1 citations · 5 across the 19 of their papers we have counts for
9 papers · 1 filter
SEAL: Reinforcing Global Safety in Mixture-of-Experts through Shared Expert ALignment
Qingyu Meng, Yiwei Zha, Jiahuan Pei +3
Mixture-of-Experts (MoE) is a scaling architecture for large language models that activates only a small subset of expert modules per token, enabling massive parameter growth with…
When Trust Meets Truth: Trust-Truth Separability in LLM-as-Judge
Xin Sun, Di Wu, Yuchen Guo +4
LLM-as-Judge systems can produce multi-dimensional evaluations, such as trustworthiness, reliability, and factuality, and these outputs are often interpreted as independent evidenc…
MedEasy: Designing AI Standardized Patients for Clinical Consultation Training
Zhiqi Gao, Huarui Luo, Guo Zhu +6
AI standardized patients are becoming a setting for professional training in clinical consultation. This paper presents MedEasy, a multi-agent system that organizes virtual-patient…
SciText2Eq: Assessing LLMs for Explainable Equation Generation for Scientific Creativity
Yifan Mo, Xiao Fu, Yue Su +4
This work investigates the ability of large language models (LLMs) to generate mathematical equations from scientific texts. Prior work faces challenges in unstructured grounding,…
Herculean: An Agentic Benchmark for Financial Intelligence
Xueqing Peng, Zhuohan Xie, Yupeng Cao +60
As AI agents advance, the central question is no longer whether they can solve isolated financial tasks, but whether their capabilities generalize across complete professional work…
StoryMI: Steerable Multi-Agent Therapeutic Dialogue Generation
Qingyu Meng, Min Chen, Dingming Liu +5
Large language models (LLMs) can generate fluent dialogue, but prior works lack situational grounding, dynamic strategy control, and evaluation aligned with clinical standards in m…
Trust Stack for Mental Health AI: A Survey of Calibration across Human, Interaction, and AI Layers
Xin Sun, Yue Su, Yifan Mo +9
Language-based AI is increasingly deployed for mental health support, yet trust is evaluated in interdisciplinary but operationally misaligned ways: NLP and AI work measures robust…
NeuroWise: A Multi-Agent LLM "Glass-Box" System for Practicing Double-Empathy Communication with Autistic Partners
Albert Tang, Yifan Mo, Jie Li +5
The double empathy problem frames communication difficulties between neurodivergent and neurotypical individuals as arising from mutual misunderstanding, yet most interventions foc…
"It Talks Like a Patient, But Feels Different": Co-Designing AI Standardized Patients with Medical Learners
Zhiqi Gao, Guo Zhu, Huarui Luo +6
Standardized patients (SPs) play a central role in clinical communication training but are costly, difficult to scale, and inconsistent. Large language model (LLM) based AI standar…