Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2101.06085.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T22:16:29.560996Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
254
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation c60b886f-1be0-4e34-a4fa-f12532ec5ca8 · inbound
BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation cites this paper.
BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:16:29.560996Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1aa21998-d941-4cd7-902f-3f6a65e31881 · inbound
OmniNWM: Omniscient Driving Navigation World Models cites this paper.
OmniNWM: Omniscient Driving Navigation World Models Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T08:57:08.905332Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac5b02b4-a38b-4d43-baa6-50ebfb6448ff · inbound
FUME: Fused Unified Multi-Gas Emission Network for Livestock Rumen Acidosis Detection cites this paper.
FUME: Fused Unified Multi-Gas Emission Network for Livestock Rumen Acidosis Detection Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:54:38.447758Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 231cbfbb-6429-4ff4-bc04-0e973ac2fa9d · inbound
PEPR: Privileged Event-based Predictive Regularization for Domain Generalization cites this paper.
PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T07:40:44.116537Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 63cadb5c-d273-4b9a-bee4-43b2dce54209 · inbound
A multi-task spatiotemporal deep neural network for predicting penetration depth and morphology in laser welding cites this paper.
A multi-task spatiotemporal deep neural network for predicting penetration depth and morphology in laser welding Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
Reference 12
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-26T01:38:50.710437Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.