works on

From the 1 of 34 linked papers with an AI index.

activity
20242026
collaborators

34 papers

cs.RO2026

nuTruck: Benchmarking Autonomous Driving Planning for Distributed Electric-drive Trucks

Jinyu Miao, Pu Zhang, Yifei He +5

The paper introduces nuTruck, a high‑fidelity simulation benchmark for evaluating rule‑based and learning‑based autonomous driving planners on distributed electric‑drive trucks, in…

cs.LG2026

Dual-Flow Reinforcement Learning with State-Aware Exploration

Qijun Li, Zheng Fu, Qi Song +4

In complex continuous-control reinforcement learning tasks, multimodal optimal actions often coincide with uncertain, multimodal return distributions, making reliable value estimat…

cs.LG2026

daVinci-kernel: Co-Evolving Skill Selection, Summarization, and Utilization via RL for GPU Kernel Optimization

Dayuan Fu, Mohan Jiang, Tongyu Wang +5

GPU kernel optimization represents a paradigm where functional correctness is assumed and execution efficiency is the objective. We present daVinci-kernel, a reinforcement learning…

cs.AI2026

MapAgent: An Industrial-Grade Agentic Framework for City-scale Lane-level Map Generation

Deguo Xia, Zihan Li, Haochen Zhao +6

Lane-level maps are critical infrastructure for autonomous driving and lane-level navigation, yet constructing and maintaining standardized lane networks for hundreds of cities rem…

cs.CV2026

Envision4D: Envisioning Visual Futures via Feed-forward 4D Gaussian Splatting for Autonomous Driving

Qi Song, Yifei He, Chi Zhang +6

Forecasting the future evolution of dynamic scenes is crucial in autonomous driving. However, existing feed-forward paradigms are primarily designed for interpolation. When extende…

cs.DC2026

DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training

Zhixin Wang, Jiaming Xu, Tianyi Zhou +10

Effectively scaling Reinforcement Learning (RL) is crucial for enhancing the reasoning and alignment of Large Language Models. The massive data and complex execution flows inherent…