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In this paper, we demonstrate a surprising capability of large language models (LLMs): given only input feature names and a description of a prediction task, they are capable of selecting the most predictive features, with performance…

Machine Learning · Computer Science 2025-04-21 Daniel P. Jeong , Zachary C. Lipton , Pradeep Ravikumar

Large Language Models (LLMs) have recently demonstrated impressive capabilities across various real-world applications. However, due to the current text-in-text-out paradigm, it remains challenging for LLMs to handle dynamic and complex…

Artificial Intelligence · Computer Science 2024-10-25 Timothy Wei , Annabelle Miin , Anastasia Miin

Forecasting future events is important for policy and decision making. In this work, we study whether language models (LMs) can forecast at the level of competitive human forecasters. Towards this goal, we develop a retrieval-augmented LM…

Machine Learning · Computer Science 2024-02-29 Danny Halawi , Fred Zhang , Chen Yueh-Han , Jacob Steinhardt

The planning ability of Large Language Models (LLMs) has garnered increasing attention in recent years due to their remarkable capacity for multi-step reasoning and their ability to generalize across a wide range of domains. While some…

Artificial Intelligence · Computer Science 2025-02-19 Mohamed Aghzal , Erion Plaku , Gregory J. Stein , Ziyu Yao

The use of Large Language Models (LLMs) has drawn growing interest within the scientific community. LLMs can handle large volumes of textual data and support methods for evidence synthesis. Although recent studies highlight the potential of…

Software Engineering · Computer Science 2026-02-12 Cauã Ferreira Barros , Marcos Kalinowski , Mohamad Kassab , Valdemar Vicente Graciano Neto

Recommender systems usually rely on large-scale interaction data to learn from users' past behaviors and make accurate predictions. However, real-world applications often face situations where no training data is available, such as when…

Information Retrieval · Computer Science 2025-12-16 Genki Kusano , Kenya Abe , Kunihiro Takeoka

Automating code documentation through explanatory text can prove highly beneficial in code understanding. Large Language Models (LLMs) have made remarkable strides in Natural Language Processing, especially within software engineering tasks…

Large language models (LLMs) are rapidly transforming materials science. This review examines recent LLM applications across the materials discovery pipeline, focusing on three key areas: mining scientific literature , predictive modelling,…

Computation and Language · Computer Science 2025-11-17 Fengxu Yang , Weitong Chen , Jack D. Evans

Large language models (LLMs) are incredible and versatile tools for text-based tasks that have enabled countless, previously unimaginable, applications. Retrieval models, in contrast, have not yet seen such capable general-purpose models…

Information Retrieval · Computer Science 2025-09-10 Julian Killingback , Hamed Zamani

Inspired by the insights in cognitive science with respect to human memory and reasoning mechanism, a novel evolvable LLM-based (Large Language Model) agent framework is proposed as REMEMBERER. By equipping the LLM with a long-term…

Computation and Language · Computer Science 2023-10-31 Danyang Zhang , Lu Chen , Situo Zhang , Hongshen Xu , Zihan Zhao , Kai Yu

Human evaluation is indispensable and inevitable for assessing the quality of texts generated by machine learning models or written by humans. However, human evaluation is very difficult to reproduce and its quality is notoriously unstable,…

Computation and Language · Computer Science 2023-05-04 Cheng-Han Chiang , Hung-yi Lee

Although large language models (LLMs) have been touted for their ability to generate natural-sounding text, there are growing concerns around possible negative effects of LLMs such as data memorization, bias, and inappropriate language.…

Machine Learning · Computer Science 2023-05-10 Michael Kuchnik , Virginia Smith , George Amvrosiadis

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

Traditional recommender systems leverage users' item preference history to recommend novel content that users may like. However, modern dialog interfaces that allow users to express language-based preferences offer a fundamentally different…

Information Retrieval · Computer Science 2023-07-27 Scott Sanner , Krisztian Balog , Filip Radlinski , Ben Wedin , Lucas Dixon

Systematic literature reviews (SLRs) are essential but labor-intensive due to high publication volumes and inefficient keyword-based filtering. To streamline this process, we evaluate Large Language Models (LLMs) for enhancing efficiency…

Machine Learning · Computer Science 2025-06-17 Lucas Joos , Daniel A. Keim , Maximilian T. Fischer

In today's rapidly evolving job market, finding the right opportunity can be a daunting challenge. With advancements in the field of AI, computers can now recommend suitable jobs to candidates. However, the task of recommending jobs is not…

Artificial Intelligence · Computer Science 2023-09-22 Preetam Ghosh , Vaishali Sadaphal

Large Language Models (LLMs) have achieved remarkable success in various fields, prompting several studies to explore their potential in recommendation systems. However, these attempts have so far resulted in only modest improvements over…

Information Retrieval · Computer Science 2024-09-20 Junyi Chen , Lu Chi , Bingyue Peng , Zehuan Yuan

Large language models (LLMs) holds significant promise in achieving general medication recommendation systems owing to their comprehensive interpretation of clinical notes and flexibility to medication encoding. We evaluated both…

Information Retrieval · Computer Science 2025-08-05 Zihao Zhao , Chenxiao Fan , Junlong Liu , Zheng Wang , Xiangnan He , Chongming Gao , Juan Li , Fuli Feng

Recently, competition in the field of artificial intelligence (AI) has intensified among major technological companies, resulting in the continuous release of new large-language models (LLMs) that exhibit improved language understanding and…

Information Retrieval · Computer Science 2025-07-29 Sinnyum Choi , Woong Kim

Large Language Models (LLMs) have emerged as powerful tools in various research domains. This article examines their potential through a literature review and firsthand experimentation. While LLMs offer benefits like cost-effectiveness and…

Human-Computer Interaction · Computer Science 2024-04-10 M. Namvarpour , A. Razi
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