Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Adver-City: Open-Source Multi-Modal Dataset for Collaborative Perception Under Adverse Weather Conditions
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.06380.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T12:28:47.538002Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T03:00:48.032160Z
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 03a27481-6ffe-4bd0-9611-a703b281e608 · inbound
Collaborative Perception Datasets for Autonomous Driving: A Review cites this paper.
Collaborative Perception Datasets for Autonomous Driving: A Review Adver-City: Open-Source Multi-Modal Dataset for Collaborative Perception Under Adverse Weather Conditions
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T12:28:47.538002Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11ff6f45-1388-4cb1-b9f3-d21e67e1f1e9 · inbound
Progressive Bird's Eye View Perception for Safety-Critical Autonomous Driving: A Comprehensive Survey cites this paper.
Progressive Bird's Eye View Perception for Safety-Critical Autonomous Driving: A Comprehensive Survey Adver-City: Open-Source Multi-Modal Dataset for Collaborative Perception Under Adverse Weather Conditions
Reference 290
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:06:55.847278Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b88e2c8f-9d05-47c0-836b-7eebeac02be5 · inbound
SlimComm: Doppler-Guided Sparse Queries for Bandwidth-Efficient Cooperative 3-D Perception cites this paper.
SlimComm: Doppler-Guided Sparse Queries for Bandwidth-Efficient Cooperative 3-D Perception Adver-City: Open-Source Multi-Modal Dataset for Collaborative Perception Under Adverse Weather Conditions
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:20:04.236065Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a7804c6d-6ebd-4d72-a7ed-1be9eba7b7d3 · inbound
All You Need for Object Detection: From Pixels, Points, and Prompts to Next-Gen Fusion and Multimodal LLMs/VLMs in Autonomous Vehicles cites this paper.
All You Need for Object Detection: From Pixels, Points, and Prompts to Next-Gen Fusion and Multimodal LLMs/VLMs in Autonomous Vehicles Adver-City: Open-Source Multi-Modal Dataset for Collaborative Perception Under Adverse Weather Conditions
Reference 112
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T03:00:48.035060Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 939aaa5b-09ad-439a-87eb-4d3fd37952e4 · inbound
FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog cites this paper.
FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog Adver-City: Open-Source Multi-Modal Dataset for Collaborative Perception Under Adverse Weather Conditions
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T20:21:07.700228Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.