8 papers
Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs
Kairun Zhang, Haoyu Li, Yanjun Zhao +2
Zeroth-order optimizers have recently emerged as an attractive approach for fine-tuning large language models (LLMs), as they avoid backpropagation and can substantially reduce mem…
Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial
Haoyu Li, Xiangru Zhong, Hao Cheng +2
Learning-based methods for synthesizing controllers have gained popularity due to their high expressiveness and strong empirical performance. However, in safety-critical scenarios…
DecepChain: Inducing Deceptive Reasoning in Large Language Models
Wei Shen, Han Wang, Haoyu Li +1
Large Language Models (LLMs) have been demonstrating strong reasoning capability with their chain-of-thoughts (CoT), which are routinely used by humans to judge answer quality. Thi…
Certified Training with Branch-and-Bound for Lyapunov-stable Neural Control
Zhouxing Shi, Haoyu Li, Cho-Jui Hsieh +1
We study the problem of learning verifiably Lyapunov-stable neural controllers that provably satisfy the Lyapunov asymptotic stability condition within a region-of-attraction (ROA)…
On The Fragility of Benchmark Contamination Detection in Reasoning Models
Han Wang, Haoyu Li, Brian Ko +1
Leaderboards for LRMs have turned evaluation into a competition, incentivizing developers to optimize directly on benchmark suites. A shortcut to achieving higher rankings is to in…
Two-Stage Learning of Stabilizing Neural Controllers via Zubov Sampling and Iterative Domain Expansion
Haoyu Li, Xiangru Zhong, Bin Hu +1
Learning-based neural network (NN) control policies have shown impressive empirical performance. However, obtaining stability guarantees and estimates of the region of attraction o…