2 citations · 4 across the 7 of their papers we have counts for
8 papers
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…
Running the Gauntlet: Hard Agentic Tasks
Mykola Vysotskyi, Runqi Lin, Grzegorz Biziel +21
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…
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…
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…
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…
Vision-Language Models Do Not Understand Negation
Kumail Alhamoud, Shaden Alshammari, Yonglong Tian +4
Many practical vision-language applications require models that understand negation, e.g., when using natural language to retrieve images which contain certain objects but not othe…
A Scalable Communication Protocol for Networks of Large Language Models
Samuele Marro, Emanuele La Malfa, Jesse Wright +4
Communication is a prerequisite for collaboration. When scaling networks of AI-powered agents, communication must be versatile, efficient, and portable. These requisites, which we…
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…