Paper Citation Record · LEDGER

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation

As of 23 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 7 inbound Pith citation observations for arXiv:2411.17141.

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

pith.paper-citation-record.v1
2411.17141 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:32:24.931874Z

measured 44 of 44 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 2026-08-16T04:10:44.883691Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:17:54.890616Z

Reference resolution

37 of 37 outbound references displayed

verified exact2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 260dec4f-839f-451c-8fb5-24f36655ce02 · outbound

This paper cites 360sfuda++: Towards source-free uda for panoramic segmentation by learning reliable category prototypes,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation 360sfuda++: Towards source-free uda for panoramic segmentation by learning reliable category prototypes,

Reference 1

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Observation c0f3adbb-80fc-43f4-94a5-208d359bfad2 · outbound

This paper cites OmniBind: Teach to Build Unequal-Scale Modality Interaction for Omni-Bind of All.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation OmniBind: Teach to Build Unequal-Scale Modality Interaction for Omni-Bind of All

Reference 2

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Observation f231be51-8b93-4d5e-978f-c193654f4819 · outbound

This paper cites Transformer-cnn cohort: Semi-supervised semantic segmentation by the best of both students,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Transformer-cnn cohort: Semi-supervised semantic segmentation by the best of both students,

Reference 3

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Observation 208590aa-0d29-4c09-8e11-a61545038cf5 · outbound

This paper cites Unibind: Llm-augmented unified and balanced representation space to bind them all,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Unibind: Llm-augmented unified and balanced representation space to bind them all,

Reference 4

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Observation 53180fda-7874-4b96-b196-5700b71621d0 · outbound

This paper cites Cmx: Cross-modal fusion for rgb- x semantic segmentation with transformers,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Cmx: Cross-modal fusion for rgb- x semantic segmentation with transformers,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:32:25.446635Z

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Observation cfd7b253-7b03-42d4-ab2f-ffacdeabe297 · outbound

This paper cites Learning modality-agnostic representation for semantic segmentation from any modalities,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Learning modality-agnostic representation for semantic segmentation from any modalities,

Reference 6

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Observation fb6d2a9d-68b3-42cc-aa72-7f0f1fb13f8b · outbound

This paper cites Centering the value of every modality: Towards efficient and resilient modality-agnostic semantic segmentation,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Centering the value of every modality: Towards efficient and resilient modality-agnostic semantic segmentation,

Reference 7

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Observation 011ccbe1-81b2-4e2f-ad3c-ab6e57939131 · outbound

This paper cites Fourier prompt tuning for modality-incomplete scene segmentation,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Fourier prompt tuning for modality-incomplete scene segmentation,

Reference 8

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Observation 1663f917-9d54-4329-9877-685a7d4928ca · outbound

This paper cites Eventbind: Learning a unified representation to bind them all for event-based open-world understanding,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Eventbind: Learning a unified representation to bind them all for event-based open-world understanding,

Reference 9

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Observation 32e991d1-1fae-4f2b-a4d1-925ab39ea800 · outbound

This paper cites Eventdance: Unsupervised source-free cross-modal adaptation for event-based object recognition,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Eventdance: Unsupervised source-free cross-modal adaptation for event-based object recognition,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:32:25.373951Z

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Observation 249dc1fb-3cb5-4a42-88ec-99a43100b5cb · outbound

This paper cites Mseg3d: Multi-modal 3d semantic segmentation for autonomous driving,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Mseg3d: Multi-modal 3d semantic segmentation for autonomous driving,

Reference 11

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Observation c59b43fb-085a-4c95-b1b1-59cda8d7a371 · outbound

This paper cites MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation

Reference 12

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This paper cites Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness

Reference 13

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Observation 0870e5c7-e46c-4b89-b4bc-4eadc3e9c561 · outbound

This paper cites Both style and distortion matter: Dual- path unsupervised domain adaptation for panoramic semantic segmentation,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Both style and distortion matter: Dual- path unsupervised domain adaptation for panoramic semantic segmentation,

Reference 14

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Observation 8d7e3d8a-529b-453f-8de2-40e6e29a8b02 · outbound

This paper cites Semantics distortion and style matter: Towards source-free uda for panoramic segmentation,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Semantics distortion and style matter: Towards source-free uda for panoramic segmentation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:32:25.337056Z

Source-reported events for the cited work

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Observation 454cc9cf-1b17-4005-8136-0d1836f1f01c · outbound

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

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

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Observation 185e2ddc-a7f2-473d-a48a-234970688f36 · outbound

This paper cites De- livering arbitrary-modal semantic segmentation,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation De- livering arbitrary-modal semantic segmentation,

Reference 17

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Observation 3b910e6f-02a1-4bd0-8a20-3592cc7fc439 · outbound

This paper cites Muses: The multi-sensor semantic perception dataset for driving under uncertainty,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Muses: The multi-sensor semantic perception dataset for driving under uncertainty,

