20 citations · 34 across the 11 of their papers we have counts for
11 papers
TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models
Fangxu Yu, Xingang Guo, Lingzhi Yuan +6
Time series are ubiquitous in real-world scenarios and crucial for applications ranging from energy management to traffic control. Consequently, the ability to reason over time ser…
Beyond Seeing: Evaluating Multimodal LLMs on Tool-Enabled Image Perception, Transformation, and Reasoning
Xingang Guo, Utkarsh Tyagi, Advait Gosai +8
Multimodal Large Language Models (MLLMs) are increasingly applied in real-world scenarios where user-provided images are often imperfect, requiring active image manipulations such…
DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models
Chengke Zou, Xingang Guo, Rui Yang +3
The rapid advancements in Vision-Language Models (VLMs) have shown great potential in tackling mathematical reasoning tasks that involve visual context. Unlike humans who can relia…
ControlAgent: Automating Control System Design via Novel Integration of LLM Agents and Domain Expertise
Xingang Guo, Darioush Keivan, Usman Syed +5
Control system design is a crucial aspect of modern engineering with far-reaching applications across diverse sectors including aerospace, automotive systems, power grids, and robo…
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…
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…
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…
COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability
Xingang Guo, Fangxu Yu, Huan Zhang +2
Jailbreaks on large language models (LLMs) have recently received increasing attention. For a comprehensive assessment of LLM safety, it is essential to consider jailbreaks with di…
Global Convergence of Direct Policy Search for State-Feedback Robust Control: A Revisit of Nonsmooth Synthesis with Goldstein Subdifferential
Xingang Guo, Bin Hu
Direct policy search has been widely applied in modern reinforcement learning and continuous control. However, the theoretical properties of direct policy search on nonsmooth robus…
Exact Formulas for Finite-Time Estimation Errors of Decentralized Temporal Difference Learning with Linear Function Approximation
Xingang Guo, Bin Hu
In this paper, we consider the policy evaluation problem in multi-agent reinforcement learning (MARL) and derive exact closed-form formulas for the finite-time mean-squared estimat…
Convex Programs and Lyapunov Functions for Reinforcement Learning: A Unified Perspective on the Analysis of Value-Based Methods
Xingang Guo, Bin Hu
Value-based methods play a fundamental role in Markov decision processes (MDPs) and reinforcement learning (RL). In this paper, we present a unified control-theoretic framework for…