5 papers · 1 filter
PersEvalBench: Can LLM Evaluators Judge Contextually Appropriate Use of Persona Information?
Xinyi Liu, Hooshang Nayyeri, Emine Yilmaz +3
Large language model (LLM) evaluators are increasingly used to assess personalized assistants, yet whether they can reliably judge personalization has rarely been tested. We introd…
Hear2Act: Benchmarking When Prosody Should Change What an Assistant Does
Xinyi Liu, Hooshang Nayyeri, Dilek Hakkani-Tur +5
Prosodic cues can carry task-relevant information that words omit, but existing benchmarks rarely test whether it changes downstream decisions. We introduce Hear2Act, a 480-scenari…
Beyond Individual Personas: Aligning Synthetic Dialogue to Population-Level Behavior Distributions
Xinyi Liu, Rinat Khaziev, Hooshang Nayyeri +3
Synthetic dialogue corpora are increasingly used as proxies for target dialogue data, yet persona-grounded generators optimize individual conversations rather than corpus compositi…
ATOD: An Evaluation Framework and Benchmark for Agentic Task-Oriented Dialogue Systems
Yifei Zhang, Hooshang Nayyeri, Rinat Khaziev +5
Agentic task-oriented dialogue (TOD) requires systems to track concurrent goals, dependencies, and long-horizon state. We examine goal-lifecycle recovery from fixed dialogue trajec…
Adaptive Multi-Agent Response Refinement in Conversational Systems
Soyeong Jeong, Aparna Elangovan, Emine Yilmaz +1
Large Language Models (LLMs) have demonstrated remarkable success in conversational systems by generating human-like responses. However, they can fall short, especially when requir…