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Large language models (LLMs) are transforming how students learn by providing readily available tools that can quickly augment or complete various learning activities with non-trivial performance. Similar paradigm shifts have occurred in…

Human-Computer Interaction · Computer Science 2025-07-29 Rahul R. Divekar , Sophia Guerra , Lisette Gonzalez , Natasha Boos , Helen Zhou

Large language models (LLMs) are rapidly changing learning processes, as they are readily available to students and quickly complete or augment several learning-related activities with non-trivial performance. Such major shifts in learning…

Human-Computer Interaction · Computer Science 2024-09-23 Rahul R. Divekar , Sophia Guerra , Lisette Gonzalez , Natasha Boos

The advent of Large Language Models (LLMs) heralds a pivotal shift in online user interactions with information. Traditional Information Retrieval (IR) systems primarily relied on query-document matching, whereas LLMs excel in comprehending…

Information Retrieval · Computer Science 2023-11-22 Samira Ghodratnama , Mehrdad Zakershahrak

The advent of Large Language Models (LLMs) has profoundly transformed the paradigms of information retrieval and problem-solving, enabling students to access information acquisition more efficiently to support learning. However, there is…

Information Retrieval · Computer Science 2025-03-26 Yiming Luo , Ting Liu , Patrick Cheong-Iao Pang , Dana McKay , Ziqi Chen , George Buchanan , Shanton Chang

Large Language Models (LLMs) have shown the potential to be valuable teaching tools, with the potential of giving every student a personalized tutor. However, one challenge with using LLMs to learn new concepts is that when learning a topic…

Human-Computer Interaction · Computer Science 2024-11-19 Steve Oney , Yue Shen , Fei Wu , Young Suh Hong , Ziang Wang , Yamini Khajekar , Jiacheng Zhang , April Yi Wang

This paper investigates the potential of AI models, particularly large language models (LLMs), to support knowledge exploration and augment human creativity during ideation. We present "Latent Lab" an interactive tool for discovering…

Artificial Intelligence · Computer Science 2023-11-23 Kevin Dunnell , Trudy Painter , Andrew Stoddard , Andy Lippman

As the applications of large language models (LLMs) expand across diverse fields, the ability of these models to adapt to ongoing changes in data, tasks, and user preferences becomes crucial. Traditional training methods, relying on static…

Machine Learning · Computer Science 2024-06-11 Junhao Zheng , Shengjie Qiu , Chengming Shi , Qianli Ma

The recent advent of powerful Large-Language Models (LLM) provides a new conversational form of inquiry into historical memory (or, training data, in this case). We show that by augmenting such LLMs with vector embeddings from highly…

Information Retrieval · Computer Science 2023-10-18 Giselle Gonzalez Garcia , Christian Weilbach

Large Language Models (LLMs) are transforming information extraction from academic literature, offering new possibilities for knowledge management. This study presents an LLM-based system designed to extract detailed information about…

Information Retrieval · Computer Science 2025-05-29 Jiseung Yoo , Curran Mahowald , Meiyu Li , Wei Ai

Large language models (LLMs) have rapidly evolved from text generators into powerful problem solvers. Yet, many open tasks demand critical thinking, multi-source, and verifiable outputs, which are beyond single-shot prompting or standard…

Information technology has profoundly altered the way humans interact with information. The vast amount of content created, shared, and disseminated online has made it increasingly difficult to access relevant information. Over the past two…

Information Retrieval · Computer Science 2025-04-14 Yu Zhang , Shutong Qiao , Jiaqi Zhang , Tzu-Heng Lin , Chen Gao , Yong Li

The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Models (LLMs) have demonstrated exceptional capabilities in…

We evaluate the ability of the current generation of large language models (LLMs) to help a decision-making agent facing an exploration-exploitation tradeoff. While previous work has largely study the ability of LLMs to solve combined…

Machine Learning · Computer Science 2026-02-18 Keegan Harris , Aleksandrs Slivkins

As a primary means of information acquisition, information retrieval (IR) systems, such as search engines, have integrated themselves into our daily lives. These systems also serve as components of dialogue, question-answering, and…

Computation and Language · Computer Science 2025-09-18 Yutao Zhu , Huaying Yuan , Shuting Wang , Jiongnan Liu , Wenhan Liu , Chenlong Deng , Haonan Chen , Zheng Liu , Zhicheng Dou , Ji-Rong Wen

A burgeoning area within reinforcement learning (RL) is the design of sequential decision-making agents centered around large language models (LLMs). While autonomous decision-making agents powered by modern LLMs could facilitate numerous…

Machine Learning · Computer Science 2026-02-10 Dilip Arumugam , Thomas L. Griffiths

Information retrieval is a rapidly evolving field of information retrieval, which is characterized by a continuous refinement of techniques and technologies, from basic hyperlink-based navigation to sophisticated algorithm-driven search…

Information Retrieval · Computer Science 2024-02-09 Dipankar Sarkar

Conversational search enables multi-turn interactions between users and systems to fulfill users' complex information needs. During this interaction, the system should understand the users' search intent within the conversational context…

Information Retrieval · Computer Science 2025-06-13 Fengran Mo , Chuan Meng , Mohammad Aliannejadi , Jian-Yun Nie

The advent of Large Language Models (LLMs) has brought in a new era of possibilities in the realm of education. This survey paper summarizes the various technologies of LLMs in educational settings from multifaceted perspectives,…

Computation and Language · Computer Science 2024-04-03 Shen Wang , Tianlong Xu , Hang Li , Chaoli Zhang , Joleen Liang , Jiliang Tang , Philip S. Yu , Qingsong Wen

Discovering efficient algorithms for solving complex problems has been an outstanding challenge in mathematics and computer science, requiring substantial human expertise over the years. Recent advancements in evolutionary search with large…

Artificial Intelligence · Computer Science 2026-05-26 Anja Surina , Amin Mansouri , Lars Quaedvlieg , Amal Seddas , Maryna Viazovska , Emmanuel Abbe , Caglar Gulcehre

Large Language Models (LLMs) are rapidly reshaping information retrieval by enabling interactive, generative, and inference-driven search. While traditional keyword-based search remains central to web and academic information access, it…

Information Retrieval · Computer Science 2025-12-02 Zhitong Guan , Yi Wang
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