154 citations · 639 across the 138 of their papers we have counts for
16 papers · 1 filter
Symbolic Guidance for LLM Agents in Distributed Multiagent Coordination
Ben Rachmut, Ning Zhang, Yevgeniy Vorobeychik +1
Large language models (LLMs) are increasingly deployed as autonomous agents in multi-agent systems, yet their ability to reliably execute distributed coordination protocols remains…
Adversarial Reinforcement Learning for Detecting False Data Injection Attacks in Vehicular Routing
Taha Eghtesad, Yevgeniy Vorobeychik, Aron Laszka
In modern transportation networks, adversaries can manipulate routing algorithms using false data injection attacks, such as simulating heavy traffic with multiple devices running…
Mind the (DH) Gap! A Contrast in Risky Choices Between Reasoning and Conversational LLMs
Luise Ge, Yongyan Zhang, Yevgeniy Vorobeychik
The use of large language models either as decision support systems, or in agentic workflows, is rapidly transforming the digital ecosystem. However, the understanding of LLM decis…
Protecting Language Models Against Unauthorized Distillation through Trace Rewriting
Xinhang Ma, William Yeoh, Ning Zhang +1
Knowledge distillation is a widely adopted technique for transferring capabilities from LLMs to smaller, more efficient student models. However, unauthorized use of knowledge disti…
Online Feedback Efficient Active Target Discovery in Partially Observable Environments
Anindya Sarkar, Binglin Ji, Yevgeniy Vorobeychik
In various scientific and engineering domains, where data acquisition is costly--such as in medical imaging, environmental monitoring, or remote sensing--strategic sampling from un…
Multi-Agent Reinforcement Learning for Assessing False-Data Injection Attacks on Transportation Networks
Taha Eghtesad, Sirui Li, Yevgeniy Vorobeychik +1
The increasing reliance of drivers on navigation applications has made transportation networks more susceptible to data-manipulation attacks by malicious actors. Adversaries may ex…