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Large Language Models (LLMs) have attained the impressive capability to resolve a wide range of NLP tasks by fine-tuning high-quality instruction data. However, collecting human-written data of high quality, especially multi-turn dialogues,…

Computation and Language · Computer Science 2023-10-20 Dongjie Yang , Ruifeng Yuan , Yuantao Fan , Yifei Yang , Zili Wang , Shusen Wang , Hai Zhao

Interacting with human via high-quality multi-turn dialogues is a key feature of large language models (LLMs). However, human-based evaluation of such capability involves intensive manual labor. This report provides a preliminary evaluation…

Computation and Language · Computer Science 2023-10-23 Haodong Duan , Jueqi Wei , Chonghua Wang , Hongwei Liu , Yixiao Fang , Songyang Zhang , Dahua Lin , Kai Chen

Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific task. While typically task-agnostic in architecture, this method still requires…

NLP models today strive for supporting multiple languages and modalities, improving accessibility for diverse users. In this paper, we evaluate their multilingual, multimodal capabilities by testing on a visual reasoning task. We observe…

Computation and Language · Computer Science 2025-02-11 Yueqi Song , Simran Khanuja , Graham Neubig

Large Language Models (LLMs) possess human-level cognitive and decision-making capabilities, making them a key technology for 6G. However, applying LLMs to the communication domain faces three major challenges: 1) Inadequate communication…

Information Theory · Computer Science 2025-02-27 Feibo Jiang , Wanyun Zhu , Li Dong , Kezhi Wang , Kun Yang , Cunhua Pan , Octavia A. Dobre

The remarkable multimodal capabilities and interactive experience of GPT-4o underscore their necessity in practical applications, yet open-source models rarely excel in both areas. In this paper, we introduce VITA, the first-ever…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Chaoyou Fu , Haojia Lin , Zuwei Long , Yunhang Shen , Yuhang Dai , Meng Zhao , Yi-Fan Zhang , Shaoqi Dong , Yangze Li , Xiong Wang , Haoyu Cao , Di Yin , Long Ma , Xiawu Zheng , Rongrong Ji , Yunsheng Wu , Ran He , Caifeng Shan , Xing Sun

Guiding users through complex procedural plans is an inherently multimodal task in which having visually illustrated plan steps is crucial to deliver an effective plan guidance. However, existing works on plan-following language models…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Diogo Glória-Silva , David Semedo , João Magalhães

Humans often interact with large language models (LLMs) in multi-turn interaction to obtain desired answers or more information. However, most existing studies overlook the multi-turn instruction following ability of LLMs, in terms of…

Computation and Language · Computer Science 2024-05-24 Yuchong Sun , Che Liu , Kun Zhou , Jinwen Huang , Ruihua Song , Wayne Xin Zhao , Fuzheng Zhang , Di Zhang , Kun Gai

Dialogue-based language models mark a huge milestone in the field of artificial intelligence, by their impressive ability to interact with users, as well as a series of challenging tasks prompted by customized instructions. However, the…

Artificial Intelligence · Computer Science 2023-04-26 Rui Hao , Linmei Hu , Weijian Qi , Qingliu Wu , Yirui Zhang , Liqiang Nie

Large language models (LLMs) like ChatGPT have exhibited remarkable abilities on a wide range of natural language processing~(NLP) tasks, including various machine translation abilities accomplished during chat. However, these models are…

Computation and Language · Computer Science 2023-11-03 Wenxiang Jiao , Jen-tse Huang , Wenxuan Wang , Zhiwei He , Tian Liang , Xing Wang , Shuming Shi , Zhaopeng Tu

Considerable progress has been made towards conversational models that generate coherent and fluent responses by training large language models on large dialogue datasets. These models have little or no control of the generated responses…

Computation and Language · Computer Science 2020-10-22 Andrea Madotto , Zhaojiang Lin , Yejin Bang , Pascale Fung

This paper evaluates the extent to which current Large Language Models (LLMs) can capture task-oriented multi-party conversations (MPCs). We have recorded and transcribed 29 MPCs between patients, their companions, and a social robot in a…

Computation and Language · Computer Science 2023-08-30 Angus Addlesee , Weronika Sieińska , Nancie Gunson , Daniel Hernández Garcia , Christian Dondrup , Oliver Lemon

Multimodal Large Language Models (MLLMs) demonstrate remarkable performance across a wide range of domains, with increasing emphasis on enhancing their zero-shot generalization capabilities for unseen tasks across various modalities.…

Large-scale language models (LLMs), such as ChatGPT, are becoming increasingly sophisticated and exhibit human-like capabilities, playing an essential role in assisting humans in a variety of everyday tasks. An important application of AI…

Computers and Society · Computer Science 2023-12-07 Yugen Sato , Taisei Nakajima , Tatsuki Kawamoto , Tomohiro Takagi

We explore Multimodal Large Language Models (MLLMs), which integrate LLMs like GPT-4 to handle multimodal data, including text, images, audio, and more. MLLMs demonstrate capabilities such as generating image captions and answering…

Computation and Language · Computer Science 2025-01-09 Shezheng Song , Xiaopeng Li , Shasha Li , Shan Zhao , Jie Yu , Jun Ma , Xiaoguang Mao , Weimin Zhang

GPT-4o, an all-encompassing model, represents a milestone in the development of large multi-modal language models. It can understand visual, auditory, and textual modalities, directly output audio, and support flexible duplex interaction.…

Audio and Speech Processing · Electrical Eng. & Systems 2024-11-06 Zhifei Xie , Changqiao Wu

Human preference alignment can greatly enhance Multimodal Large Language Models (MLLMs), but collecting high-quality preference data is costly. A promising solution is the self-evolution strategy, where models are iteratively trained on…

Machine Learning · Computer Science 2024-12-23 Wentao Tan , Qiong Cao , Yibing Zhan , Chao Xue , Changxing Ding

ChatGPT is attracting a cross-field interest as it provides a language interface with remarkable conversational competency and reasoning capabilities across many domains. However, since ChatGPT is trained with languages, it is currently not…

Computer Vision and Pattern Recognition · Computer Science 2023-03-09 Chenfei Wu , Shengming Yin , Weizhen Qi , Xiaodong Wang , Zecheng Tang , Nan Duan

Human communication is inherently multimodal, involving a combination of verbal and non-verbal cues such as speech, facial expressions, and body gestures. Modeling these behaviors is essential for understanding human interaction and for…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Changan Chen , Juze Zhang , Shrinidhi K. Lakshmikanth , Yusu Fang , Ruizhi Shao , Gordon Wetzstein , Li Fei-Fei , Ehsan Adeli

While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides, they mostly fall prey to the limitation of only input-side multimodal understanding, without the ability to produce content in multiple modalities. As we…

Artificial Intelligence · Computer Science 2024-06-26 Shengqiong Wu , Hao Fei , Leigang Qu , Wei Ji , Tat-Seng Chua