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相关论文: Trustworthy Large Models in Vision: A Survey

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Large Language Models (LLMs) have gained significant attention in the medical domain for their human-level capabilities, leading to increased efforts to explore their potential in various healthcare applications. However, despite such a…

The success of large language models (LLMs) has fostered a new research trend of multi-modality large language models (MLLMs), which changes the paradigm of various fields in computer vision. Though MLLMs have shown promising results in…

计算机视觉与模式识别 · 计算机科学 2024-06-12 Boyang Zheng , Jinjin Gu , Shijun Li , Chao Dong

Large Language Models (LLMs) represent an advanced evolution of earlier, simpler language models. They boast enhanced abilities to handle complex language patterns and generate coherent text, images, audios, and videos. Furthermore, they…

密码学与安全 · 计算机科学 2024-03-01 Jun Huang , Jiawei Zhang , Qi Wang , Weihong Han , Yanchun Zhang

With the advent of Large Language Models (LLMs), medical artificial intelligence (AI) has experienced substantial technological progress and paradigm shifts, highlighting the potential of LLMs to streamline healthcare delivery and improve…

计算与语言 · 计算机科学 2024-12-10 Lei Liu , Xiaoyan Yang , Junchi Lei , Yue Shen , Jian Wang , Peng Wei , Zhixuan Chu , Zhan Qin , Kui Ren

Large Language Models (LLMs) are increasingly applied to medical imaging tasks, including image interpretation and synthetic image generation. However, these models often produce hallucinations, which are confident but incorrect outputs…

图像与视频处理 · 电气工程与系统科学 2025-08-12 Anindya Bijoy Das , Shahnewaz Karim Sakib , Shibbir Ahmed

Large language models (LLMs) have significantly transformed the landscape of Natural Language Processing (NLP). Their impact extends across a diverse spectrum of tasks, revolutionizing how we approach language understanding and generations.…

密码学与安全 · 计算机科学 2025-06-13 Sara Abdali , Richard Anarfi , CJ Barberan , Jia He , Erfan Shayegani

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generation capabilities. Despite their remarkable performance, LLMs…

Large Vision-Language Models (LVLMs) have shown impressive performance in various tasks. However, LVLMs suffer from hallucination, which hinders their adoption in the real world. Existing studies emphasized that the strong language priors…

计算机视觉与模式识别 · 计算机科学 2025-02-19 Zongyu Wu , Yuwei Niu , Hongcheng Gao , Minhua Lin , Zhiwei Zhang , Zhifang Zhang , Qi Shi , Yilong Wang , Sike Fu , Junjie Xu , Junjie Ao , Enyan Dai , Lei Feng , Xiang Zhang , Suhang Wang

Advances in deep learning systems have allowed large models to match or surpass human accuracy on a number of skills such as image classification, basic programming, and standardized test taking. As the performance of the most capable…

机器学习 · 计算机科学 2024-06-10 Sarah Pratt , Seth Blumberg , Pietro Kreitlon Carolino , Meredith Ringel Morris

Large Language Models have taken the cognitive science world by storm. It is perhaps timely now to take stock of the various research paradigms that have been used to make scientific inferences about ``cognition" in these models or about…

人工智能 · 计算机科学 2024-06-17 Desmond C. Ong

The emergence of large language models (LLMs) has marked a significant breakthrough in natural language processing (NLP), fueling a paradigm shift in information acquisition. Nevertheless, LLMs are prone to hallucination, generating…

Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, their…

Large Language Models (LLMs) have emerged as a promising cornerstone for the development of natural language processing (NLP) and artificial intelligence (AI). However, ensuring the robustness of LLMs remains a critical challenge. To…

计算与语言 · 计算机科学 2025-11-07 Pankaj Kumar , Subhankar Mishra

Language and Vision-Language Models (LLMs/VLMs) have revolutionized the field of AI by their ability to generate human-like text and understand images, but ensuring their reliability is crucial. This paper aims to evaluate the ability of…

计算机视觉与模式识别 · 计算机科学 2024-05-07 Tobias Groot , Matias Valdenegro-Toro

Robustness against uncertain and ambiguous inputs is a critical challenge for deep learning models. While recent advancements in large scale vision language models (VLMs, e.g. GPT4o) might suggest that increasing model and training dataset…

计算机视觉与模式识别 · 计算机科学 2025-05-20 Xi Wang , Eric Nalisnick

Large Language Models (LLMs) have quickly risen to prominence due to their ability to perform at or close to the state-of-the-art in a variety of fields while handling natural language. An important field of research is the application of…

密码学与安全 · 计算机科学 2024-02-28 Gabriel de Jesus Coelho da Silva , Carlos Becker Westphall

The advent of Large Language Models (LLMs) has garnered significant popularity and wielded immense power across various domains within Natural Language Processing (NLP). While their capabilities are undeniably impressive, it is crucial to…

机器学习 · 计算机科学 2024-07-31 Sara Abdali , Jia He , CJ Barberan , Richard Anarfi

Large Language Models (LLMs) trained on extensive textual corpora have emerged as leading solutions for a broad array of Natural Language Processing (NLP) tasks. Despite their notable performance, these models are prone to certain…

计算与语言 · 计算机科学 2023-07-25 Yufei Wang , Wanjun Zhong , Liangyou Li , Fei Mi , Xingshan Zeng , Wenyong Huang , Lifeng Shang , Xin Jiang , Qun Liu

Machine learning can provide deep insights into data, allowing machines to make high-quality predictions and having been widely used in real-world applications, such as text mining, visual classification, and recommender systems. However,…

机器学习 · 计算机科学 2020-08-11 Meng Wang , Weijie Fu , Xiangnan He , Shijie Hao , Xindong Wu

Large Language Models (LLMs) have shown impressive potential to simulate human behavior. We identify a fundamental challenge in using them to simulate experiments: when LLM-simulated subjects are blind to the experimental design (as is…

人工智能 · 计算机科学 2025-11-25 George Gui , Olivier Toubia