2 citations · 3 across the 5 of their papers we have counts for
5 papers
Grounding Large Language Models In Embodied Environment With Imperfect World Models
Haolan Liu, Jishen Zhao
Despite a widespread success in various applications, large language models (LLMs) often stumble when tackling basic physical reasoning or executing robotics tasks, due to a lack o…
Interpretable and Flexible Target-Conditioned Neural Planners For Autonomous Vehicles
Haolan Liu, Jishen Zhao, Liangjun Zhang
Learning-based approaches to autonomous vehicle planners have the potential to scale to many complicated real-world driving scenarios by leveraging huge amounts of driver demonstra…
Safety-Critical Scenario Generation Via Reinforcement Learning Based Editing
Haolan Liu, Liangjun Zhang, Siva Kumar Sastry Hari +1
Generating safety-critical scenarios is essential for testing and verifying the safety of autonomous vehicles. Traditional optimization techniques suffer from the curse of dimensio…
COLA: Characterizing and Optimizing the Tail Latency for Safe Level-4 Autonomous Vehicle Systems
Haolan Liu, Zixuan Wang, Jishen Zhao
Autonomous vehicles (AVs) are envisioned to revolutionize our life by providing safe, relaxing, and convenient ground transportation. The computing systems in such vehicles are req…
A Neural-based Program Decompiler
Cheng Fu, Huili Chen, Haolan Liu +4
Reverse engineering of binary executables is a critical problem in the computer security domain. On the one hand, malicious parties may recover interpretable source codes from the…