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This paper presents the development and application of a Large Language Model Retrieval-Augmented Generation (LLM-RAG) system tailored for nanotechnology research. The system leverages the capabilities of a sophisticated language model to…

Background: Identification of the interactions and regulatory relations between biomolecules play pivotal roles in understanding complex biological systems and the mechanisms underlying diverse biological functions. However, the collection…

计算与语言 · 计算机科学 2025-04-24 Gilchan Park , Byung-Jun Yoon , Xihaier Luo , Vanessa López-Marrero , Shinjae Yoo , Shantenu Jha

This study explores the application of Large Language Models (LLMs), specifically GPT-4, in the analysis of classroom dialogue, a crucial research task for both teaching diagnosis and quality improvement. Recognizing the knowledge-intensive…

计算与语言 · 计算机科学 2024-10-08 Yun Long , Haifeng Luo , Yu Zhang

There is an increasing interest in leveraging Large Language Models (LLMs) for managing structured data and enhancing data science processes. Despite the potential benefits, this integration poses significant questions regarding their…

人工智能 · 计算机科学 2023-11-21 Nathalia Nascimento , Cristina Tavares , Paulo Alencar , Donald Cowan

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by…

计算与语言 · 计算机科学 2023-10-31 Yizhe Yang , Huashan Sun , Jiawei Li , Runheng Liu , Yinghao Li , Yuhang Liu , Heyan Huang , Yang Gao

Generalized large language models (LLMs) such as GPT-4 may not provide specific answers to queries formulated by materials science researchers. These models may produce a high-level outline but lack the capacity to return detailed…

计算与语言 · 计算机科学 2024-06-04 Achuth Chandrasekhar , Jonathan Chan , Francis Ogoke , Olabode Ajenifujah , Amir Barati Farimani

Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materials or manufacturing techniques. Large language models (LLMs)…

We introduce a novel continued pre-training method, MELT (MatEriaLs-aware continued pre-Training), specifically designed to efficiently adapt the pre-trained language models (PLMs) for materials science. Unlike previous adaptation…

计算与语言 · 计算机科学 2024-10-22 Junho Kim , Yeachan Kim , Jun-Hyung Park , Yerim Oh , Suho Kim , SangKeun Lee

In the wake of relentless digital transformation, data-driven solutions are emerging as powerful tools to address multifarious industrial tasks such as forecasting, anomaly detection, planning, and even complex decision-making. Although…

人工智能 · 计算机科学 2023-10-18 Xu Yang , Xiao Yang , Weiqing Liu , Jinhui Li , Peng Yu , Zeqi Ye , Jiang Bian

Large language models (LLMs) are a class of artificial intelligence models based on deep learning, which have great performance in various tasks, especially in natural language processing (NLP). Large language models typically consist of…

定量方法 · 定量生物学 2025-02-04 Jiajia Liu , Mengyuan Yang , Yankai Yu , Haixia Xu , Tiangang Wang , Kang Li , Xiaobo Zhou

Large Language Models (LLMs) have transformed numerous domains by providing advanced capabilities in natural language understanding, generation, and reasoning. Despite their groundbreaking applications across industries such as research,…

人工智能 · 计算机科学 2025-01-22 Aditi Singh , Nirmal Prakashbhai Patel , Abul Ehtesham , Saket Kumar , Tala Talaei Khoei

The rise of large language models (LLMs) has revolutionized the way that we interact with artificial intelligence systems through natural language. However, LLMs often misinterpret user queries because of their uncertain intention, leading…

计算与语言 · 计算机科学 2024-02-07 Jing-Cheng Pang , Heng-Bo Fan , Pengyuan Wang , Jia-Hao Xiao , Nan Tang , Si-Hang Yang , Chengxing Jia , Sheng-Jun Huang , Yang Yu

Large language models (LLMs) have demonstrated immense capabilities in understanding textual data and are increasingly being adopted to help researchers accelerate scientific discovery through knowledge extraction (information retrieval),…

计算机视觉与模式识别 · 计算机科学 2025-05-30 Robinson Umeike , Neil Getty , Fangfang Xia , Rick Stevens

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…

Large Language Models (LLMs) are the cornerstone in automating Requirements Engineering (RE) tasks, underpinning recent advancements in the field. Their pre-trained comprehension of natural language is pivotal for effectively tailoring them…

软件工程 · 计算机科学 2024-05-16 Andreas Vogelsang , Jannik Fischbach

With the exponential increase in online scientific literature, identifying reliable domain-specific data has become increasingly important but also very challenging. Manual data collection and filtering for domain-specific scientific…

信息检索 · 计算机科学 2026-03-10 Nikita Gautam , Doina Caragea , Ignacio Ciampitti , Federico Gomez

Open Information Extraction (OIE) aims to extract objective structured knowledge from natural texts, which has attracted growing attention to build dedicated models with human experience. As the large language models (LLMs) have exhibited…

计算与语言 · 计算机科学 2023-10-17 Ji Qi , Kaixuan Ji , Xiaozhi Wang , Jifan Yu , Kaisheng Zeng , Lei Hou , Juanzi Li , Bin Xu

Large language models (LLMs) have been widely adopted due to their remarkable performance across various applications, driving the accelerated development of a large number of diverse models. However, these individual LLMs show limitations…

计算与语言 · 计算机科学 2025-06-13 Kaushal Kumar Maurya , KV Aditya Srivatsa , Ekaterina Kochmar

Large language models (LLMs) have achieved huge success for their general knowledge and ability to solve a wide spectrum of tasks in natural language processing (NLP). Due to their impressive abilities, LLMs have shed light on potential…

Large language models (LLMs) enable researchers to analyze text at unprecedented scale and minimal cost. Researchers can now revisit old questions and tackle novel ones with rich data. We provide an econometric framework for realizing this…

计量经济学 · 经济学 2025-12-08 Jens Ludwig , Sendhil Mullainathan , Ashesh Rambachan