382 citations · 3.4k across the 65 of their papers we have counts for
7 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…
Trajectory-Level Redirection Attacks on Vision-Language-Action Models
Gokul Puthumanaillam, Vardhan Dongre, Pranay Thangeda +3
Vision-language-action (VLA) policies bring natural language into closed-loop robot control, enabling robots to execute manipulation tasks directly from text instructions. The same…
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…
Learning to See Sharper: A Physics-Informed Artificial Intelligence Framework for Super-Resolving Galaxy Spectra
Aryana Haghjoo, Shoubaneh Hemmati, Bahram Mobasher +7
The information recoverable from galaxy spectra depends fundamentally on spectral resolution, yet assembling large samples at high resolution remains observationally expensive. We…
Interactive World Simulator for Robot Policy Training and Evaluation
Yixuan Wang, Rhythm Syed, Fangyu Wu +7
Action-conditioned video prediction models (often referred to as world models) have shown strong potential for robotics applications, but existing approaches are often slow and str…
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…