D2-V2X benchmark and LiDAR-aligned VLM baseline raise occluded hazard recall to 24.4% and cut spatial estimation error by 77% versus zero-shot models in cooperative V2X settings.
arXiv preprint arXiv:2503.02239 (2025)
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LACO introduces Iterative Latent Deliberation, Cross-Horizon Saliency Attribution, and Structured Semantic Knowledge Distillation to enable low-latency latent communication in collaborative driving while preserving performance in CARLA simulations.
OKH-RAG represents knowledge as ordered hyperedges and retrieves coherent interaction sequences via a learned transition model, outperforming permutation-invariant RAG baselines on order-sensitive QA tasks.
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D2-V2X: Depth-Driven Cooperative V2X Reasoning for Autonomous Driving
D2-V2X benchmark and LiDAR-aligned VLM baseline raise occluded hazard recall to 24.4% and cut spatial estimation error by 77% versus zero-shot models in cooperative V2X settings.
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LACO: Adaptive Latent Communication for Collaborative Driving
LACO introduces Iterative Latent Deliberation, Cross-Horizon Saliency Attribution, and Structured Semantic Knowledge Distillation to enable low-latency latent communication in collaborative driving while preserving performance in CARLA simulations.
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Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language Models
OKH-RAG represents knowledge as ordered hyperedges and retrieves coherent interaction sequences via a learned transition model, outperforming permutation-invariant RAG baselines on order-sensitive QA tasks.