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Large language models (LMs) such as GPT-3 have the surprising ability to do in-context learning, where the model learns to do a downstream task simply by conditioning on a prompt consisting of input-output examples. The LM learns from these…

Computation and Language · Computer Science 2022-07-22 Sang Michael Xie , Aditi Raghunathan , Percy Liang , Tengyu Ma

The overwhelming success of GPT-4 in early 2023 highlighted the transformative potential of large language models (LLMs) across various sectors, including national security. This article explores the implications of LLM integration within…

Cryptography and Security · Computer Science 2024-07-08 William N. Caballero , Phillip R. Jenkins

Large language models (LLMs) are a special class of pretrained language models obtained by scaling model size, pretraining corpus and computation. LLMs, because of their large size and pretraining on large volumes of text data, exhibit…

Computation and Language · Computer Science 2023-10-20 Katikapalli Subramanyam Kalyan

While automated vulnerability detection techniques have made promising progress in detecting security vulnerabilities, their scalability and applicability remain challenging. The remarkable performance of Large Language Models (LLMs), such…

Cryptography and Security · Computer Science 2024-10-24 Avishree Khare , Saikat Dutta , Ziyang Li , Alaia Solko-Breslin , Rajeev Alur , Mayur Naik

In this paper we present the first investigation into the effectiveness of Large Language Models (LLMs) for Failure Mode Classification (FMC). FMC, the task of automatically labelling an observation with a corresponding failure mode code,…

Computation and Language · Computer Science 2023-09-18 Michael Stewart , Melinda Hodkiewicz , Sirui Li

Large language models (LLMs) have achieved substantial progress in processing long contexts but still struggle with long-context reasoning. Existing approaches typically involve fine-tuning LLMs with synthetic data, which depends on…

Computation and Language · Computer Science 2024-11-14 Siheng Li , Cheng Yang , Zesen Cheng , Lemao Liu , Mo Yu , Yujiu Yang , Wai Lam

Large Language Models (LLMs) are increasingly used in intelligent systems that perform reasoning, summarization, and code generation. Their ability to follow natural-language instructions, while powerful, also makes them vulnerable to a new…

Cryptography and Security · Computer Science 2025-11-13 Daniyal Ganiuly , Assel Smaiyl

Unlocking the potential of Large Language Models (LLMs) in data classification represents a promising frontier in natural language processing. In this work, we evaluate the performance of different LLMs in comparison with state-of-the-art…

Computation and Language · Computer Science 2025-01-16 Arina Kostina , Marios D. Dikaiakos , Dimosthenis Stefanidis , George Pallis

Large language models (LLMs) have garnered significant attention across various research disciplines, including the wireless communication community. There have been several heated discussions on the intersection of LLMs and wireless…

Signal Processing · Electrical Eng. & Systems 2024-07-16 Yuyang Du , Hongyu Deng , Soung Chang Liew , Kexin Chen , Yulin Shao , He Chen

Providing effective feedback is important for student learning in programming problem-solving. In this sense, Large Language Models (LLMs) have emerged as potential tools to automate feedback generation. However, their reliability and…

Software Engineering · Computer Science 2025-03-20 Priscylla Silva , Evandro Costa

We explore the ability of large language models (LLMs) to act as speech recognition post-processors that perform rescoring and error correction. Our first focus is on instruction prompting to let LLMs perform these task without fine-tuning,…

Computation and Language · Computer Science 2024-01-29 Chao-Han Huck Yang , Yile Gu , Yi-Chieh Liu , Shalini Ghosh , Ivan Bulyko , Andreas Stolcke

Large language models (LLMs) exhibit a strong capacity for in-context learning: Given labeled examples, they can generate good predictions without parameter updates. However, many interactive settings go beyond static prediction to online…

Machine Learning · Computer Science 2026-05-12 Emile Anand , Abdullah Ateyeh , Xinyuan Cao , Max Dabagia

Large Language Models (LLMs) are transformer-based machine learning models that have shown remarkable performance in tasks for which they were not explicitly trained. Here, we explore the potential of LLMs to perform symbolic regression --…

Computation and Language · Computer Science 2026-04-17 Samiha Sharlin , Tyler R. Josephson

Large models (LMs), such as ChatGPT, have made a significant impact across diverse domains and hold great potential to facilitate the evolution of network intelligence. Wireless-native multi-modal large models (WMLMs) can sense and…

Networking and Internet Architecture · Computer Science 2025-12-01 Zhuoran Duan , Yuhao Wei , Guoshun Nan , Zijun Wang , Yan Yan , Lihua Xiong , Yuhan Ran , Ji Zhang , Jian Li , Qimei Cui , Xiaofeng Tao , Tony Q. S. Quek

Large Language Models (LLMs) have garnered considerable interest within both academic and industrial. Yet, the application of LLMs to graph data remains under-explored. In this study, we evaluate the capabilities of four LLMs in addressing…

Artificial Intelligence · Computer Science 2023-09-12 Chang Liu , Bo Wu

Large language models (LLMs) trained on huge corpora of text datasets demonstrate intriguing capabilities, achieving state-of-the-art performance on tasks they were not explicitly trained for. The precise nature of LLM capabilities is often…

Artificial Intelligence · Computer Science 2024-04-17 Eric J. Bigelow , Ekdeep Singh Lubana , Robert P. Dick , Hidenori Tanaka , Tomer D. Ullman

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

Large language models (LLMs) and large multimodal models (LMMs) have achieved unprecedented breakthrough, showcasing remarkable capabilities in natural language understanding, generation, and complex reasoning. This transformative potential…

Machine Learning · Computer Science 2025-10-24 Hyun Jong Yang , Hyunsoo Kim , Hyeonho Noh , Seungnyun Kim , Byonghyo Shim

Large Language Models (LLMs) have seen great advance in both academia and industry, and their popularity results in numerous open-source frameworks and techniques in accelerating LLM pre-training, fine-tuning, and inference. Training and…

Performance · Computer Science 2023-12-04 Longteng Zhang , Xiang Liu , Zeyu Li , Xinglin Pan , Peijie Dong , Ruibo Fan , Rui Guo , Xin Wang , Qiong Luo , Shaohuai Shi , Xiaowen Chu

Large language models (LLMs) have revolutionized natural language processing by achieving state-of-the-art performance across various tasks. Recently, their effectiveness as embedding models has gained attention, marking a paradigm shift…

Computation and Language · Computer Science 2025-07-28 Chongyang Tao , Tao Shen , Shen Gao , Junshuo Zhang , Zhen Li , Kai Hua , Wenpeng Hu , Zhengwei Tao , Shuai Ma