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Paper Citation Record · LEDGER

Q-GroundCAM: Quantifying Grounding in Vision Language Models via GradCAM

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.19128.

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

pith.paper-citation-record.v1
2404.19128 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T16:20:19.874172Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 7af040c9-0487-4b28-87e5-0854081b4c33 · inbound

Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval cites this paper.

Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval Q-GroundCAM: Quantifying Grounding in Vision Language Models via GradCAM

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-11T16:32:55.757864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T16:32:55.757864Z digest=sha256:70e86bc985df699c834d21eacf44ec8b9599221c03b646bb6d1e1248e9975340

Observation d6f69e71-bdc3-4e4c-be96-b8a33365b224 · inbound

Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval cites this paper.

Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval Q-GroundCAM: Quantifying Grounding in Vision Language Models via GradCAM

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-14T16:20:19.874172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T16:20:19.874172Z digest=sha256:88985918e8e15318b4e66576066f47516e98f4bdbf3bbd45477de18c27552a2f