Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2505.06635.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:32:24.838004Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T22:17:54.418808Z
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 454cc9cf-1b17-4005-8136-0d1836f1f01c · inbound
Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation cites this paper.
Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:32:24.838004Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e45e6ac9-3e93-41c6-abc1-da0260c12089 · inbound
EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation cites this paper.
EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:43:30.492138Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9eaf1cb3-d80c-4765-8697-b2d87d7cbae4 · inbound
MLLMs are Deeply Affected by Modality Bias cites this paper.
MLLMs are Deeply Affected by Modality Bias Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:30:22.147211Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7243d09-eeae-4c5f-a155-1e5b031e0ed9 · 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 Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:04:00.581807Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e1c273b-7338-45da-88d4-416ccc4dbf91 · 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 Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T22:17:54.427094Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.