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This paper presents LLM4ES, a novel framework that exploits large pre-trained language models (LLMs) to derive user embeddings from event sequences. Event sequences are transformed into a textual representation, which is subsequently used…

Information Retrieval · Computer Science 2025-12-18 Aleksei Shestov , Omar Zoloev , Maksim Makarenko , Mikhail Orlov , Egor Fadeev , Ivan Kireev , Andrey Savchenko

Large language models (LLMs) often struggle to provide up-to-date information due to their one-time training and the constantly evolving nature of the world. To keep LLMs current, existing approaches typically involve continued pre-training…

Computation and Language · Computer Science 2025-05-19 Xiaoying Zhang , Baolin Peng , Ye Tian , Jingyan Zhou , Yipeng Zhang , Haitao Mi , Helen Meng

Recent advances in training large language models (LLMs) using massive amounts of solely textual data lead to strong generalization across many domains and tasks, including document-specific tasks. Opposed to that there is a trend to train…

Computation and Language · Computer Science 2024-02-16 Marcel Lamott , Yves-Noel Weweler , Adrian Ulges , Faisal Shafait , Dirk Krechel , Darko Obradovic

Large language models (LLMs) have ushered in a new era for processing complex information in various fields, including science. The increasing amount of scientific literature allows these models to acquire and understand scientific…

Computation and Language · Computer Science 2024-08-21 Huy Quoc To , Ming Liu , Guangyan Huang

Large language models (LLMs) are introducing a paradigm shift in molecular discovery by enabling text-guided interaction with chemical spaces through natural language, symbolic notations, with emerging extensions to incorporate multi-modal…

Machine Learning · Computer Science 2025-05-23 Ziqing Wang , Kexin Zhang , Zihan Zhao , Yibo Wen , Abhishek Pandey , Han Liu , Kaize Ding

This paper proposes LayoutLLM, a more flexible document analysis method for understanding imaged documents. Visually Rich Document Understanding tasks, such as document image classification and information extraction, have gained…

Computation and Language · Computer Science 2024-03-22 Masato Fujitake

The promise of generative AI to revolutionize education is constrained by the pedagogical limits of large language models (LLMs). A major issue is the lack of access to high-quality training data that reflect the learning of actual…

Computation and Language · Computer Science 2025-10-07 Janos Perczel , Jin Chow , Dorottya Demszky

Intelligent Tutoring Systems (ITSs) can provide personalized and self-paced learning experience. The emergence of large language models (LLMs) further enables better human-machine interaction, and facilitates the development of…

Computation and Language · Computer Science 2025-05-29 Zhengyuan Liu , Stella Xin Yin , Geyu Lin , Nancy F. Chen

Recent advancements in the field of Natural Language Processing, particularly the development of large-scale language models that are pretrained on vast amounts of knowledge, are creating novel opportunities within the realm of Knowledge…

Computation and Language · Computer Science 2023-10-06 Anisa Rula , Jennifer D'Souza

With the growing influence of Large Language Models (LLMs), there is increasing interest in integrating speech representations with them to enable more seamless multi-modal processing and speech understanding. This study introduces a novel…

Computation and Language · Computer Science 2025-06-02 Amirbek Djanibekov , Hanan Aldarmaki

Large Language Models (LLMs) excel in handling general knowledge tasks, yet they struggle with user-specific personalization, such as understanding individual emotions, writing styles, and preferences. Personalized Large Language Models…

Artificial Intelligence · Computer Science 2025-09-23 Jiahong Liu , Zexuan Qiu , Zhongyang Li , Quanyu Dai , Wenhao Yu , Jieming Zhu , Minda Hu , Menglin Yang , Tat-Seng Chua , Irwin King

Large Language Models (LLMs) offer a promising solution to complement traditional teaching and address global teacher shortages that affect hundreds of millions of children, but they fail to provide grade-appropriate responses for students…

Computers and Society · Computer Science 2026-03-09 Jio Oh , Steven Euijong Whang , James Evans , Jindong Wang

Large language models (LLMs) are becoming increasingly better at a wide range of Natural Language Processing tasks (NLP), such as text generation and understanding. Recently, these models have extended their capabilities to coding tasks,…

Machine Learning · Computer Science 2024-10-23 Nishat Raihan , Mohammed Latif Siddiq , Joanna C. S. Santos , Marcos Zampieri

The emergence of large language models (LLMs) has resulted in the production of LLM-generated texts that is highly sophisticated and almost indistinguishable from texts written by humans. However, this has also sparked concerns about the…

Computation and Language · Computer Science 2023-06-06 Ruixiang Tang , Yu-Neng Chuang , Xia Hu

With the increasing prevalence of online learning, adapting education to diverse learner needs remains a persistent challenge. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), promise powerful…

Human-Computer Interaction · Computer Science 2025-03-18 Xinyu Jessica Wang , Christine Lee , Bilge Mutlu

This study explores the effectiveness of Large Language Models (LLMs) for Automatic Question Generation in educational settings. Three LLMs are compared in their ability to create questions from university slide text without fine-tuning.…

Computation and Language · Computer Science 2024-09-17 Ivo Lodovico Molina , Valdemar Švábenský , Tsubasa Minematsu , Li Chen , Fumiya Okubo , Atsushi Shimada

Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the…

Computation and Language · Computer Science 2024-04-12 Linyi Yang , Shuibai Zhang , Zhuohao Yu , Guangsheng Bao , Yidong Wang , Jindong Wang , Ruochen Xu , Wei Ye , Xing Xie , Weizhu Chen , Yue Zhang

The emergence of large language models (LLMs) has revolutionized the capabilities of text comprehension and generation. Multi-modal generation attracts great attention from both the industry and academia, but there is little work on…

Information Retrieval · Computer Science 2024-04-16 Xiaoteng Shen , Rui Zhang , Xiaoyan Zhao , Jieming Zhu , Xi Xiao

Large Language Models (LLMs) have revolutionised the field of Natural Language Processing (NLP) and have achieved state-of-the-art performance in practically every task in this field. However, the prevalent approach used in text generation,…

Computation and Language · Computer Science 2024-08-12 Nicolo Micheletti , Samuel Belkadi , Lifeng Han , Goran Nenadic

Large Language Models (LLMs) are reshaping unsupervised learning by offering an unprecedented ability to perform text clustering based on their deep semantic understanding. However, their direct application is fundamentally limited by a…

Computation and Language · Computer Science 2026-04-08 Yuanjie Zhu , Liangwei Yang , Ke Xu , Weizhi Zhang , Zihe Song , Jindong Wang , Philip S. Yu