Reference 18

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Observation 5fcf5c26-9c72-4f0e-ab6f-06168516796a · outbound

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

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

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Observation ef61cb6b-32e6-457d-a3f1-72b4086f2ab9 · outbound

This paper cites Hrfuser: A multi-resolution sensor fusion architecture for 2d object detection,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Hrfuser: A multi-resolution sensor fusion architecture for 2d object detection,

Reference 20

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Observation a508a839-7d30-44f8-bc6b-c296f4c1cc8d · outbound

This paper cites Mmanet: Margin-aware distillation and modality-aware regular- ization for incomplete multimodal learning,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Mmanet: Margin-aware distillation and modality-aware regular- ization for incomplete multimodal learning,

Reference 21

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Observation d521160a-5337-491d-9567-155c12ad3855 · outbound

This paper cites Abmdrnet: Adaptive-weighted bi- directional modality difference reduction network for rgb-t semantic segmentation,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Abmdrnet: Adaptive-weighted bi- directional modality difference reduction network for rgb-t semantic segmentation,

Reference 22

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Observation 9e36c7ab-695a-45fd-96ee-831824b668a6 · outbound

This paper cites Bev-guided multi-modality fusion for driving perception,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Bev-guided multi-modality fusion for driving perception,

Reference 23

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Observation 9d5a4892-b5ae-45c5-bf26-d19bf326cea4 · outbound

This paper cites Multimodal token fusion for vision transformers,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Multimodal token fusion for vision transformers,

Reference 24

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Observation bf2299d7-8fc1-4d18-8084-178dea535ce7 · outbound

This paper cites Spatial information guided convolution for real-time rgbd semantic segmentation,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Spatial information guided convolution for real-time rgbd semantic segmentation,

Reference 25

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Observation 38d1cdd8-206b-49c0-be93-95896b167460 · outbound

This paper cites Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts

Reference 26

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This paper cites Critical learning periods for multisensory integration in deep networks,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Critical learning periods for multisensory integration in deep networks,

Reference 27

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Observation 3e7dca70-c69f-49ee-adfb-34c75f4f71bc · outbound

This paper cites Balanced multimodal learning via on-the-fly gradient modulation,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Balanced multimodal learning via on-the-fly gradient modulation,

Reference 28

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This paper cites Modality competition: What makes joint training of multi-modal network fail in deep learning? (provably),.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Modality competition: What makes joint training of multi-modal network fail in deep learning? (provably),

Reference 29

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Observation 9d849bdb-e8cf-42f5-97cd-9105720bea9a · outbound

This paper cites Understanding unimodal bias in multimodal deep linear networks,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Understanding unimodal bias in multimodal deep linear networks,

Reference 30

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This paper cites Multi-modal 3d object detection in autonomous driving: a survey,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Multi-modal 3d object detection in autonomous driving: a survey,

Reference 31

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Observation dc9cea52-1612-4e2e-a112-4e5c9f5b546c · outbound

This paper cites Missing modality robustness in semi-supervised multi-modal semantic segmentation,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Missing modality robustness in semi-supervised multi-modal semantic segmentation,

Reference 32

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Observation 2e30c20d-04a8-4d4d-8576-bd01a914601d · outbound

This paper cites Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation

Reference 33

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This paper cites Redundancy-Adaptive Multimodal Learning for Imperfect Data.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Redundancy-Adaptive Multimodal Learning for Imperfect Data

Reference 34

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Observation c75099af-1218-4e73-ba52-779db09b2b42 · outbound

This paper cites Multimodal Guidance Network for Missing-Modality Inference in Content Moderation.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Multimodal Guidance Network for Missing-Modality Inference in Content Moderation

Reference 35

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Observation ac6ff724-3b41-4787-b0ce-7d3b10ed323d · outbound

This paper cites Learnable cross- modal knowledge distillation for multi-modal learning with missing modality,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Learnable cross- modal knowledge distillation for multi-modal learning with missing modality,

Reference 36

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Observation 86d63514-1253-4e33-afe0-430890cd1e20 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 37

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Pith citing papers

Observation 79be1a93-79f7-405a-ad4d-5ee606768927 · inbound

Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts cites this paper.

Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation

Reference 35

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Observation a4ef6b52-f6e4-4ca7-a035-926c2f6bb63f · inbound

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

Segment Any RGB-Thermal Model with Language-aided Distillation Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation

Reference 29

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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 Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation

Reference 17

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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 Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation

Reference 45

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Observation 32bd4f51-859d-493b-a30d-7056d89fb687 · inbound

MLLMs are Deeply Affected by Modality Bias cites this paper.

MLLMs are Deeply Affected by Modality Bias Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation

Reference 40

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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 Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation

Reference 11

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Observation de2a37fa-ebb5-4d43-97be-c10566395a0a · 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 Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:17:54.928596Z

Source-reported events for the cited work

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