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Recent advancements in multimodal techniques open exciting possibilities for models excelling in diverse tasks involving text, audio, and image processing. Models like GPT-4V, blending computer vision and language modeling, excel in complex…

Computation and Language · Computer Science 2023-10-20 Xiang Zhang , Senyu Li , Zijun Wu , Ning Shi

Although instruction-tuned large language models (LLMs) have exhibited remarkable capabilities across various NLP tasks, their effectiveness on other data modalities beyond text has not been fully studied. In this work, we propose…

Computation and Language · Computer Science 2023-06-16 Chenyang Lyu , Minghao Wu , Longyue Wang , Xinting Huang , Bingshuai Liu , Zefeng Du , Shuming Shi , Zhaopeng Tu

This paper explores the potential of leveraging Large Language Models (LLMs) for data augmentation in multilingual commonsense reasoning datasets where the available training data is extremely limited. To achieve this, we utilise several…

Computation and Language · Computer Science 2023-10-24 Chenxi Whitehouse , Monojit Choudhury , Alham Fikri Aji

The disruptive technology provided by large-scale pre-trained language models (LLMs) such as ChatGPT or GPT-4 has received significant attention in several application domains, often with an emphasis on high-level opportunities and…

Human-Computer Interaction · Computer Science 2023-06-27 Philippe J. Giabbanelli

We introduce X-VILA, an omni-modality model designed to extend the capabilities of large language models (LLMs) by incorporating image, video, and audio modalities. By aligning modality-specific encoders with LLM inputs and diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Hanrong Ye , De-An Huang , Yao Lu , Zhiding Yu , Wei Ping , Andrew Tao , Jan Kautz , Song Han , Dan Xu , Pavlo Molchanov , Hongxu Yin

By integrating the perception capabilities of multimodal encoders with the generative power of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), exemplified by GPT-4V, have achieved great success in various multimodal…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Wenbin An , Jiahao Nie , Yaqiang Wu , Feng Tian , Shijian Lu , Qinghua Zheng

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

Extremely large-scale massive multiple-input multiple-output (XL-MIMO) is a key enabler for sixth-generation (6G) networks, offering massive spatial degrees of freedom. Despite these advantages, the coexistence of near-field and far-field…

Machine Learning · Computer Science 2025-12-11 Renbin Li , Shuangshuang Li , Peihao Dong

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among…

Computation and Language · Computer Science 2023-08-01 Hanyao Huang , Ou Zheng , Dongdong Wang , Jiayi Yin , Zijin Wang , Shengxuan Ding , Heng Yin , Chuan Xu , Renjie Yang , Qian Zheng , Bing Shi

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 demonstrated exceptional natural language understanding abilities and have excelled in a variety of natural language processing (NLP)tasks in recent years. Despite the fact that most LLMs are trained…

Computation and Language · Computer Science 2023-10-25 Xiang Zhang , Senyu Li , Bradley Hauer , Ning Shi , Grzegorz Kondrak

Multimodal large language models (MLLMs) have gained significant attention due to their strong multimodal understanding capability. However, existing works rely heavily on modality-specific encoders, which usually differ in architecture and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Jiaming Han , Kaixiong Gong , Yiyuan Zhang , Jiaqi Wang , Kaipeng Zhang , Dahua Lin , Yu Qiao , Peng Gao , Xiangyu Yue

Instruction tuning large language models (LLMs) using machine-generated instruction-following data has improved zero-shot capabilities on new tasks, but the idea is less explored in the multimodal field. In this paper, we present the first…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Haotian Liu , Chunyuan Li , Qingyang Wu , Yong Jae Lee

Multimodal large language models (MLLMs) have shown remarkable performance in vision-language tasks. However, existing MLLMs are primarily trained on generic datasets, limiting their ability to reason on domain-specific visual cues such as…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Hatef Otroshi Shahreza , Sébastien Marcel

Large language models (LLMs) constitute a breakthrough state-of-the-art Artificial Intelligence technology which is rapidly evolving and promises to aid in medical diagnosis. However, the correctness and the accuracy of their returns has…

Computation and Language · Computer Science 2024-02-07 Dimitrios P. Panagoulias , Maria Virvou , George A. Tsihrintzis

This study explores the application of Large Language Models (LLMs), specifically GPT-4, in the analysis of classroom dialogue, a crucial research task for both teaching diagnosis and quality improvement. Recognizing the knowledge-intensive…

Computation and Language · Computer Science 2024-10-08 Yun Long , Haifeng Luo , Yu Zhang

To democratize large language models (LLMs) to most natural languages, it is imperative to make these models capable of understanding and generating texts in many languages, in particular low-resource ones. While recent multilingual LLMs…

Computation and Language · Computer Science 2024-06-05 Wen Lai , Mohsen Mesgar , Alexander Fraser

Rapidly developing large language models (LLMs) have brought tremendous intelligent applications. Especially, the GPT-4o's excellent duplex speech interaction ability has brought impressive experience to users. Researchers have recently…

Sound · Computer Science 2024-12-10 Xiong Wang , Yangze Li , Chaoyou Fu , Yunhang Shen , Lei Xie , Ke Li , Xing Sun , Long Ma

Visual storytelling is an emerging field that combines images and narratives to create engaging and contextually rich stories. Despite its potential, generating coherent and emotionally resonant visual stories remains challenging due to the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Xiaochuan Lin , Xiangyong Chen

With the emergence of large language models (LLMs), multimodal models based on LLMs have demonstrated significant potential. Models such as LLaSM, X-LLM, and SpeechGPT exhibit an impressive ability to comprehend and generate human…

Computation and Language · Computer Science 2023-10-04 Hao Zhang , Nianwen Si , Yaqi Chen , Wenlin Zhang , Xukui Yang , Dan Qu , Xiaolin Jiao