Paper Citation Record · LEDGER

Training-Free Semantic Segmentation via LLM-Supervision

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2404.00701.

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

pith.paper-citation-record.v1
2404.00701 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 2026-08-22T06:32:14.747728+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:39:14.648989Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T21:43:00.175224Z

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 8bb18308-13aa-4590-b3e6-469160fad51a · inbound

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

Adapting Vision-Language Models Without Labels: A Comprehensive Survey Training-Free Semantic Segmentation via LLM-Supervision

Reference 103

Resolution: unresolved; no resolver link, observed 2026-08-05T23:17:06.737689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ebbd834-0513-4f36-a63e-7abfcabe6308 · inbound

SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation cites this paper.

SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation Training-Free Semantic Segmentation via LLM-Supervision

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T23:01:00.114920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53c69dd0-5a1b-4817-b0cd-4dd27368b0f4 · inbound

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation cites this paper.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Training-Free Semantic Segmentation via LLM-Supervision

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T22:26:53.219984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33b8cd70-e4c8-4af3-8bdd-a0a6ccfad771 · inbound

VIP: Visual-guided Prompt Evolution for Efficient Dense Vision-Language Inference cites this paper.

VIP: Visual-guided Prompt Evolution for Efficient Dense Vision-Language Inference Training-Free Semantic Segmentation via LLM-Supervision

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:27:29.170597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation db343aad-b31a-4437-9c21-df7b141b40ba · inbound

VIP: Visual-guided Prompt Evolution for Efficient Dense Vision-Language Inference cites this paper.

VIP: Visual-guided Prompt Evolution for Efficient Dense Vision-Language Inference Training-Free Semantic Segmentation via LLM-Supervision

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:43:00.178084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f144f5d2-99c7-4ca1-bf53-957a77dcf7df · inbound

Perceptual Anchoring: Prototype-Guided Text Calibration for Training-free Open-Vocabulary Semantic Segmentation cites this paper.

Perceptual Anchoring: Prototype-Guided Text Calibration for Training-free Open-Vocabulary Semantic Segmentation Training-Free Semantic Segmentation via LLM-Supervision

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T04:27:17.879688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5663c27c-1b67-43ce-86a5-5ff44ba34642 · inbound

Perceptual Anchoring: Prototype-Guided Text Calibration for Training-free Open-Vocabulary Semantic Segmentation cites this paper.

Perceptual Anchoring: Prototype-Guided Text Calibration for Training-free Open-Vocabulary Semantic Segmentation Training-Free Semantic Segmentation via LLM-Supervision

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T00:39:14.648989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.