activity
20212026
most citedMachine Learning for Electronic Design Automation: A Survey

18 citations · 32 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2026

DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression

DeepSeek-AI, :, Anyi Xu +585

The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost of long-context computation…

cs.RO2026

RoboDrop: Curating VLA Post-Training Data via Local Gradient Compatibility

Runze Xu, Yuanfan Xu, Cuijie Xu +4

Vision--language--action (VLA) models acquire broad generalization through large-scale pretraining, yet adapting them to a new task and robot embodiment still requires post-trainin…

cs.RO2026

The Curse of Precision: A Data Scaling Law for High-Precision Robotic Manipulation

Cuijie Xu, Yuanfan Xu, Min Xue +5

While scaling laws for imitation learning have primarily focused on generalization in open-world settings, the relationship between data and precision in closed-world tasks like ro…

cs.CL2026

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-AI, Anyi Xu, Bangcai Lin +315

We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…

cs.RO2024

Localization matters too: How localization error affects UAV flight

Suquan Zhang, Yuanfan Xu, Shu'ang Yu +3

The maximum safe flight speed of a Unmanned Aerial Vehicle (UAV) is an important indicator for measuring its efficiency in completing various tasks. This indicator is influenced by…

cs.RO2022

Explore-Bench: Data Sets, Metrics and Evaluations for Frontier-based and Deep-reinforcement-learning-based Autonomous Exploration

Yuanfan Xu, Jincheng Yu, Jiahao Tang +5

Autonomous exploration and mapping of unknown terrains employing single or multiple robots is an essential task in mobile robotics and has therefore been widely investigated. Never…