Paper Citation Record · LEDGER

Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2503.02581.

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

pith.paper-citation-record.v1
2503.02581 v2

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 2026-08-20T06:33:59.587034+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:10:44.902798Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:17:54.162887Z

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 5fcf5c26-9c72-4f0e-ab6f-06168516796a · inbound

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation cites this paper.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T12:32:24.851653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b815fa3-55c0-4008-a977-d1d92c47aac7 · inbound

Segment Any RGB-Thermal Model with Language-aided Distillation cites this paper.

Segment Any RGB-Thermal Model with Language-aided Distillation Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-16T04:10:44.902798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55ea5e7c-7e37-4f68-8f5a-2591a07048d1 · inbound

Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization cites this paper.

Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T22:44:46.293624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc8c2481-e51c-412e-ac7e-b27307c3b3ee · inbound

RMMSS: Towards Advanced Robust Multi-Modal Semantic Segmentation with Hybrid Prototype Distillation and Feature Selection cites this paper.

RMMSS: Towards Advanced Robust Multi-Modal Semantic Segmentation with Hybrid Prototype Distillation and Feature Selection Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T20:30:57.853154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 385a25b5-c5b0-41fe-bbb8-94eced14162c · inbound

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation cites this paper.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:30.697183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85c2180f-2b79-46a1-8897-ba83e26bbc90 · inbound

BiXFormer: A Robust Framework for Maximizing Modality Effectiveness in Multi-Modal Semantic Segmentation cites this paper.

BiXFormer: A Robust Framework for Maximizing Modality Effectiveness in Multi-Modal Semantic Segmentation Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:00.526326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0523980e-47e1-4ab9-847e-56598d3eed4c · inbound

Partial CLIP is Enough: Chimera-Seg for Zero-shot Semantic Segmentation cites this paper.

Partial CLIP is Enough: Chimera-Seg for Zero-shot Semantic Segmentation Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:17:54.171444Z

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.