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Paper Citation Record · LEDGER

DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2309.09668.

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

pith.paper-citation-record.v1
2309.09668 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:09:15.026680Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:08:22.184713Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • 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 bb40b631-3476-4b03-a2a6-9c3e0dde5334 · inbound

SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge cites this paper.

SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:45:50.762146Z

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=2026-05-23T22:44:36.339252Z digest=sha256:546501eb6c5bba51c50e7f08e33c1b487251429aa46aac2fea243bea9b051aca

Observation c0ae726e-f4e7-4f20-ad8b-185d8de0b79e · inbound

Ultra-High Resolution Segmentation via Boundary-Enhanced Patch-Merging Transformer cites this paper.

Ultra-High Resolution Segmentation via Boundary-Enhanced Patch-Merging Transformer DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-11T16:19:58.464369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T16:19:58.464369Z digest=sha256:b7fddd5491b9520476512afebb5da4181643a5b0dd55fb1f65d584374b45ca80

Observation b40795a7-b3c0-468d-9dcc-9c949c104e80 · inbound

HDBFormer: Efficient RGB-D Semantic Segmentation with A Heterogeneous Dual-Branch Framework cites this paper.

HDBFormer: Efficient RGB-D Semantic Segmentation with A Heterogeneous Dual-Branch Framework DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-16T12:09:15.026680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:09:15.026680Z digest=sha256:d064eb7cc52ff5bfbcf1a6c8d1e0259046f9c9bf5faaba670cfb820b5193ea85

Observation d7ed4ac6-79ef-4b78-9c47-0cb2e8190850 · 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 DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T11:04:00.543430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:04:00.543430Z digest=sha256:0cd39c95b520b5c2d420b1c818a8d1bd5bcebaf62de9f68e2e68384fb06587be

Observation d5821b6b-8880-40b5-b590-652229c31f57 · inbound

Semantics-aware Predictive Inspection Path Planning cites this paper.

Semantics-aware Predictive Inspection Path Planning DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T05:58:51.075960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:58:51.075960Z digest=sha256:86970db9cc5b12e3e52226fa8fe95d6d84fb2c5bc550fa46fa0e3b7eb91987b3

Observation 17807937-e839-4460-8b22-f6fb084a057e · inbound

Efficient Segment Anything with Depth-Aware Fusion and Limited Training Data cites this paper.

Efficient Segment Anything with Depth-Aware Fusion and Limited Training Data DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-03T00:02:11.598690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:02:11.598690Z digest=sha256:a2aa428f7a7b5b585dc557e4d803a8222ec083bd1c56c978590ad62df17a69b1

Observation 55cf13d6-f5da-4c22-b2ec-44a8166aed06 · inbound

CrossWeaver: Cross-modal Weaving for Arbitrary-Modality Semantic Segmentation cites this paper.

CrossWeaver: Cross-modal Weaving for Arbitrary-Modality Semantic Segmentation DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-13T19:38:10.429256Z

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=2026-05-13T19:37:18.613746Z digest=sha256:38b5013992827dc4acae384f25460101f8c607ca977d2d5632bfbdb7bb142374

Observation 8e32345f-61da-4325-b15f-9980d07d8fa0 · inbound

Visual Place Recognition in Forests with Depth-Aware Distillation cites this paper.

Visual Place Recognition in Forests with Depth-Aware Distillation DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:08:22.188363Z

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=arxiv_source observed=2026-06-27T07:11:56.186001Z digest=sha256:051e6b3760251c7df3cfd20f853dd156a844e6d19603ce7b3efd8ba493596fe5

Observation 1e62da8a-dd83-4759-8b69-4507ec00af44 · inbound

Toward Reliable RGB-D Semantic Segmentation: Handling Missing Modalities via Condition Dropout cites this paper.

Toward Reliable RGB-D Semantic Segmentation: Handling Missing Modalities via Condition Dropout DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-01T10:12:03.265043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:12:03.265043Z digest=sha256:791b8a9ab7b48351bf5efa1982682e23f09298e1f2605ecc1ca0e2a904b372d2