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We observe that MLRMs oriented toward human-centric service are highly susceptible to user emotional cues during the deep-thinking stage, often overriding safety protocols or built-in safety checks under high emotional intensity. Inspired…

人工智能 · 计算机科学 2025-08-07 Yuan Xun , Xiaojun Jia , Xinwei Liu , Hua Zhang

Large language models (LLMs) now mediate many web-based mental-health, crisis, and other emotionally sensitive services, yet their psychosocial safety in these settings remains poorly understood and weakly evaluated. We present DialogGuard,…

人工智能 · 计算机科学 2025-12-03 Han Luo , Guy Laban

As AI systems become increasingly integrated into daily life, their potential to exacerbate or trigger severe psychological harms remains poorly understood and inadequately tested. This paper presents a proactive methodology for…

Large Language Models (LLMs) are transforming artificial intelligence, evolving into task-oriented systems capable of autonomous planning and execution. One of the primary applications of LLMs is conversational AI systems, which must…

计算与语言 · 计算机科学 2025-01-22 Elad Levi , Ilan Kadar

The emergence of autonomous Large Language Model (LLM) agents has created a new ecosystem of strategic, agent-to-agent interactions. However, a critical challenge remains unaddressed: in high-stakes, emotion-sensitive domains like debt…

计算与语言 · 计算机科学 2025-11-05 Yunbo Long , Yuhan Liu , Liming Xu , Alexandra Brintrup

The proliferation of Large Language Models (LLMs) and Intelligent Virtual Agents acting as psychotherapists presents significant opportunities for expanding mental healthcare access. However, their deployment has also been linked to serious…

计算与语言 · 计算机科学 2025-09-23 Ian Steenstra , Timothy W. Bickmore

Many people suffer from mental health problems but not everyone seeks professional help or has access to mental health care. AI chatbots have increasingly become a go-to for individuals who either have mental disorders or simply want…

其他定量生物学 · 定量生物学 2025-11-03 Aditya Naik , Jovi Thomas , Teja Sree Mandava , Himavanth Reddy Vemula

The believable simulation of multi-user behavior is crucial for understanding complex social systems. Recently, large language models (LLMs)-based AI agents have made significant progress, enabling them to achieve human-like intelligence…

人工智能 · 计算机科学 2024-12-16 Yijun Liu , Wu Liu , Xiaoyan Gu , Yong Rui , Xiaodong He , Yongdong Zhang

As large language models (LLMs) are increasingly deployed as interactive agents, open-ended human-AI interactions can involve deceptive behaviors with serious real-world consequences, yet existing evaluations remain largely…

人工智能 · 计算机科学 2026-02-09 Yichen Wu , Qianqian Gao , Xudong Pan , Geng Hong , Min Yang

Affective Image Manipulation (AIM) aims to alter visual elements within an image to evoke specific emotional responses from viewers. However, existing AIM approaches rely on rigid \emph{one-to-one} mappings between emotions and visual cues,…

计算机视觉与模式识别 · 计算机科学 2025-06-24 Qi Mao , Haobo Hu , Yujie He , Difei Gao , Haokun Chen , Libiao Jin

Large language models (LLMs) has been widely used for automated negotiation, but their high computational cost and privacy risks limit deployment in privacy-sensitive, on-device settings such as mobile assistants or rescue robots. Small…

人工智能 · 计算机科学 2026-04-14 Yunbo Long , Yuhan Liu , Liming Xu

The rapid advancement of conversational agents, particularly chatbots powered by Large Language Models (LLMs), poses a significant risk of social engineering (SE) attacks on social media platforms. SE detection in multi-turn, chat-based…

The delivery of mental health interventions via ubiquitous devices has shown much promise. A conversational chatbot is a promising oracle for delivering appropriate just-in-time interventions. However, designing emotionally-aware agents,…

人机交互 · 计算机科学 2019-07-24 Asma Ghandeharioun , Daniel McDuff , Mary Czerwinski , Kael Rowan

The rapid advancement of Large Language Models (LLMs), reasoning models, and agentic AI approaches coincides with a growing global mental health crisis, where increasing demand has not translated into adequate access to professional…

人机交互 · 计算机科学 2025-04-03 Kellie Yu Hui Sim , Kenny Tsu Wei Choo

Constrained by the cost and ethical concerns of involving real seekers in AI-driven mental health, researchers develop LLM-based conversational agents (CAs) with tailored configurations, such as profiles, symptoms, and scenarios, to…

计算与语言 · 计算机科学 2025-10-13 Ming Wang , Peidong Wang , Lin Wu , Xiaocui Yang , Daling Wang , Shi Feng , Yuxin Chen , Bixuan Wang , Yifei Zhang

Access to mental health support remains limited, particularly in marginalized communities where structural and cultural barriers hinder timely care. This paper explores the potential of AI-enabled chatbots as a scalable solution, focusing…

计算机与社会 · 计算机科学 2024-10-07 Rawan AlMakinah , Andrea Norcini-Pala , Lindsey Disney , M. Abdullah Canbaz

Large Language Models (LLMs) have demonstrated impressive fluency and reasoning capabilities, but their potential for misuse has raised growing concern. In this paper, we present ScamAgent, an autonomous multi-turn agent built on top of…

密码学与安全 · 计算机科学 2026-01-15 Sanket Badhe

Demand for mental health support through AI chatbots is surging, though current systems present several limitations, like sycophancy or overvalidation, and reinforcement of maladaptive beliefs. A core obstacle to the creation of better…

计算与语言 · 计算机科学 2025-12-08 José Pombal , Maya D'Eon , Nuno M. Guerreiro , Pedro Henrique Martins , António Farinhas , Ricardo Rei

This paper explores the growing presence of emotionally responsive artificial intelligence through a critical and interdisciplinary lens. Bringing together the voices of early-career researchers from multiple fields, it explores how AI…

Human communication is a complex and diverse process that not only involves multiple factors such as language, commonsense, and cultural backgrounds but also requires the participation of multimodal information, such as speech. Large…

计算与语言 · 计算机科学 2024-01-09 Dong Zhang , Zhaowei Li , Pengyu Wang , Xin Zhang , Yaqian Zhou , Xipeng Qiu
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