133 citations · 316 across the 39 of their papers we have counts for
5 papers · 1 filter
Large Language Models as User-Agents for Evaluating Task-Oriented-Dialogue Systems
Taaha Kazi, Ruiliang Lyu, Sizhe Zhou +2
Traditionally, offline datasets have been used to evaluate task-oriented dialogue (TOD) models. These datasets lack context awareness, making them suboptimal benchmarks for convers…
ReSpAct: Harmonizing Reasoning, Speaking, and Acting Towards Building Large Language Model-Based Conversational AI Agents
Vardhan Dongre, Xiaocheng Yang, Emre Can Acikgoz +3
Large language model (LLM)-based agents are increasingly employed to interact with external environments (e.g., games, APIs, world models) to solve user-provided tasks. However, cu…
Simulating User Agents for Embodied Conversational-AI
Daniel Philipov, Vardhan Dongre, Gokhan Tur +1
Embodied agents designed to assist users with tasks must engage in natural language interactions, interpret instructions, execute actions, and communicate effectively to resolve is…
Confidence Estimation for LLM-Based Dialogue State Tracking
Yi-Jyun Sun, Suvodip Dey, Dilek Hakkani-Tur +1
Estimation of a model's confidence on its outputs is critical for Conversational AI systems based on large language models (LLMs), especially for reducing hallucination and prevent…
Dialog Flow Induction for Constrainable LLM-Based Chatbots
Stuti Agrawal, Nishi Uppuluri, Pranav Pillai +5
LLM-driven dialog systems are used in a diverse set of applications, ranging from healthcare to customer service. However, given their generalization capability, it is difficult to…