中文
相关论文

相关论文: Future of AI Models: A Computational perspective o…

200 篇论文

Large language models (LLMs) are remarkable data annotators. They can be used to generate high-fidelity supervised training data, as well as survey and experimental data. With the widespread adoption of LLMs, human gold--standard…

计算与语言 · 计算机科学 2023-06-14 Veniamin Veselovsky , Manoel Horta Ribeiro , Robert West

Scientific breakthroughs typically emerge through the surprising violation of established research ideas, yet quantifying surprise has remained elusive because it requires a coherent model of all contemporary scientific worldviews. Deep…

社会与信息网络 · 计算机科学 2025-09-09 Zhen Zhang , James Evans

Cutting-edge Artificial Intelligence (AI) techniques keep reshaping our view of the world. For example, Large Language Models (LLMs) based applications such as ChatGPT have shown the capability of generating human-like conversation on…

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,…

The potentials of Generative-AI technologies like Large Language models (LLMs) to revolutionize education are undermined by ethical considerations around their misuse which worsens the problem of academic dishonesty. LLMs like GPT-4 and…

机器学习 · 计算机科学 2024-07-11 Suriya Prakash Jambunathan , Ashwath Shankarnarayan , Parijat Dube

Large language models (LLMs) have rapidly emerged in civil and environmental engineering (CEE) research, education, and practice as tools for project ideation, execution, and communication. However, it is unknown how prevalent LLM adoption…

数字图书馆 · 计算机科学 2026-03-17 Morgan D. Sanger , Brett W. Maurer

The emergence of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) has marked a new era of Natural Language Processing (NLP), introducing unprecedented capabilities that are revolutionizing various domains. This paper…

计算与语言 · 计算机科学 2024-08-26 Desta Haileselassie Hagos , Rick Battle , Danda B. Rawat

The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large…

Large language models (LLMs) are increasingly employed for decision-support across multiple domains. We investigate whether these models display a systematic preferential bias in favor of artificial intelligence (AI) itself. Across three…

计算与语言 · 计算机科学 2026-01-21 Benaya Trabelsi , Jonathan Shaki , Sarit Kraus

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 rapid advancement of Large Language Models (LLMs) has generated considerable speculation regarding their transformative potential for labor markets. However, existing approaches to measuring AI exposure in the workforce predominantly…

计算机与社会 · 计算机科学 2025-11-21 Shurui Cao , Wenyue Hua , William Yang Wang , Hong Shen , Fei Fang

Large Language Models (LLMs) have drawn a lot of attention due to their strong performance on a wide range of natural language tasks, since the release of ChatGPT in November 2022. LLMs' ability of general-purpose language understanding and…

计算与语言 · 计算机科学 2025-03-25 Shervin Minaee , Tomas Mikolov , Narjes Nikzad , Meysam Chenaghlu , Richard Socher , Xavier Amatriain , Jianfeng Gao

Large language models (LLMs) have recently become a popular topic in the field of Artificial Intelligence (AI) research, with companies such as Google, Amazon, Facebook, Amazon, Tesla, and Apple (GAFA) investing heavily in their…

Modern Artificial Intelligence applications show great potential for language-related tasks that rely on next-word prediction. The current generation of Large Language Models (LLMs) have been linked to claims about human-like linguistic…

计算与语言 · 计算机科学 2024-09-05 Evelina Leivada , Gary Marcus , Fritz Günther , Elliot Murphy

Large Language Models (LLMs) have delivered impressive results in language understanding, generation, reasoning, and pushes the ability boundary of multimodal models. Transformer models, as the foundation of modern LLMs, offer a strong…

In the rapidly evolving landscape of artificial intelligence (AI), generative large language models (LLMs) stand at the forefront, revolutionizing how we interact with our data. However, the computational intensity and memory consumption of…

机器学习 · 计算机科学 2025-07-24 Xupeng Miao , Gabriele Oliaro , Zhihao Zhang , Xinhao Cheng , Hongyi Jin , Tianqi Chen , Zhihao Jia

As Large Language Models (LLMs) continue to advance in their ability to write human-like text, a key challenge remains around their tendency to hallucinate generating content that appears factual but is ungrounded. This issue of…

计算与语言 · 计算机科学 2024-01-09 S. M Towhidul Islam Tonmoy , S M Mehedi Zaman , Vinija Jain , Anku Rani , Vipula Rawte , Aman Chadha , Amitava Das

Large Language Models (LLMs) have ushered in a transformative era in Natural Language Processing (NLP), reshaping research and extending NLP's influence to other fields of study. However, there is little to no work examining the degree to…

计算与语言 · 计算机科学 2024-10-01 Aniket Pramanick , Yufang Hou , Saif M. Mohammad , Iryna Gurevych

Large language models (LLMs) have revolutionized natural language processing, yet their propensity for hallucination, generating plausible but factually incorrect or fabricated content, remains a critical challenge. This report provides a…

计算与语言 · 计算机科学 2025-08-05 Manuel Cossio

While artificial intelligence has the potential to process vast amounts of data, generate new insights, and unlock greater productivity, its widespread adoption may entail unforeseen consequences. We identify conditions under which AI, by…

人工智能 · 计算机科学 2025-01-22 Andrew J. Peterson