collaborators

7 papers

cs.AI2026

SETA: Scaling Environments for Terminal Agents

Qijia Shen, Zhiqi Huang, Vamsidhar Kamanuru +19

Large language models (LLMs) are rapidly shifting toward agents that solve tasks through diverse interfaces, including web and graphical user interfaces (GUIs). Among these, the te…

cs.LG2026

Running the Gauntlet: Re-evaluating the Capabilities of Agents Beyond Familiar Environments

Mykola Vysotskyi, Runqi Lin, Grzegorz Biziel +22

As agentic systems continue to evolve and are widely deployed in real-world scenarios, there is a growing demand to faithfully evaluate their capabilities. However, current benchma…

cs.CE2026

Are LLMs Socially Adaptive? Contrasting Belief Evolution in Large Language Models and Humans

Yu Lei, Hao Liu, Chengxing Xie +6

As large language models (LLMs) increasingly engage in complex social interactions, ensuring that their behaviors align with human ethical principles and intentions, known as value…

cs.CR2026

MIP against Agent: Malicious Image Patches Hijacking Multimodal OS Agents

Lukas Aichberger, Alasdair Paren, Guohao Li +3

Recent advances in operating system (OS) agents have enabled vision-language models (VLMs) to directly control a user's computer. Unlike conventional VLMs that passively output tex…

cs.CL2025

Can an Individual Manipulate the Collective Decisions of Multi-Agents?

Fengyuan Liu, Rui Zhao, Shuo Chen +4

Individual Large Language Models (LLMs) have demonstrated significant capabilities across various domains, such as healthcare and law. Recent studies also show that coordinated mul…

cs.LG2025

Loong: Synthesize Long Chain-of-Thoughts at Scale through Verifiers

Xingyue Huang, Rishabh, Gregor Franke +43

Recent advances in Large Language Models (LLMs) have shown that their reasoning capabilities can be significantly improved through Reinforcement Learning with Verifiable Reward (RL…