20 citations · 22 across the 3 of their papers we have counts for
3 papers
cs.AI2024★ 2 cited
Benchmarking the Capabilities of Large Language Models in Transportation System Engineering: Accuracy, Consistency, and Reasoning Behaviors
Usman Syed, Ethan Light, Xingang Guo +4
In this paper, we explore the capabilities of state-of-the-art large language models (LLMs) such as GPT-4, GPT-4o, Claude 3.5 Sonnet, Claude 3 Opus, Gemini 1.5 Pro, Llama 3, and Ll…
math.OC2024★ 20 cited
Capabilities of Large Language Models in Control Engineering: A Benchmark Study on GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra
Darioush Kevian, Usman Syed, Xingang Guo +5
In this paper, we explore the capabilities of state-of-the-art large language models (LLMs) such as GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra in solving undergraduate-level contro…
math.OC2024
Model-Free -Synthesis: A Nonsmooth Optimization Perspective
Darioush Keivan, Xingang Guo, Peter Seiler +2
In this paper, we revisit model-free policy search on an important robust control benchmark, namely -synthesis. In the general output-feedback setting, there do not exist convex…