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The performance of language models is commonly limited by insufficient knowledge and constrained reasoning. Prior approaches such as Retrieval-Augmented Generation (RAG) and Chain-of-Thought (CoT) address these issues by incorporating…

Information Retrieval · Computer Science 2026-03-31 Xinyi Duan , Yuanrong Tang , Jiangtao Gong

Knowledge tracing (KT) is the problem of predicting students' future performance based on their historical interactions with intelligent tutoring systems. Recently, many works present lots of special methods for applying deep neural…

Machine Learning · Computer Science 2023-02-24 Zitao Liu , Qiongqiong Liu , Jiahao Chen , Shuyan Huang , Weiqi Luo

Large language model (LLM)-based educational assistants often provide direct answers that short-circuit learning by reducing exploration, self-explanation, and engagement with course materials. We present BLADE (Better Language Answers…

Human-Computer Interaction · Computer Science 2026-04-07 Chathuri Jayaweera , Bonnie J. Dorr

Automating teaching presents unique challenges, as replicating human interaction and adaptability is complex. Automated systems cannot often provide nuanced, real-time feedback that aligns with students' individual learning paces or…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Ruslan Gokhman , Jialu Li , Youshan Zhang

Clients wishing to implement generative AI in the domain of IT Support and AIOps face two critical issues: domain coverage and model size constraints due to model choice limitations. Clients might choose to not use larger proprietary models…

Knowledge tracing (KT) plays a crucial role in computer-aided education and intelligent tutoring systems, aiming to assess students' knowledge proficiency by predicting their future performance on new questions based on their past response…

Computers and Society · Computer Science 2024-06-03 Jiajun Cui , Minghe Yu , Bo Jiang , Aimin Zhou , Jianyong Wang , Wei Zhang

Requirements elicitation interviews are a widely adopted technique, where the interview success heavily depends on the interviewer's preparedness and communication skills. Students can enhance these skills through practice interviews.…

Software Engineering · Computer Science 2023-08-31 Binnur Görer , Fatma Başak Aydemir

Text-generating AI technology has the potential to revolutionize writing education. However, current AI writing-support tools are limited to providing linear feedback to users. In this work, we demonstrate how text-generating AI can be…

Human-Computer Interaction · Computer Science 2023-04-24 Tae Wook Kim , Quan Tan

Integrating AI-driven tools in higher education is an emerging area with transformative potential. This paper introduces Iris, a chat-based virtual tutor integrated into the interactive learning platform Artemis that offers personalized,…

Human-Computer Interaction · Computer Science 2024-07-11 Patrick Bassner , Eduard Frankford , Stephan Krusche

Retrieval-Augmented Generation (RAG) has demonstrated significant effectiveness in enhancing large language models (LLMs) for complex multi-hop question answering (QA). For multi-hop QA tasks, current iterative approaches predominantly rely…

Computation and Language · Computer Science 2026-01-19 Yuling Shi , Maolin Sun , Zijun Liu , Mo Yang , Yixiong Fang , Tianran Sun , Xiaodong Gu

KnowledgeTracing (KT) involves predicting students' knowledge states based on their interactions with Intelligent Tutoring Systems (ITS). A key challenge is the cold start problem, accurately predicting knowledge for new students with…

Computers and Society · Computer Science 2026-02-09 Indronil Bhattacharjee , Christabel Wayllace

Knowledge tracing (KT) has recently been an active research area of computational pedagogy. The task is to model students' mastery level of knowledge concepts based on their responses to the questions in the past, as well as predict the…

Machine Learning · Computer Science 2021-10-15 Shanghui Yang , Mengxia Zhu , Xuesong Lu

Retrieval-Augmented Generation (RAG) systems have emerged as a promising solution to enhance large language models (LLMs) by integrating external knowledge retrieval with generative capabilities. While significant advancements have been…

Human-Computer Interaction · Computer Science 2025-08-11 Sizhe Cheng , Jiaping Li , Huanchen Wang , Yuxin Ma

Retrieval-Augmented Generation (RAG) has emerged as a key paradigm for enhancing large language models (LLMs) by incorporating external knowledge. However, current RAG methods face two limitations: (1) they only cover limited RAG scenarios.…

Computation and Language · Computer Science 2025-01-03 Wanlong Liu , Junying Chen , Ke Ji , Li Zhou , Wenyu Chen , Benyou Wang

Knowledge tracing (KT) is the problem of modeling each student's mastery of knowledge concepts (KCs) as (s)he engages with a sequence of learning activities. It is an active research area to help provide learners with personalized feedback…

Artificial Intelligence · Computer Science 2021-01-19 Shalini Pandey , George Karypis , Jaideep Srivastava

Retrieval-Augmented Generation (RAG) has demonstrated strong effectiveness in knowledge-intensive tasks by grounding language generation in external evidence. Despite its success, many existing RAG systems are built based on a…

Computation and Language · Computer Science 2026-04-27 Lichang Song , Ting Long , Yi Chang

Retrieval-Augmented Generation (RAG) mitigates hallucination in Large Language Models (LLMs) by incorporating external data, with Knowledge Graphs (KGs) offering crucial information for question answering. Traditional Knowledge Graph…

Computation and Language · Computer Science 2025-09-08 Yushi Sun , Kai Sun , Yifan Ethan Xu , Xiao Yang , Xin Luna Dong , Nan Tang , Lei Chen

Generative AI creates new opportunities for programming education, but many existing systems remain overly directive, producing lengthy explanations and premature solutions that can overwhelm K-12 novices. In this paper, we present a…

Human-Computer Interaction · Computer Science 2026-05-19 Cassandra Lucas , Anshul Bihani , Rohini Kukka , Chun-Hua Tsai , Jaydeb Sarker , Mia Mohammad Imran

We present KITE, a training-free, keyframe-anchored, layout-grounded front-end that converts long robot-execution videos into compact, interpretable tokenized evidence for vision-language models (VLMs). KITE distills each trajectory into a…

Robotics · Computer Science 2026-04-09 Mehdi Hosseinzadeh , King Hang Wong , Feras Dayoub

This paper presents the iterative development of Habit Coach, a GPT-based chatbot designed to support users in habit change through personalized interaction. Employing a user-centered design approach, we developed the chatbot using a…

Human-Computer Interaction · Computer Science 2024-12-17 Arian Fooroogh Mand Arabi , Cansu Koyuturk , Michael O'Mahony , Raffaella Calati , Dimitri Ognibene
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