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Paper Citation Record · LEDGER

In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.04961.

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

pith.paper-citation-record.v1
2408.04961 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:02:00.883564Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T13:53:33.946271Z

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 c8b36e7f-adc5-4911-9e66-11a38ed94a0a · inbound

Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation cites this paper.

Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T21:02:00.883564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:02:00.883564Z digest=sha256:20c60281b03e64bd033d6f7f54bb70fdf0a81377336c5f81bd97f5b0b06bc024

Observation 82495263-bf02-403d-aded-aefa128c51e0 · inbound

ResCLIP: Residual Attention for Training-free Dense Vision-language Inference cites this paper.

ResCLIP: Residual Attention for Training-free Dense Vision-language Inference In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-12T13:53:33.969268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-12T13:53:33.113821Z digest=sha256:8693560ca7eca5b9e9e06e488275ca8f405bda9aa18f151483f1cb113c35c0f3