1 citations · 2 across the 5 of their papers we have counts for
6 papers
Implicit Beliefs as Scalable Process Rewards for Strategic Persuasion
Minqian Liu, Yuexi Shen, Heajun An +5
Training large language models (LLMs) for multi-turn strategic persuasion faces two coupled obstacles: (i) realistic simulation of psychologically grounded persuadees, and (ii) den…
DeepSAGE: Stage-Aware Reinforcement Learning for Structured CBT Counseling Dialogue
Qi Zhang, Heajun An, Prakriti Dumaru +4
Large Language Model (LLM)-based counseling agents can generate fluent and supportive responses, but they often lack the structured, goal-directed progression required to conduct a…
From Vulnerable to Resilient: Examining Parent and Teen Perceptions on How to Respond to Unwanted Cybergrooming Advances
Xinyi Zhang, Mamtaj Akter, Heajun An +6
Cybergrooming is a form of online abuse that threatens teens' mental health and physical safety. Yet, most prior work has focused on detecting perpetrators' behaviors, leaving a li…
LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models
Minqian Liu, Zhiyang Xu, Xinyi Zhang +8
Recent advancements in Large Language Models (LLMs) have enabled them to approach human-level persuasion capabilities. However, such potential also raises concerns about the safety…
Toward Integrated Solutions: A Systematic Interdisciplinary Review of Cybergrooming Research
Heajun An, Marcos Silva, Qi Zhang +8
Cybergrooming exploits minors through online trust-building, yet research remains fragmented, limiting holistic prevention. Social sciences focus on behavioral insights, while comp…
Generating A Crowdsourced Conversation Dataset to Combat Cybergrooming
Xinyi Zhang, Pamela J. Wisniewski, Jin-hee Cho +2
Cybergrooming emerges as a growing threat to adolescent safety and mental health. One way to combat cybergrooming is to leverage predictive artificial intelligence (AI) to detect p…