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Paper Citation Record · LEDGER

DAR-Net: Dynamic Aggregation Network for Semantic Scene Segmentation

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1907.12022.

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

pith.paper-citation-record.v1
1907.12022 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:43:24.191745Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T23:07:42.815421Z

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 f66599b0-31db-4a90-bf04-71e8be0a0edc · inbound

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention cites this paper.

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention DAR-Net: Dynamic Aggregation Network for Semantic Scene Segmentation

Reference 274

Resolution
verified exact
arxiv_id, observed 2026-05-14T23:07:42.818799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-14T23:07:42.245641Z digest=sha256:98a38b4c04c9c841893d42a0e6e7e4e9925d3af25010f2126cf5da62b8b4e630

Observation 8a558fe4-7ae0-44b8-a624-26082de11eb7 · inbound

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation cites this paper.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation DAR-Net: Dynamic Aggregation Network for Semantic Scene Segmentation

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-12T16:43:24.191745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:43:24.191745Z digest=sha256:c40bee542afbe6174688269169cb5896968e0726f76be69702f9deebad332d64