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Large Language Models (LLMs) have demonstrated exceptional capabilities across various natural language processing tasks. Yet, many of these advanced LLMs are tailored for broad, general-purpose applications. In this technical report, we…

The number and dynamic nature of web and mobile applications presents significant challenges for assessing their compliance with data protection laws. In this context, symbolic and statistical Natural Language Processing (NLP) techniques…

计算与语言 · 计算机科学 2025-12-22 David Rodriguez , Ian Yang , Jose M. Del Alamo , Norman Sadeh

The rapid advancement of artificial intelligence, particularly with the development of Large Language Models (LLMs) built on the transformer architecture, has redefined the capabilities of natural language processing. These models now…

计算与语言 · 计算机科学 2025-02-11 Andrea Matarazzo , Riccardo Torlone

Deductive coding is a widely used qualitative research method for determining the prevalence of themes across documents. While useful, deductive coding is often burdensome and time consuming since it requires researchers to read, interpret,…

计算与语言 · 计算机科学 2023-06-28 Robert Chew , John Bollenbacher , Michael Wenger , Jessica Speer , Annice Kim

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach,…

Large Language Models (LLMs) have demonstrated impressive capabilities across a range of scientific tasks including mathematics, physics, and chemistry. Despite their successes, the effectiveness of LLMs in handling complex statistical…

计算与语言 · 计算机科学 2024-10-11 Yizhang Zhu , Shiyin Du , Boyan Li , Yuyu Luo , Nan Tang

Since the advent of GPT, large language models (LLMs) have brought about revolutionary advancements in all walks of life. As a superior natural language processing (NLP) technology, LLMs have consistently achieved state-of-the-art…

网络与互联网体系结构 · 计算机科学 2024-06-26 Danshi Wang , Yidi Wang , Xiaotian Jiang , Yao Zhang , Yue Pang , Min Zhang

Large Language Models (LLMs) have demonstrated remarkable capabilities across various fields, from natural language understanding to text generation. Compared to non-generative LLMs like BERT and DeBERTa, generative LLMs like GPT series and…

硬件体系结构 · 计算机科学 2025-06-16 Jinhao Li , Jiaming Xu , Shan Huang , Yonghua Chen , Wen Li , Jun Liu , Yaoxiu Lian , Jiayi Pan , Li Ding , Hao Zhou , Yu Wang , Guohao Dai

The programming capabilities of large language models (LLMs) have revolutionized automatic code generation and opened new avenues for automatic statistical analysis. However, the validity and quality of these generated codes need to be…

Large language models (LLMs) have garnered significant attention in both the AI community and beyond. Among these, the Generative Pre-trained Transformer (GPT) has emerged as the dominant architecture, spawning numerous variants. However,…

分布式、并行与集群计算 · 计算机科学 2024-02-02 Junqi Yin , Avishek Bose , Guojing Cong , Isaac Lyngaas , Quentin Anthony

This paper investigates the utilization of Large Language Models (LLMs) for solving complex linguistic puzzles, a domain requiring advanced reasoning and adept translation capabilities akin to human cognitive processes. We explore specific…

计算与语言 · 计算机科学 2025-02-04 Zheng-Lin Lin , Yu-Fei Shih , Shu-Kai Hsieh

Large Language Models (LLMs) have demonstrated their remarkable capabilities in numerous fields. This survey focuses on how LLMs empower users, regardless of their technical background, to use human languages to automatically generate…

软件工程 · 计算机科学 2025-04-03 Nam Huynh , Beiyu Lin

The rapid advancement of Large Language Models (LLMs) in the realm of mathematical reasoning necessitates comprehensive evaluations to gauge progress and inspire future directions. Existing assessments predominantly focus on problem-solving…

计算与语言 · 计算机科学 2024-06-05 Xiaoyuan Li , Wenjie Wang , Moxin Li , Junrong Guo , Yang Zhang , Fuli Feng

Assessing the effectiveness of large language models (LLMs) in performing different tasks is crucial for understanding their strengths and weaknesses. This paper presents Hierarchical Prompting Taxonomy (HPT), grounded on human cognitive…

计算与语言 · 计算机科学 2025-07-22 Devichand Budagam , Ashutosh Kumar , Mahsa Khoshnoodi , Sankalp KJ , Vinija Jain , Aman Chadha

Recently, the fast development of Large Language Models (LLMs) such as ChatGPT has significantly advanced NLP tasks by enhancing the capabilities of conversational models. However, the application of LLMs in the recommendation domain has…

信息检索 · 计算机科学 2023-08-24 Junling Liu , Chao Liu , Peilin Zhou , Qichen Ye , Dading Chong , Kang Zhou , Yueqi Xie , Yuwei Cao , Shoujin Wang , Chenyu You , Philip S. Yu

Large Language Models (LLMs) have demonstrated exceptional capabilities in various natural language tasks, often achieving performances that surpass those of humans. Despite these advancements, the domain of mathematics presents a…

计算与语言 · 计算机科学 2024-04-02 Ankit Satpute , Noah Giessing , Andre Greiner-Petter , Moritz Schubotz , Olaf Teschke , Akiko Aizawa , Bela Gipp

This paper presents a comprehensive performance evaluation of Large Language Models (LLMs) in solving programming challenges from Leetcode, a widely used platform for algorithm practice and technical interviews. We began by crawling the…

软件工程 · 计算机科学 2025-03-04 Lun Wang , Chuanqi Shi , Shaoshui Du , Yiyi Tao , Yixian Shen , Hang Zheng , Yanxin Shen , Xinyu Qiu

Large language models (LLMs) have made significant progress in various domains, including healthcare. However, the specialized nature of clinical language understanding tasks presents unique challenges and limitations that warrant further…

计算与语言 · 计算机科学 2023-08-01 Yuqing Wang , Yun Zhao , Linda Petzold

Performance modeling, a pivotal domain in program cost analysis, currently relies on manually crafted models constrained by various program and hardware limitations, especially in the intricate landscape of GPGPU. Meanwhile, Large Language…

性能 · 计算机科学 2025-03-17 Khoi N. M. Nguyen , Hoang Duy Nguyen Do , Huyen Thao Le , Thanh Tuan Dao

This paper explores the efficacy of large language models (LLMs) for Persian. While ChatGPT and consequent LLMs have shown remarkable performance in English, their efficiency for more low-resource languages remains an open question. We…