6 papers
Backdoor Decontamination Dynamics in LLM Agents
Gabriel Huang, Abhay Puri, Léo Boisvert +4
Open-weight LLM agents are vulnerable to backdoors installed during fine-tuning, which may be undetectable if the trigger conditions are never met during testing. Assuming defender…
Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain
Léo Boisvert, Léo Boisvert, Abhay Puri +8
While finetuning AI agents on interaction data -- such as web browsing or tool use -- improves their capabilities, it also introduces critical security vulnerabilities within the a…
DoomArena: A framework for Testing AI Agents Against Evolving Security Threats
Leo Boisvert, Mihir Bansal, Chandra Kiran Reddy Evuru +9
We present DoomArena, a security evaluation framework for AI agents. DoomArena is designed on three principles: 1) It is a plug-in framework and integrates easily into realistic ag…
FocusAgent: Simple Yet Effective Ways of Trimming the Large Context of Web Agents
Imene Kerboua, Sahar Omidi Shayegan, Megh Thakkar +7
Web agents powered by large language models (LLMs) must process lengthy web page observations to complete user goals; these pages often exceed tens of thousands of tokens. This sat…
The BrowserGym Ecosystem for Web Agent Research
Thibault Le Sellier De Chezelles, Maxime Gasse, Alexandre Drouin +17
The BrowserGym ecosystem addresses the growing need for efficient evaluation and benchmarking of web agents, particularly those leveraging automation and Large Language Models (LLM…
WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
Léo Boisvert, Megh Thakkar, Maxime Gasse +6
The ability of large language models (LLMs) to mimic human-like intelligence has led to a surge in LLM-based autonomous agents. Though recent LLMs seem capable of planning and reas…