3 citations · 6 across the 4 of their papers we have counts for
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cs.AI2024
IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents
Shrestha Mohanty, Negar Arabzadeh, Andrea Tupini +5
Seamless interaction between AI agents and humans using natural language remains a key goal in AI research. This paper addresses the challenges of developing interactive agents cap…
cs.CL2024★ 1 cited
Towards better Human-Agent Alignment: Assessing Task Utility in LLM-Powered Applications
Negar Arabzadeh, Julia Kiseleva, Qingyun Wu +5
The rapid development in the field of Large Language Models (LLMs) has led to a surge in applications that facilitate collaboration among multiple agents to assist humans in their…