MDrive benchmark shows multi-agent cooperative driving systems generally outperform single-agent ones in closed-loop settings but perception sharing does not always improve planning and negotiation can harm performance in complex traffic.
Opv2v: An open benchmark dataset and fusion pipeline for perception with vehicle-to-vehicle communication
2 Pith papers cite this work. Polarity classification is still indexing.
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citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
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use dataset 1representative citing papers
BOLT is a 0.9M-parameter plug-and-play module that uses ego-as-teacher distillation on high-confidence predictions to align neighbor features online, raising AP@50 by up to 32.3 points over unadapted fusion while beating ego-only baselines on DAIR-V2X and OPV2V.
citing papers explorer
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MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems
MDrive benchmark shows multi-agent cooperative driving systems generally outperform single-agent ones in closed-loop settings but perception sharing does not always improve planning and negotiation can harm performance in complex traffic.
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BOLT: Online Lightweight Adaptation for Preparation-Free Heterogeneous Cooperative Perception
BOLT is a 0.9M-parameter plug-and-play module that uses ego-as-teacher distillation on high-confidence predictions to align neighbor features online, raising AP@50 by up to 32.3 points over unadapted fusion while beating ego-only baselines on DAIR-V2X and OPV2V.