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The escalating global mental health crisis, marked by persistent treatment gaps, availability, and a shortage of qualified therapists, positions Large Language Models (LLMs) as a promising avenue for scalable support. While LLMs offer…

Empathy is central to human connection, yet people often struggle to express it effectively. In blinded evaluations, large language models (LLMs) generate responses that are often judged more empathic than human-written ones. Yet when a…

计算与语言 · 计算机科学 2026-03-17 Aakriti Kumar , Nalin Poungpeth , Diyi Yang , Bruce Lambert , Matthew Groh

Large Language Models (LLMs) are increasingly deployed in socially complex, interaction-driven tasks, yet their ability to mirror human behavior in emotionally and strategically complex contexts remains underexplored. This study assesses…

计算与语言 · 计算机科学 2025-09-23 Deuksin Kwon , Kaleen Shrestha , Bin Han , Elena Hayoung Lee , Gale Lucas

Evaluating Large Language Models (LLMs) for mental health support is challenging due to the emotionally and cognitively complex nature of therapeutic dialogue. Existing benchmarks are limited in scale, reliability, often relying on…

Emotions exert an immense influence over human behavior and cognition in both commonplace and high-stress tasks. Discussions of whether or how to integrate large language models (LLMs) into everyday life (e.g., acting as proxies for, or…

人工智能 · 计算机科学 2025-08-21 Mattson Ogg , Chace Ashcraft , Ritwik Bose , Raphael Norman-Tenazas , Michael Wolmetz

This paper argues that Large Language Models (LLMs) should incorporate explicit mechanisms for human empathy. As LLMs become increasingly deployed in high-stakes human-centered settings, their success depends not only on correctness or…

计算与语言 · 计算机科学 2026-04-14 Xiaoxing You , Qiang Huang , Jun Yu

Large language models are moving beyond transactional question answering to act as companions, coaches, mediators, and curators that scaffold human growth, decision-making, and well-being. This paper proposes a role-based framework for…

人机交互 · 计算机科学 2026-01-27 Zhiyin Zhou

Speech Language Models (SLMs) have made significant progress in spoken language understanding. Yet it remains unclear whether they can fully perceive non lexical vocal cues alongside spoken words, and respond with empathy that aligns with…

计算与语言 · 计算机科学 2026-03-06 Li Zhou , Lutong Yu , You Lyu , Yihang Lin , Zefeng Zhao , Junyi Ao , Yuhao Zhang , Benyou Wang , Haizhou Li

Conversational human-likeness plays a central role in human-AI interaction, yet it has remained difficult to define, measure, and optimize. As a result, improvements in human-like behavior are largely driven by scale or broad supervised…

人工智能 · 计算机科学 2026-01-08 Masum Hasan , Junjie Zhao , Ehsan Hoque

The rapid evolution of large language models (LLMs) and their capacity to simulate human cognition and behavior has given rise to LLM-based frameworks and tools that are evaluated and applied based on their ability to perform tasks…

计算与语言 · 计算机科学 2024-12-03 Jing Yi Wang , Nicholas Sukiennik , Tong Li , Weikang Su , Qianyue Hao , Jingbo Xu , Zihan Huang , Fengli Xu , Yong Li

Evaluating Large Language Models' (LLMs) anthropomorphic capabilities has become increasingly important in contemporary discourse. Utilizing the emotion appraisal theory from psychology, we propose to evaluate the empathy ability of LLMs,…

计算与语言 · 计算机科学 2024-10-08 Jen-tse Huang , Man Ho Lam , Eric John Li , Shujie Ren , Wenxuan Wang , Wenxiang Jiao , Zhaopeng Tu , Michael R. Lyu

The rise of large language models (LLMs) has shifted time series analysis from narrow analytics to general-purpose reasoning. Yet, existing benchmarks cover only a small set of health time series modalities and tasks, failing to reflect the…

机器学习 · 计算机科学 2026-03-17 Sirui Li , Shuhan Xiao , Mihir Joshi , Ahmed Metwally , Daniel McDuff , Wei Wang , Yuzhe Yang

Emotional support is a core capability in human-AI interaction, with applications including psychological counseling, role play, and companionship. However, existing evaluations of large language models (LLMs) often rely on short, static…

As LLMs become increasingly integrated into daily life, understanding how their presence will shape human linguistic behavior is an open question. We present a large-scale study of linguistic convergence in human-LLM dialogue, examining how…

计算与语言 · 计算机科学 2026-05-29 Terra Blevins

With the emergence of large language models (LLMs), investigating if they can surpass humans in areas such as emotion recognition and empathetic responding has become a focal point of research. This paper presents a comprehensive study…

计算与语言 · 计算机科学 2024-06-10 Anuradha Welivita , Pearl Pu

Test-time scaling has significantly improved how AI models solve problems, yet current methods often get stuck in repetitive, incorrect patterns of thought. We introduce HEART, a framework that uses emotional cues to guide the model's…

Empathy serves as a cornerstone in enabling prosocial behaviors, and can be evoked through sharing of personal experiences in stories. While empathy is influenced by narrative content, intuitively, people respond to the way a story is told…

计算与语言 · 计算机科学 2024-10-02 Jocelyn Shen , Joel Mire , Hae Won Park , Cynthia Breazeal , Maarten Sap

Emotional intelligence (EI), the ability to perceive, understand, and respond appropriately to others' emotional states, is central to human communication, and increasingly important to assess as LLMs assume conversational roles in everyday…

Large language models (LLMs) excel at generating empathic responses in text-based conversations. But, how reliably do they judge the nuances of empathic communication? We investigate this question by comparing how experts, crowdworkers, and…

计算与语言 · 计算机科学 2025-10-06 Aakriti Kumar , Nalin Poungpeth , Diyi Yang , Erina Farrell , Bruce Lambert , Matthew Groh

Effective and safe human-machine collaboration requires the regulated and meaningful exchange of emotions between humans and artificial intelligence (AI). Current AI systems based on large language models (LLMs) can provide feedback that…

计算与语言 · 计算机科学 2025-06-18 Xiuwen Wu , Hao Wang , Zhiang Yan , Xiaohan Tang , Pengfei Xu , Wai-Ting Siok , Ping Li , Jia-Hong Gao , Bingjiang Lyu , Lang Qin
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