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Language is typically modelled with discrete sequences. However, the most successful approaches to language modelling, namely neural networks, are continuous and smooth function approximators. In this work, we show that Transformer-based…

Computation and Language · Computer Science 2025-04-08 Samuele Marro , Davide Evangelista , X. Angelo Huang , Emanuele La Malfa , Michele Lombardi , Michael Wooldridge

We present Foundation-Sec-8B-Reasoning, the first open-source native reasoning model for cybersecurity. Built upon our previously released Foundation-Sec-8B base model (derived from Llama-3.1-8B-Base), the model is trained through a…

Large Language Models (LLMs) offer powerful capabilities for natural language understanding, enabling more intelligent smart home assistants. However, existing systems often rely on cloud-based LLMs, raising concerns around user privacy and…

Human-Computer Interaction · Computer Science 2025-08-12 Ziqi Yin , Mingxin Zhang , Daisuke Kawahara

Recently developed large language models (LLMs) such as ChatGPT, Claude, and Llama have demonstrated impressive abilities, and even surpass human-level performance in several tasks. Despite their success, the resource-intensive demands of…

Computation and Language · Computer Science 2024-06-17 Jie Wu , Yufeng Zhu , Lei Shen , Xuqing Lu

Large Language Models, such as Generative Pre-trained Transformer 3 (aka. GPT-3), have been developed to understand language through the analysis of extensive text data, allowing them to identify patterns and connections between words.…

Computation and Language · Computer Science 2023-10-03 Baphumelele Masikisiki , Vukosi Marivate , Yvette Hlope

Large Language Models (LLMs) have propelled groundbreaking advancements across several domains and are commonly used for text generation applications. However, the computational demands of these complex models pose significant challenges,…

Large language models (LLMs) have revolutionized natural language processing (NLP) with impressive performance across various text-based tasks. However, the extension of text-dominant LLMs to with speech generation tasks remains…

Computation and Language · Computer Science 2024-10-29 Maohao Shen , Shun Zhang , Jilong Wu , Zhiping Xiu , Ehab AlBadawy , Yiting Lu , Mike Seltzer , Qing He

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

Artificial Intelligence · Computer Science 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada

Large language models (LLMs) have shown remarkable abilities to generate code, however their ability to develop software for embedded systems, which requires cross-domain knowledge of hardware and software has not been studied. In this…

Software Engineering · Computer Science 2023-11-23 Zachary Englhardt , Richard Li , Dilini Nissanka , Zhihan Zhang , Girish Narayanswamy , Joseph Breda , Xin Liu , Shwetak Patel , Vikram Iyer

In this work, we introduce ChatQA 2, an Llama 3.0-based model with a 128K context window, designed to bridge the gap between open-source LLMs and leading proprietary models (e.g., GPT-4-Turbo-2024-04-09) in long context understanding and…

Computation and Language · Computer Science 2025-02-18 Peng Xu , Wei Ping , Xianchao Wu , Chejian Xu , Zihan Liu , Mohammad Shoeybi , Bryan Catanzaro

Recent advancements in large language models (LLMs) like ChatGPT and LLaMA show promise in medical applications, yet challenges remain in medical language comprehension. This study presents Me-LLaMA, a new medical LLM family based on…

Large Language Models (LLMs) have demonstrated remarkable capabilities across a variety of software engineering and coding tasks. However, their application in the domain of code and compiler optimization remains underexplored. Training…

Programming Languages · Computer Science 2024-07-04 Chris Cummins , Volker Seeker , Dejan Grubisic , Baptiste Roziere , Jonas Gehring , Gabriel Synnaeve , Hugh Leather

Large Language Models (LLMs) like GPT and LLaMA are revolutionizing the AI industry with their sophisticated capabilities. Training these models requires vast GPU clusters and significant computing time, posing major challenges in terms of…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-30 Jiangfei Duan , Shuo Zhang , Zerui Wang , Lijuan Jiang , Wenwen Qu , Qinghao Hu , Guoteng Wang , Qizhen Weng , Hang Yan , Xingcheng Zhang , Xipeng Qiu , Dahua Lin , Yonggang Wen , Xin Jin , Tianwei Zhang , Peng Sun

Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered as a promising approach to address some of the challenging…

The rapid evolution of large language models (LLMs) has opened new possibilities for automating various tasks in software development. This paper evaluates the capabilities of the Llama 2-70B model in automating these tasks for scientific…

Software Engineering · Computer Science 2025-07-09 Patrick Diehl , Nojoud Nader , Maxim Moraru , Steven R. Brandt

Recent advances in machine learning have made revolutionary breakthroughs in computer games, image and natural language understanding, and scientific discovery. Foundation models and large-scale language models (LLMs) have recently achieved…

Neurons and Cognition · Quantitative Biology 2023-10-31 Ran Wang , Zhe Sage Chen

Large Language Models (LLMs) represent a major step toward artificial general intelligence, significantly advancing our ability to interact with technology. While LLMs perform well on Natural Language Processing tasks -- such as…

Computation and Language · Computer Science 2025-05-15 Brandon Smith , Mohamed Reda Bouadjenek , Tahsin Alamgir Kheya , Phillip Dawson , Sunil Aryal

Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate their emerging abilities. In this study, we show that LLMs…

Computation and Language · Computer Science 2023-10-10 Thilo Hagendorff , Sarah Fabi , Michal Kosinski

Efficient fine-tuning is vital for adapting large language models (LLMs) to downstream tasks. However, it requires non-trivial efforts to implement these methods on different models. We present LlamaFactory, a unified framework that…

Computation and Language · Computer Science 2024-07-01 Yaowei Zheng , Richong Zhang , Junhao Zhang , Yanhan Ye , Zheyan Luo , Zhangchi Feng , Yongqiang Ma
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