3 citations · 6 across the 4 of their papers we have counts for
4 papers
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…
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…
Rethinking Supervised Learning and Reinforcement Learning in Task-Oriented Dialogue Systems
Ziming Li, Julia Kiseleva, Maarten de Rijke
Dialogue policy learning for task-oriented dialogue systems has enjoyed great progress recently mostly through employing reinforcement learning methods. However, these approaches h…
SEntNet: Source-aware Recurrent Entity Network for Dialogue Response Selection
Jiahuan Pei, Arent Stienstra, Julia Kiseleva +1
Dialogue response selection is an important part of Task-oriented Dialogue Systems (TDSs); it aims to predict an appropriate response given a dialogue context. Obtaining key inform…