activity
20222026
most citedTowards Building AI-CPS with NVIDIA Isaac Sim: An Industrial Benchmark and Case Study for Robotics Manipulation

41 citations · 57 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2026

KAT-Coder-V2 Technical Report

Fengxiang Li, Han Zhang, Haoyang Huang +43

We present KAT-Coder-V2, an agentic coding model developed by the KwaiKAT team at Kuaishou. KAT-Coder-V2 adopts a "Specialize-then-Unify" paradigm that decomposes agentic coding in…

cs.SE2025

Fine-grained Testing for Autonomous Driving Software: a Study on Autoware with LLM-driven Unit Testing

Wenhan Wang, Xuan Xie, Yuheng Huang +3

Testing autonomous driving systems (ADS) is critical to ensuring their reliability and safety. Existing ADS testing works focuses on designing scenarios to evaluate system-level be…

cs.SE2024

LeCov: Multi-level Testing Criteria for Large Language Models

Xuan Xie, Jiayang Song, Yuheng Huang +4

Large Language Models (LLMs) are widely used in many different domains, but because of their limited interpretability, there are questions about how trustworthy they are in various…

cs.SE2024★ 2 cited

MORTAR: A Model-based Runtime Action Repair Framework for AI-enabled Cyber-Physical Systems

Renzhi Wang, Zhehua Zhou, Jiayang Song +3

Cyber-Physical Systems (CPSs) are increasingly prevalent across various industrial and daily-life domains, with applications ranging from robotic operations to autonomous driving.…

cs.AI2024★ 4 cited

GenSafe: A Generalizable Safety Enhancer for Safe Reinforcement Learning Algorithms Based on Reduced Order Markov Decision Process Model

Zhehua Zhou, Xuan Xie, Jiayang Song +2

Safe Reinforcement Learning (SRL) aims to realize a safe learning process for Deep Reinforcement Learning (DRL) algorithms by incorporating safety constraints. However, the efficac…

cs.SE2024★ 1 cited

Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward

Xuan Xie, Jiayang Song, Zhehua Zhou +3

While Large Language Models (LLMs) have seen widespread applications across numerous fields, their limited interpretability poses concerns regarding their safe operations from mult…

cs.LG2023★ 2 cited

LUNA: A Model-Based Universal Analysis Framework for Large Language Models

Da Song, Xuan Xie, Jiayang Song +4

Over the past decade, Artificial Intelligence (AI) has had great success recently and is being used in a wide range of academic and industrial fields. More recently, LLMs have made…

cs.SE2023★ 41 cited

Towards Building AI-CPS with NVIDIA Isaac Sim: An Industrial Benchmark and Case Study for Robotics Manipulation

Zhehua Zhou, Jiayang Song, Xuan Xie +5

As a representative cyber-physical system (CPS), robotic manipulator has been widely adopted in various academic research and industrial processes, indicating its potential to act…

cs.SE2023★ 3 cited

Mosaic: Model-based Safety Analysis Framework for AI-enabled Cyber-Physical Systems

Xuan Xie, Jiayang Song, Zhehua Zhou +2

Cyber-physical systems (CPSs) are now widely deployed in many industrial domains, e.g., manufacturing systems and autonomous vehicles. To further enhance the capability and applica…

cs.AI2022★ 4 cited

Neuro-Symbolic Verification of Deep Neural Networks

Xuan Xie, Kristian Kersting, Daniel Neider

Formal verification has emerged as a powerful approach to ensure the safety and reliability of deep neural networks. However, current verification tools are limited to only a handf…