd8298ad3