1 citations · 2 across the 4 of their papers we have counts for
5 papers
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…
AutoGLM: Autonomous Foundation Agents for GUIs
Xiao Liu, Bo Qin, Dongzhu Liang +27
We present AutoGLM, a new series in the ChatGLM family, designed to serve as foundation agents for autonomous control of digital devices through Graphical User Interfaces (GUIs). W…
VisualAgentBench: Towards Large Multimodal Models as Visual Foundation Agents
Xiao Liu, Tianjie Zhang, Yu Gu +27
Large Multimodal Models (LMMs) have ushered in a new era in artificial intelligence, merging capabilities in both language and vision to form highly capable Visual Foundation Agent…