English
Related papers

Related papers: Chain-of-Interaction: Enhancing Large Language Mod…

200 papers

We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce Large Language Models (LLMs) to reason about human emotional states. This method is inspired by various psychotherapy…

Computation and Language · Computer Science 2024-09-17 Yoon Kyung Lee , Inju Lee , Minjung Shin , Seoyeon Bae , Sowon Hahn

Large language models demonstrated state-of-the-art results on various reasoning tasks when applying the chain-of-thought (CoT) prompting technique. CoT prompting guides the model into breaking tasks into a few intermediate steps and…

Computation and Language · Computer Science 2024-10-11 Oxana Vitman , Nika Amaglobeli , Paul Plachinda

The human brain is naturally equipped to comprehend and interpret visual information rapidly. When confronted with complex problems or concepts, we use flowcharts, sketches, and diagrams to aid our thought process. Leveraging this inherent…

Computer Vision and Pattern Recognition · Computer Science 2023-11-17 Fanxu Meng , Haotong Yang , Yiding Wang , Muhan Zhang

Large Language Models (LLMs) often struggle with complex reasoning tasks due to insufficient in-depth insights in their training data, which are typically absent in publicly available documents. This paper introduces the Chain of…

Computation and Language · Computer Science 2025-06-10 Cong Liu , Jie Wu , Weigang Wu , Xu Chen , Liang Lin , Wei-Shi Zheng

As large language models (LLMs) move into persistent, user-facing roles, their behavior must be understood not as isolated responses but as a trajectory unfolding over sustained interaction. We introduce the concept of the chain-of-affect…

Human-Computer Interaction · Computer Science 2026-04-29 Junjie Xu , Xingjiao Wu , Luwei Xiao , Yuzhe Yang , Jie Zhou , Zihao Zhang , Luhan Wang , Yi Huang , Nan Wu , Yingbin Zheng , Chao Yan , Cheng Jin , Honglin Li , Liang He

Background: Motivational interviewing (MI) is an effective counseling approach for promoting health behavior change, but its impact is constrained by the need for highly trained human counselors. Objective: This study aimed to explore a…

Computation and Language · Computer Science 2025-12-18 Run-ze Hu , Yang Yang , Yi-hang Yang , Jing-qi Kong , Jia-hui Luo , Wen-yu Yang , Jing Chen , Jing-yao Liu , Hui-qun Zeng , Lei Zhang , Zheng Liu

Chain-of-Thought (CoT), a step-wise and coherent reasoning chain, shows its impressive strength when used as a prompting strategy for large language models (LLM). Recent years, the prominent effect of CoT prompting has attracted emerging…

Computation and Language · Computer Science 2023-10-10 Zihan Yu , Liang He , Zhen Wu , Xinyu Dai , Jiajun Chen

Large language models (LLMs) have achieved remarkable performance in various natural language processing tasks, especially in dialogue systems. However, LLM may also pose security and moral threats, especially in multi round conversations…

Computation and Language · Computer Science 2024-05-10 Xikang Yang , Xuehai Tang , Songlin Hu , Jizhong Han

Automatically analyzing dialogue can help understand and guide behavior in domains such as counseling, where interactions are largely mediated by conversation. In this paper, we study modeling behavioral codes used to asses a psychotherapy…

Computation and Language · Computer Science 2025-08-05 Jie Cao , Michael Tanana , Zac E. Imel , Eric Poitras , David C. Atkins , Vivek Srikumar

Large Language Models (LLMs), such as \texttt{ChatGPT}, greatly empower dialogue systems with strong language understanding and generation capabilities. However, most of the previous works prompt the LLMs to directly generate a response…

Computation and Language · Computer Science 2023-10-17 Hongru Wang , Rui Wang , Fei Mi , Yang Deng , Zezhong Wang , Bin Liang , Ruifeng Xu , Kam-Fai Wong

Addressing the challenge of effectively processing long contexts has become a critical issue for Large Language Models (LLMs). Two common strategies have emerged: 1) reducing the input length, such as retrieving relevant chunks by…

Computation and Language · Computer Science 2024-06-06 Yusen Zhang , Ruoxi Sun , Yanfei Chen , Tomas Pfister , Rui Zhang , Sercan Ö. Arik

Depression is one of the leading causes of disability worldwide, posing a severe burden on individuals, healthcare systems, and society at large. Recent advancements in Large Language Models (LLMs) have shown promise in addressing mental…

Computation and Language · Computer Science 2025-02-11 Shiyu Teng , Jiaqing Liu , Rahul Kumar Jain , Shurong Chai , Ruibo Hou , Tomoko Tateyama , Lanfen Lin , Yen-wei Chen

Large Language Models (LLMs) leverage chain-of-thought (CoT) prompting to provide step-by-step rationales, improving performance on complex tasks. Despite its benefits, vanilla CoT often fails to fully verify intermediate inferences and can…

Computation and Language · Computer Science 2025-02-05 Manish Sanwal

Reasoning capabilities in large language models (LLMs) have substantially advanced through methods such as chain-of-thought and explicit step-by-step explanations. However, these improvements have not yet fully transitioned to multimodal…

Computation and Language · Computer Science 2025-08-07 Nima Iji , Kia Dashtipour

Large language models (LLMs) demonstrate their promise in tackling complicated practical challenges by combining action-based policies with chain of thought (CoT) reasoning. Having high-quality prompts on hand, however, is vital to the…

Machine Learning · Computer Science 2024-03-01 Xue Yan , Yan Song , Xinyu Cui , Filippos Christianos , Haifeng Zhang , David Henry Mguni , Jun Wang

Fine-tuning large language models (LLMs) with a collection of large and diverse instructions has improved the model's generalization to different tasks, even for unseen tasks. However, most existing instruction datasets include only single…

Computation and Language · Computer Science 2025-01-07 Shirley Anugrah Hayati , Taehee Jung , Tristan Bodding-Long , Sudipta Kar , Abhinav Sethy , Joo-Kyung Kim , Dongyeop Kang

Although large language models (LLMs) have demonstrated impressive potential on simple tasks, their breadth of scope, lack of transparency, and insufficient controllability can make them less effective when assisting humans on more complex…

Human-Computer Interaction · Computer Science 2022-03-21 Tongshuang Wu , Michael Terry , Carrie J. Cai

Large Language Models (LLMs) have transformed human-computer interaction by enabling natural language-based communication with AI-powered chatbots. These models are designed to be intuitive and user-friendly, allowing users to articulate…

Continuing advances in Large Language Models (LLMs) in artificial intelligence offer important capacities in intuitively accessing and using medical knowledge in many contexts, including education and training as well as assessment and…

Computation and Language · Computer Science 2024-08-01 Roma Shusterman , Allison C. Waters , Shannon O`Neill , Phan Luu , Don M. Tucker

Recent advancements in large language models (LLMs) have shown promise in generating psychotherapeutic dialogues, particularly in the context of motivational interviewing (MI). However, the inherent lack of transparency in LLM outputs…

Computation and Language · Computer Science 2024-12-18 Xin Sun , Xiao Tang , Abdallah El Ali , Zhuying Li , Pengjie Ren , Jan de Wit , Jiahuan Pei , Jos A. Bosch
‹ Prev 1 2 3 10 Next ›