43 citations · 58 across the 9 of their papers we have counts for
9 papers
OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks
Mengqi Yuan, Zilong Zhou, Xinzhuang Xiong +33
Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to reveal the limitations of f…
EnactToM: An Evolving Benchmark for Functional Theory of Mind in Embodied Agents
Gurusha Juneja, Dylan Lu, Saaket Agashe +7
Theory of Mind (ToM), the ability to track others epistemic state, makes humans efficient collaborators. AI agents need the same capacity in multi agent settings, yet existing benc…
On the Reliability of Computer Use Agents
Gonzalo Gonzalez-Pumariega, Saaket Agashe, Jiachen Yang +2
Computer-use agents have rapidly improved on real-world tasks such as web navigation, desktop automation, and software interaction, in some cases surpassing human performance. Yet…
Context Bootstrapped Reinforcement Learning
Saaket Agashe, Jayanth Srinivasa, Gaowen Liu +2
Reinforcement Learning from Verifiable Rewards (RLVR) suffers from exploration inefficiency, where models struggle to generate successful rollouts, resulting in minimal learning si…
Self-Resource Allocation in Multi-Agent LLM Systems
Alfonso Amayuelas, Jingbo Yang, Saaket Agashe +4
With the development of LLMs as agents, there is a growing interest in connecting multiple agents into multi-agent systems to solve tasks concurrently, focusing on their role in ta…
Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents
Saaket Agashe, Kyle Wong, Vincent Tu +3
Computer use agents automate digital tasks by directly interacting with graphical user interfaces (GUIs) on computers and mobile devices, offering significant potential to enhance…
Agent S: An Open Agentic Framework that Uses Computers Like a Human
Saaket Agashe, Jiuzhou Han, Shuyu Gan +3
We present Agent S, an open agentic framework that enables autonomous interaction with computers through a Graphical User Interface (GUI), aimed at transforming human-computer inte…
LLM-Coordination: Evaluating and Analyzing Multi-agent Coordination Abilities in Large Language Models
Saaket Agashe, Yue Fan, Anthony Reyna +1
Large Language Models (LLMs) have demonstrated emergent common-sense reasoning and Theory of Mind (ToM) capabilities, making them promising candidates for developing coordination a…
Interacting with next-phrase suggestions: How suggestion systems aid and influence the cognitive processes of writing
Advait Bhat, Saaket Agashe, Niharika Mohile +3
Writing with next-phrase suggestions powered by large language models is becoming more pervasive by the day. However, research to understand writers' interaction and decision-makin…