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Planning for an upcoming project iteration (sprint) is one of the key activities in Scrum planning. In this paper, we present our work in progress on exploring the applicability of Large Language Models (LLMs) for solving this problem. We…

软件工程 · 计算机科学 2025-12-23 Yuwon Yoon , Kevin Iwan , Madeleine Zwart , Xiaohan Qin , Hina Lee , Maria Spichkova

Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough evaluation of these models is crucial before deploying them…

The rapid development of large language models (LLM) has greatly enhanced everyday applications. While many FPGA-based accelerators, with flexibility for fine-grained data control, exhibit superior speed and energy efficiency compared to…

硬件体系结构 · 计算机科学 2026-03-24 Zifan He , Shengyu Ye , Rui Ma , Yang Wang , Jason Cong

With the rapid development of large language models (LLMs), which possess powerful natural language processing and generation capabilities, LLMs are poised to provide more natural and personalized user experiences. Their deployment on…

人工智能 · 计算机科学 2026-03-03 Lianjun Liu , Hongli An , Pengxuan Chen , Longxiang Ye

Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…

An increasing number of organizations are deploying Large Language Models (LLMs) for a wide range of tasks. Despite their general utility, LLMs are prone to errors, ranging from inaccuracies to hallucinations. To objectively assess the…

人工智能 · 计算机科学 2024-10-15 Kiran Busch , Henrik Leopold

The widespread public deployment of large language models (LLMs) in recent months has prompted a wave of new attention and engagement from advocates, policymakers, and scholars from many fields. This attention is a timely response to the…

计算与语言 · 计算机科学 2023-04-04 Samuel R. Bowman

Aligning future system design with the ever-increasing compute needs of large language models (LLMs) is undoubtedly an important problem in today's world. Here, we propose a general performance modeling methodology and workload analysis of…

硬件体系结构 · 计算机科学 2024-07-23 Joyjit Kundu , Wenzhe Guo , Ali BanaGozar , Udari De Alwis , Sourav Sengupta , Puneet Gupta , Arindam Mallik

Large Language Models (LLMs) have become ubiquitous across various domains, transforming the way we interact with information and conduct research. However, most high-performing LLMs remain confined behind proprietary walls, hindering…

Recent advancements in large language models have demonstrated remarkable capabilities across various NLP tasks. But many questions remain, including whether open-source models match closed ones, why these models excel or struggle with…

计算与语言 · 计算机科学 2023-08-22 Hao Yu , Zachary Yang , Kellin Pelrine , Jean Francois Godbout , Reihaneh Rabbany

Large language models (LLMs) are increasingly relied upon for complex multi-turn conversations across diverse real-world applications. However, existing benchmarks predominantly focus on single-turn evaluations, overlooking the models'…

计算与语言 · 计算机科学 2024-01-31 Wai-Chung Kwan , Xingshan Zeng , Yuxin Jiang , Yufei Wang , Liangyou Li , Lifeng Shang , Xin Jiang , Qun Liu , Kam-Fai Wong

The increasing complexity and demand for faster, energy-efficient hardware designs necessitate innovative High-Level Synthesis (HLS) methodologies. This paper explores the potential of Large Language Models (LLMs) to streamline or replace…

硬件体系结构 · 计算机科学 2024-08-21 Yuchao Liao , Tosiron Adegbija , Roman Lysecky

As large language models (LLMs) become more common in educational tools and programming environments, questions arise about how these systems should interact with users. This study investigates how different interaction styles with…

人机交互 · 计算机科学 2025-07-08 Kai Deng

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language processing tasks. Recently, several LLMs-based pipelines have been developed to enhance learning on graphs with text attributes,…

机器学习 · 计算机科学 2024-07-30 Kai Guo , Zewen Liu , Zhikai Chen , Hongzhi Wen , Wei Jin , Jiliang Tang , Yi Chang

With the widespread adoption of Large Language Models (LLMs), in this paper we investigate the multilingual capability of these models. Our preliminary results show that, translating the native language context, question and answer into a…

计算与语言 · 计算机科学 2024-02-05 Adar Kahana , Jaya Susan Mathew , Said Bleik , Jeremy Reynolds , Oren Elisha

Large Language Models (LLMs) have garnered significant attention due to their remarkable ability to process information across various languages. Despite their capabilities, they exhibit inconsistencies in handling identical queries in…

计算与语言 · 计算机科学 2024-06-24 Yue Huang , Chenrui Fan , Yuan Li , Siyuan Wu , Tianyi Zhou , Xiangliang Zhang , Lichao Sun

As large language models (LLMs) increasingly integrate into every aspect of our work and daily lives, there are growing concerns about user privacy, which push the trend toward local deployment of these models. There are a number of…

机器学习 · 计算机科学 2026-02-10 Jie Xiao , Qianyi Huang , Xu Chen , Chen Tian

Large language models (LLMs) regularly demonstrate new and impressive performance on a wide range of language, knowledge, and reasoning benchmarks. Such rapid progress has led many commentators to argue that LLM general cognitive…

计算与语言 · 计算机科学 2025-02-21 James Fodor

Large language models (LLMs) exhibit impressive capabilities across a wide range of tasks, yet the choice of which model to use often involves a trade-off between performance and cost. More powerful models, though effective, come with…

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