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Generative large language models (LLMs) are incredibly useful, versatile, and promising tools. However, they will be of most use to political and social science researchers when they are used in a way that advances understanding about real…

Computers and Society · Computer Science 2025-04-08 Lisa P. Argyle , Ethan C. Busby , Joshua R. Gubler , Bryce Hepner , Alex Lyman , David Wingate

Current interactive systems with natural language interfaces lack the ability to understand a complex information-seeking request which expresses several implicit constraints at once, and there is no prior information about user preferences…

Large Language Models (LLMs) have been emerging as prominent AI models for solving many natural language tasks due to their high performance (e.g., accuracy) and capabilities in generating high-quality responses to the given inputs.…

Neural and Evolutionary Computing · Computer Science 2026-04-22 Rachmad Vidya Wicaksana Putra , Pasindu Wickramasinghe , Muhammad Shafique

Creating and deploying customized applications is crucial for operational success and enriching user experiences in the rapidly evolving modern business world. A prominent facet of modern user experiences is the integration of chatbots or…

Large Language Models (LLMs) have become a key element of modern artificial intelligence, demonstrating the ability to address a wide range of language processing tasks at unprecedented levels of accuracy without the need of collecting…

Large Language Models (LLMs) are starting to be profiled as one of the most significant disruptions in the Software Testing field. Specifically, they have been successfully applied in software testing tasks such as generating test code, or…

Software Engineering · Computer Science 2025-09-30 Cristian Augusto , Antonia Bertolino , Guglielmo De Angelis , Francesca Lonetti , Jesús Morán

Since the launch of ChatGPT, a powerful AI Chatbot developed by OpenAI, large language models (LLMs) have made significant advancements in both academia and industry, bringing about a fundamental engineering paradigm shift in many areas.…

Software Engineering · Computer Science 2023-11-22 Xiaoxia Liu , Jingyi Wang , Jun Sun , Xiaohan Yuan , Guoliang Dong , Peng Di , Wenhai Wang , Dongxia Wang

Large Language Models (LLMs) have achieved remarkable success across a wide range of natural language tasks, and recent efforts have sought to extend their capabilities to multimodal domains and resource-constrained environments. However,…

Machine Learning · Computer Science 2025-05-26 Yun-Da Tsai

Large Language Models (LLMs) have recently developed new advanced functionalities. Their effectiveness relies on statistical learning and generalization capabilities. However, they face limitations in internalizing the data they process and…

Machine Learning · Computer Science 2026-01-14 Farah Ben Slama , Frédéric Armetta

Pre-trained Language Models (PLMs) are integral to many modern natural language processing (NLP) systems. Although multilingual models cover a wide range of languages, they often grapple with challenges like high inference costs and a lack…

Computation and Language · Computer Science 2024-07-19 Murtadha Ahmed , Saghir Alfasly , Bo Wen , Jamaal Qasem , Mohammed Ahmed , Yunfeng Liu

Recently, various studies have leveraged Large Language Models (LLMs) to help decision-making and planning in environments, and try to align the LLMs' knowledge with the world conditions. Nonetheless, the capacity of LLMs to continuously…

Machine Learning · Computer Science 2023-10-16 Yicheng Feng , Yuxuan Wang , Jiazheng Liu , Sipeng Zheng , Zongqing Lu

Large language models (LLMs) have exhibited impressive capabilities across a myriad of tasks, yet they occasionally yield undesirable outputs. We posit that these limitations are rooted in the foundational autoregressive architecture of…

Computation and Language · Computer Science 2025-03-03 Cheng Yang , Chufan Shi , Siheng Li , Bo Shui , Yujiu Yang , Wai Lam

The rapid advancement of Large Language Models (LLMs) has revolutionized various sectors by automating routine tasks, marking a step toward the realization of Artificial General Intelligence (AGI). However, they still struggle to…

Machine Learning · Computer Science 2024-02-21 Zihao Tang , Zheqi Lv , Shengyu Zhang , Fei Wu , Kun Kuang

In this work, we explain our approach employed in the BabyLM Challenge, which uses various methods of training language models (LMs) with significantly less data compared to traditional large language models (LLMs) and are inspired by how…

Computation and Language · Computer Science 2025-03-07 Mohammad Amin Ghanizadeh , Mohammad Javad Dousti

Recent research has highlighted the potential of large language models (LLMs) to improve their problem-solving capabilities with the aid of suitable external tools. In our work, we further advance this concept by introducing a closed-loop…

Machine Learning · Computer Science 2024-03-12 Tianle Cai , Xuezhi Wang , Tengyu Ma , Xinyun Chen , Denny Zhou

The increasing demand for large language model (LLM) serving has necessitated significant advancements in the optimization and profiling of LLM inference systems. As these models become integral to a wide range of applications, the need for…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-20 Feiyang Wu , Zhuohang Bian , Guoyang Duan , Tianle Xu , Junchi Wu , Teng Ma , Yongqiang Yao , Ruihao Gong , Youwei Zhuo

As the application of large language models in various fields continues to expand, materials science also ushers in opportunities for AI-driven innovation. The traditional way of relying on manual search for materials science-related…

Artificial Intelligence · Computer Science 2024-11-14 Chao Huang , Huichen Xiao , Chen Chen , Chunyan Chen , Yi Zhao , Shiyu Du , Yiming Zhang , He Sha , Ruixin Gu

Large language models (LLMs) have achieved remarkable advancements in natural language processing, showcasing exceptional performance across various tasks. However, the expensive memory and computational requirements present significant…

Artificial Intelligence · Computer Science 2025-11-13 Ruihao Gong , Yifu Ding , Zining Wang , Chengtao Lv , Xingyu Zheng , Jinyang Du , Haotong Qin , Jinyang Guo , Michele Magno , Xianglong Liu

Large Language Models (LLMs) as chatbots have drawn remarkable attention thanks to their versatile capability in natural language processing as well as in a wide range of tasks. While there has been great enthusiasm towards adopting such…

Systems and Control · Electrical Eng. & Systems 2024-06-24 Subir Majumder , Lin Dong , Fatemeh Doudi , Yuting Cai , Chao Tian , Dileep Kalathi , Kevin Ding , Anupam A. Thatte , Na Li , Le Xie

Large language models (LLMs) have shown impressive ability for open-domain NLP tasks. However, LLMs are sometimes too footloose for natural language understanding (NLU) tasks which always have restricted output and input format. Their…

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