End-to-end driving models that learn directly from sensor inputs to control commands, including transformer-based, imitation learning and reinforcement learning approaches.
In this paper, we propose Clear2Fog (C2F), an end-to-end, physics-based pipeline that simulates fog for clear-weather datasets under a unified camera and LiDAR framework.
Engineering 6.5 · Research 8.0 · Business 6.5
We present a conceptual framework for Collaborative Joint Perception and Prediction (Co-P&P) that improves motion prediction of surrounding road users, thereby enhancing situational awareness in complex and dynamic traffic environments.
Engineering 6.0 · Research 7.0 · Business 6.0
To address these limitations, we propose FactorDrive, an end-to-end autonomous driving framework for adaptive multi-step reasoning driven by planning-critical factors (PCFs).
Engineering 6.0 · Research 8.0 · Business 5.0
To address these challenges, we propose UnsDrive, an end-to-end planner designed for unstructured mining scenes.
Engineering 5.5 · Research 8.0 · Business 5.0
To address these challenges, we propose DH-VLM, a dual-horizon cooperative latent reasoning framework that enables asymmetric semantic cooperation between the infrastructure and ego vehicle.
Engineering 6.0 · Research 8.0 · Business 6.0
To address these limitations, this paper proposes DOU-Pose (Depthwise Over-parameterized U-shaped Pose estimation), a visual pose estimation framework built upon the Differentiable SAmple Consensus (DSAC)* pipeline.
Engineering 5.5 · Research 7.0 · Business 5.0
The acceleration of molecular and materials discovery is one of the most critical challenges in modern chemistry, materials science, and pharmaceutical research.
Engineering 5.5 · Research 8.0 · Business 5.0
We present SimWAM, a simple yet effective WAM that leverages future-video prediction as a training-time supervision signal.
Engineering 7.5 · Research 8.0 · Business 5.0
An autonomous driving research paper: CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models.
Engineering 7.0 · Research 7.0 · Business 5.0
This paper proposes a mobility-aware predictive task offloading framework designed for reliable edge communications in future 6G-inspired vehicular network environments.
Engineering 5.5 · Research 7.0 · Business 6.0
Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation, reasoning, planning, and multimodal understanding.
Engineering 7.5 · Research 7.0 · Business 7.0
Natural products (NPs) have historically yielded numerous therapeutic agents, yet their integration into modern drug discovery has been constrained by chemical complexity, low abundance, laborious dereplication, and limited target annotation.
Engineering 5.5 · Research 7.5 · Business 5.0
We propose MapAgent, an industrial-grade agentic architecture that augments a vectorization backbone for specification-compliant lane-map production.
Engineering 6.0 · Research 7.0 · Business 6.5
End-to-end autonomous driving is an emerging technology and a prominent research focus in both industry and academia.
Engineering 6.0 · Research 8.0 · Business 6.5
To address these limitations, we propose a Big Data-Driven Multi-Constraint Learning framework to generate safe driving action proxies derived from ego motion represented by steering and acceleration.
Engineering 6.0 · Research 7.0 · Business 5.0
To address these challenges, this paper proposes an end-to-end, high-precision, ultra-low-latency object detection method tailored for event cameras, achieving an excellent trade-off between detection accuracy and computational efficiency.
Engineering 5.5 · Research 8.0 · Business 5.0
We introduce SUV, a unified end-to-end driving framework that casts future Scene Understanding as Video generation using a pretrained video foundation model.
Engineering 5.5 · Research 8.5 · Business 5.0
Building on this insight, we propose a probabilistic deep supervision framework that regularizes intermediate latent representations directly from GT data.
Engineering 6.0 · Research 7.0 · Business 5.0
To bridge this divide, we introduce WAM-Diff2, a multi-task discrete diffusion VLA framework powered by a three-stage hierarchical distillation strategy.
Engineering 6.0 · Research 7.0 · Business 6.0
An autonomous driving research paper: The Current State and Future Trends of Automotive AI Safety Governance.
Engineering 6.5 · Research 7.5 · Business 8.5