Paper Citation Record · LEDGER

Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2305.05803.

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

pith.paper-citation-record.v1
2305.05803 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:26:01.313696Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T11:13:02.894545Z

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 62a6b45a-7b5e-47a4-a76a-66b1245355b0 · inbound

SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation cites this paper.

SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T17:26:01.313696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dddf379a-f1db-4f26-a41a-3b486c0bf65c · inbound

Annotation-Efficient Task Guidance for Medical Segment Anything cites this paper.

Annotation-Efficient Task Guidance for Medical Segment Anything Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:54.229450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ab04993-ecfa-46b3-871f-af0ef73acea1 · inbound

SAM-guided Pseudo Label Enhancement for Multi-modal 3D Semantic Segmentation cites this paper.

SAM-guided Pseudo Label Enhancement for Multi-modal 3D Semantic Segmentation Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T17:11:06.811250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3408d9c7-c2dc-4feb-963a-ea1fd1904aa7 · inbound

SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement cites this paper.

SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T14:29:00.483251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30e6229b-707f-4382-811a-ea23b7f3db58 · inbound

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models cites this paper.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T11:01:44.990598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 279d5f37-ea74-49f7-8507-b45140b68e69 · inbound

AVA-Bench: Atomic Visual Ability Benchmark for Vision Foundation Models cites this paper.

AVA-Bench: Atomic Visual Ability Benchmark for Vision Foundation Models Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-19T11:13:02.896114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e2344a0e-1e0f-4c12-9428-ece971814fd2 · inbound

Know Your Attention Maps: Class-specific Token Masking for Weakly Supervised Semantic Segmentation cites this paper.

Know Your Attention Maps: Class-specific Token Masking for Weakly Supervised Semantic Segmentation Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T18:58:37.326625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c07172a2-ccc4-4f84-bc87-5543cbcecda0 · inbound

Emerging Trends in Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation with Image-Level Supervision cites this paper.

Emerging Trends in Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation with Image-Level Supervision Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T12:39:20.728027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 199c55af-8dfd-4215-8585-efb364cb37ea · inbound

Mitigating Spurious Correlations in Weakly Supervised Semantic Segmentation via Cross-architecture Consistency Regularization cites this paper.

Mitigating Spurious Correlations in Weakly Supervised Semantic Segmentation via Cross-architecture Consistency Regularization Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T12:21:25.553776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cf61c8e-5ae3-4888-be82-4197a485db1f · inbound

WS$^2$: Weakly Supervised Segmentation using Before-After Supervision in Waste Sorting cites this paper.

WS$^2$: Weakly Supervised Segmentation using Before-After Supervision in Waste Sorting Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T23:33:20.006374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c98bc407-db4c-4eeb-b927-be5fb0b79206 · inbound

Top-P Sensor Selection for Target Localization cites this paper.

Top-P Sensor Selection for Target Localization Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-13T08:43:51.830129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c600864-aaf2-4bfc-8f0f-470358b4a5d2 · inbound

Exploring SAM Supervision for Fine-Grained UAV Target Segmentation under Data Scarcity cites this paper.

Exploring SAM Supervision for Fine-Grained UAV Target Segmentation under Data Scarcity Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-12T00:11:33.168015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.