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This study explores the application of Large Language Models (LLMs), specifically GPT-4, in the analysis of classroom dialogue, a crucial research task for both teaching diagnosis and quality improvement. Recognizing the knowledge-intensive…

Computation and Language · Computer Science 2024-10-08 Yun Long , Haifeng Luo , Yu Zhang

Empathetic dialogue is an indispensable part of building harmonious social relationships and contributes to the development of a helpful AI. Previous approaches are mainly based on fine small-scale language models. With the advent of…

Computation and Language · Computer Science 2024-07-29 Yushan Qian , Wei-Nan Zhang , Ting Liu

The rapid advancement of Artificial Intelligence has resulted in the advent of Large Language Models (LLMs) with the capacity to produce text that closely resembles human communication. These models have been seamlessly integrated into…

Machine Learning · Computer Science 2025-02-04 Zenon Lamprou , Yashar Moshfeghi

Language models (LMs) are pre-trained on raw text datasets to generate text sequences token-by-token. While this approach facilitates the learning of world knowledge and reasoning, it does not explicitly optimize for linguistic competence.…

Computation and Language · Computer Science 2026-04-17 Atsuki Yamaguchi , Maggie Mi , Nikolaos Aletras

Generative artificial intelligence (AI) and large language models (LLMs) have gained rapid popularity through publicly available tools such as ChatGPT. The adoption of LLMs for personal and professional use is fueled by the natural…

Computation and Language · Computer Science 2024-07-25 Sinan Abdulhak , Wayne Hubbard , Karthik Gopalakrishnan , Max Z. Li

Large language models (LLMs) increasingly serve as educational tools, yet evaluating their teaching capabilities remains challenging due to the resource-intensive, context-dependent, and methodologically complex nature of teacher-student…

Artificial Intelligence · Computer Science 2025-08-01 Yao Shi , Rongkeng Liang , Yong Xu

Student commitment towards a learning recommendation is not separable from their understanding of the reasons it was recommended to them; and their ability to modify it based on that understanding. Among explainability approaches, chatbots…

Artificial Intelligence · Computer Science 2024-01-25 Hasan Abu-Rasheed , Mohamad Hussam Abdulsalam , Christian Weber , Madjid Fathi

The reasoning capability of large language models (LLMs), defined as their ability to analyze, infer, and make decisions based on input information, is essential for building intelligent task-oriented dialogue systems. However, existing…

Computation and Language · Computer Science 2026-03-02 Yu Zhu , Kai Yang

Large language models (LLMs) excel at solving problems with clear and complete statements, but often struggle with nuanced environments or interactive tasks which are common in most real-world scenarios. This highlights the critical need…

The effectiveness of large language models (LLMs) in conversational AI is hindered by their reliance on single-turn supervised fine-tuning (SFT) data, which limits contextual coherence in multi-turn dialogues. Existing methods for…

Computation and Language · Computer Science 2025-07-08 Jiangxu Wu , Cong Wang , TianHuang Su , Jun Yang , Haozhi Lin , Chao Zhang , Ming Peng , Kai Shi , SongPan Yang , BinQing Pan , ZiXian Li , Ni Yang , ZhenYu Yang

The socially-aware navigation system has evolved to adeptly avoid various obstacles while performing multiple tasks, such as point-to-point navigation, human-following, and -guiding. However, a prominent gap persists: in Human-Robot…

Robotics · Computer Science 2024-03-22 Weiqin Zu , Wenbin Song , Ruiqing Chen , Ze Guo , Fanglei Sun , Zheng Tian , Wei Pan , Jun Wang

The rapid evolution of Large Language Models (LLMs) has accelerated the transition from conversational chatbots to general agents. However, effectively balancing empathetic communication with budget-aware decision-making remains an open…

Computation and Language · Computer Science 2026-02-27 Ning Gao , Wei Zhang , Yuqin Dai , Ling Shi , Ziyin Wang , Yujie Wang , Wei He , Jinpeng Wang , Chaozheng Wang

Large language models (LLMs) have achieved remarkable breakthroughs in new dialogue capabilities by leveraging instruction tuning, which refreshes human impressions of dialogue systems. The long-standing goal of dialogue systems is to be…

Computation and Language · Computer Science 2024-04-01 Jiao Ou , Junda Lu , Che Liu , Yihong Tang , Fuzheng Zhang , Di Zhang , Kun Gai

Instruction tuning as an effective technique aligns the outputs of large language models (LLMs) with human preference. But how to generate the seasonal multi-turn dialogues from raw documents for instruction tuning still requires further…

Computation and Language · Computer Science 2024-07-04 Xia Hou , Qifeng Li , Jian Yang , Tongliang Li , Linzheng Chai , Xianjie Wu , Hangyuan Ji , Zhoujun Li , Jixuan Nie , Jingbo Dun , Wenfeng Song

Recent work has explored the use of large language models (LLMs) to generate tutoring responses in mathematics, yet it remains unclear how closely their instructional behavior aligns with expert human practice. We analyze a dataset of math…

Computation and Language · Computer Science 2026-05-28 Ramatu Oiza Abdulsalam , Segun Aroyehun

Collaborative dialogue offers rich insights into students' learning and critical thinking, which is essential for personalizing pedagogical agent interactions in STEM+C settings. While large language models (LLMs) facilitate dynamic…

With the rapid evolution of Natural Language Processing (NLP), Large Language Models (LLMs) like ChatGPT have emerged as powerful tools capable of transforming various sectors. Their vast knowledge base and dynamic interaction capabilities…

Computers and Society · Computer Science 2024-01-02 Kevin Wang , Jason Ramos , Ramon Lawrence

Large Language Models (LLMs) have showcased remarkable capabilities in various Natural Language Processing tasks. For automatic open-domain dialogue evaluation in particular, LLMs have been seamlessly integrated into evaluation frameworks,…

Computation and Language · Computer Science 2024-07-08 John Mendonça , Alon Lavie , Isabel Trancoso

This paper presents a system for diversity-aware autonomous conversation leveraging the capabilities of large language models (LLMs). The system adapts to diverse populations and individuals, considering factors like background,…

Robotics · Computer Science 2024-06-26 Lucrezia Grassi , Carmine Tommaso Recchiuto , Antonio Sgorbissa