A proven therapeutic technique to overcome negative thoughts is to replace them with a more hopeful "reframed thought." Although therapy can help people practice and learn this Cognitive Reframing of Negative Thoughts, clinician shortages and mental health stigma commonly limit people's access to therapy. In this paper, we conduct a human-centered study of how language models may assist people in reframing negative thoughts. Based on psychology literature, we define a framework of seven linguistic attributes that can be used to reframe a thought. We develop automated metrics to measure these attributes and validate them with expert judgements from mental health practitioners. We collect a dataset of 600 situations, thoughts and reframes from practitioners and use it to train a retrieval-enhanced in-context learning model that effectively generates reframed thoughts and controls their linguistic attributes. To investigate what constitutes a "high-quality" reframe, we conduct an IRB-approved randomized field study on a large mental health website with over 2,000 participants. Amongst other findings, we show that people prefer highly empathic or specific reframes, as opposed to reframes that are overly positive. Our findings provide key implications for the use of LMs to assist people in overcoming negative thoughts.
Cognitive Loop of Thought: Reversible Hierarchical Markov Chain for Efficient Mathematical Reasoning
School of Computer Science and Technology, East China Normal University（1 计算机科学与技术学院，华东师范大学）；School of Electronic and Electrical Engineering, Shanghai University of Engineering Science（2 电子电气工程学院，上海工程技术大学）
Cognitive Chain-of-Thought (CoCoT): Structured Multimodal Reasoning about Social Situations
Seoul National University（首尔国立大学）；Human-Computer Interaction Institute, Carnegie Mellon University（人机交互研究所，卡内基梅隆大学）；Language Technologies Institute, Carnegie Mellon University（语言技术研究所，卡内基梅隆大学）
The Homogenizing Effect of Large Language Models on Human Expression and Thought
Department of Computer Science（计算机科学系）；Center for Computational Language Sciences（计算语言学中心）；Department of Psychology, University of Southern California（心理学系，南加州大学）
PRIME: Large Language Model Personalization with Cognitive Dual-Memory and Personalized Thought Process
Computer Science and Engineering, University of Michigan, Ann Arbor, MI（计算机科学与工程系，密歇根大学，安娜堡分校）；Department of Political Science, Northeastern University, Boston, MA（政治学系，东北大学，波士顿分校）
该研究提出融合认知双记忆与个性化慢思考的 PRIME 框架，并构建基于 Reddit CMV 的长上下文个性化数据集，实验证明其可捕捉动态用户偏好。
Understanding Reasoning in Chain-of-Thought from the Hopfieldian View
King Abdullah University of Science and Technology（阿卜杜拉国王科技大学）；Soochow University（苏州大学）；University of Southampton（南安普顿大学）；Arizona State University（亚利桑那州立大学）
ViTCoT: Video-Text Interleaved Chain-of-Thought for Boosting Video Understanding in Large Language Models
School of Computer Science and Engineering, Central South University（计算机科学与工程学院，中南大学）；Research Center for SCIR, Harbin Institute of Technology（SCIR研究中心，哈尔滨工业大学）；NExT Research Center, National University of Singapore（NExT研究中心，新加坡国立大学）
Cross-Linguistic Persona-Driven Data Synthesis for Robust Multimodal Cognitive Decline Detection
Engineering Research Center of Intelligent Theranostics Technology and Instruments, Ministry of Education, School of Biomedical Engineering and Informatics, Nanjing Medical University（智能诊疗技术与仪器工程研究中心、教育部、生物医学工程与信息学院、南京医科大学）；Institute of Biomedical Engineering, University of Oxford（生物医学工程研究所、牛津大学）；Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR)（高性能计算研究所、科技研究局（A*STAR））；Department of Neurology, National Neuroscience Institute, Singapore, 308433, Singapore（神经病学部、新加坡国家神经科学研究所）；Duke-NUS Medical School, Singapore, 169857, Singapore（新加坡国立大学医学院）
Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse
Department of Computer Science, Princeton University, Princeton, NJ, USA（计算机科学系，普林斯顿大学）；NYU Center for Data Science, New York University, New York, NY, USA（纽约大学数据科学中心）；Department of Psychology, Princeton University, Princeton, NJ, USA（心理学系，普林斯顿大学）
CogRAG: Tackling Heterogeneous Cognitive Demands in RAG via Stratified Retrieval and Reasoning
School of Computer and Computing Science, Hangzhou City University（杭州城市大学计算机与计算科学学院）；Innovation Center of Yangtze River Delta, Zhejiang University（长三角创新中心，浙江大学）；Institute of Digital Twin, Eastern Institute of Technology（数字孪生研究院，东部技术研究院）
Cantor: Inspiring Multimodal Chain-of-Thought of MLLM
Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University（厦门大学 多媒体可信感知与高效计算重点实验室（教育部））；Tencent Youtu Lab（腾讯优图实验室）
