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Paper Citation Record · LEDGER

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

As of 23 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 2026-08-23T06:30:58.430688+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.

source=pdf_text observed=2026-08-12T12:32:24.851653Z digest=sha256:861864557280f4b779e1a393fb02f6856678a856f41cfacb60972b0a7db26dfd

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.

source=pdf_text observed=2026-08-16T04:10:44.902798Z digest=sha256:112a1b2eb5afb029bb385c7715e0de99754ada737eed0511e586199e1b3ba4d5

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.

source=pdf_text observed=2026-08-15T22:44:46.293624Z digest=sha256:f6c1391e48729b743bfcf681a1f982298e89e10bb2935ebb5e0cc945cc0c27e4

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.

source=arxiv_source observed=2026-08-15T20:30:57.853154Z digest=sha256:7d149f99372b1d282bb80179f8b3e47df1f29c7374386d781819ded68185cfb0

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.

source=pdf_text observed=2026-08-07T15:43:30.697183Z digest=sha256:a3b38a53f411f8d3e5b1ca4f24f84dd59a06e190278ef6092456c505667b3e44

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.

source=pdf_text observed=2026-08-07T11:04:00.526326Z digest=sha256:9aa51846effba5442920d48e79d47cd5691c0be5af5cbc2bd43a890654f70991

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T22:17:53.873542Z digest=sha256:c212eb4088c00f52911d151992511ab4e2f912eeeeb50f3215af8212a03012d3