5 citations · 11 across the 4 of their papers we have counts for
4 papers
ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders
Ofer Meshi, Krisztian Balog, Sally Goldman +5
The promise of LLM-based user simulators to improve conversational AI is hindered by a critical "realism gap," leading to systems that are optimized for simulated interactions, but…
"Stupid robot, I want to speak to a human!" User Frustration Detection in Task-Oriented Dialog Systems
Mireia Hernandez Caralt, Ivan Sekulić, Filip Carević +9
Detecting user frustration in modern-day task-oriented dialog (TOD) systems is imperative for maintaining overall user satisfaction, engagement, and retention. However, most recent…
Reliable LLM-based User Simulator for Task-Oriented Dialogue Systems
Ivan Sekulić, Silvia Terragni, Victor Guimarães +5
In the realm of dialogue systems, user simulation techniques have emerged as a game-changer, redefining the evaluation and enhancement of task-oriented dialogue (TOD) systems. Thes…
In-Context Learning User Simulators for Task-Oriented Dialog Systems
Silvia Terragni, Modestas Filipavicius, Nghia Khau +3
This paper presents a novel application of large language models in user simulation for task-oriented dialog systems, specifically focusing on an in-context learning approach. By h…