Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MV2DFusion: Leveraging Modality-Specific Object Semantics for Multi-Modal 3D Detection
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2408.05945.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:41:00.229708Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T14:37:03.138269Z
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 3e5059b0-7843-4f13-9331-d396f5030087 · inbound
RoCA: Robust Cross-Domain End-to-End Autonomous Driving cites this paper.
RoCA: Robust Cross-Domain End-to-End Autonomous Driving MV2DFusion: Leveraging Modality-Specific Object Semantics for Multi-Modal 3D Detection
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:41:00.229708Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16fbb166-3fec-4c5b-b9f9-746c9764b31e · 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 MV2DFusion: Leveraging Modality-Specific Object Semantics for Multi-Modal 3D Detection
Reference 288
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T03:00:48.120939Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c8143564-79f2-46ec-bf1e-a08540deb3ee · inbound
GaussianFusion: Unified 3D Gaussian Representation for Multi-Modal Fusion Perception cites this paper.
GaussianFusion: Unified 3D Gaussian Representation for Multi-Modal Fusion Perception MV2DFusion: Leveraging Modality-Specific Object Semantics for Multi-Modal 3D Detection
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T14:37:03.140425Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.