112 citations · 141 across the 12 of their papers we have counts for
20 papers · 1 filter
RedTeamCUA: Realistic Adversarial Testing of Computer-Use Agents in Hybrid Web-OS Environments
Zeyi Liao, Jaylen Jones, Linxi Jiang +5
Computer-use agents (CUAs) promise to automate complex tasks across operating systems (OS) and the web, but remain vulnerable to indirect prompt injection. Current evaluations of t…
ARM: Adaptive Reasoning Model
Siye Wu, Jian Xie, Yikai Zhang +4
While large reasoning models demonstrate strong performance on complex tasks, they lack the ability to adjust reasoning token usage based on task difficulty. This often leads to th…
MICE for CATs: Model-Internal Confidence Estimation for Calibrating Agents with Tools
Nishant Subramani, Jason Eisner, Justin Svegliato +3
Tool-using agents that act in the world need to be both useful and safe. Well-calibrated model confidences can be used to weigh the risk versus reward of potential actions, but pri…
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jiménez Gutiérrez, Yiheng Shu, Weijian Qi +2
Our ability to continuously acquire, organize, and leverage knowledge is a key feature of human intelligence that AI systems must approximate to unlock their full potential. Given…
ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
Ziru Chen, Shijie Chen, Yuting Ning +17
The advancements of large language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked…
Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankers
Shijie Chen, Bernal Jiménez Gutiérrez, Yu Su
Information retrieval (IR) systems have played a vital role in modern digital life and have cemented their continued usefulness in this new era of generative AI via retrieval-augme…