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Related papers: On Path to Multimodal Generalist: General-Level an…

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While large language models (LLMs) are still being adopted to new domains and utilized in novel applications, we are experiencing an influx of the new generation of foundation models, namely multi-modal large language models (MLLMs). These…

Computation and Language · Computer Science 2024-08-23 Kian Ahrabian , Zhivar Sourati , Kexuan Sun , Jiarui Zhang , Yifan Jiang , Fred Morstatter , Jay Pujara

In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventional single- and multi-class AD, general AD aims to train a general AD model that can…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Xincheng Yao , Zefeng Qian , Chao Shi , Jiayang Song , Chongyang Zhang

The advancement of Multimodal Large Language Models (MLLMs) has greatly accelerated the development of applications in understanding integrated texts and images. Recent works leverage image-caption datasets to train MLLMs, achieving…

Computation and Language · Computer Science 2024-11-22 Mingxu Tao , Quzhe Huang , Kun Xu , Liwei Chen , Yansong Feng , Dongyan Zhao

The rapid advancement of Large Language Models (LLMs) has outpaced the scalability of traditional evaluation benchmarks, which remain heavily dependent on labor-intensive expert curation. We address this bottleneck with Conv-to-Bench, a…

Based on the foundation of Large Language Models (LLMs), Multilingual LLMs (MLLMs) have been developed to address the challenges faced in multilingual natural language processing, hoping to achieve knowledge transfer from high-resource…

Computation and Language · Computer Science 2024-12-10 Yuemei Xu , Ling Hu , Jiayi Zhao , Zihan Qiu , Kexin XU , Yuqi Ye , Hanwen Gu

The rapid development of large language models (LLMs) has been witnessed in recent years. Based on the powerful LLMs, multi-modal LLMs (MLLMs) extend the modality from text to a broader spectrum of domains, attracting widespread attention…

Artificial Intelligence · Computer Science 2024-08-06 Zhen Qin , Daoyuan Chen , Wenhao Zhang , Liuyi Yao , Yilun Huang , Bolin Ding , Yaliang Li , Shuiguang Deng

Since the release of ChatGPT and GPT-4, large language models (LLMs) and multimodal large language models (MLLMs) have attracted widespread attention for their exceptional capabilities in understanding, reasoning, and generation,…

Computation and Language · Computer Science 2024-12-31 Hanguang Xiao , Feizhong Zhou , Xingyue Liu , Tianqi Liu , Zhipeng Li , Xin Liu , Xiaoxuan Huang

With the increasing integration of visual and textual content in Social Networking Services (SNS), evaluating the multimodal capabilities of Large Language Models (LLMs) is crucial for enhancing user experience, content understanding, and…

Computation and Language · Computer Science 2025-12-16 Hongcheng Guo , Zheyong Xie , Shaosheng Cao , Boyang Wang , Weiting Liu , Anjie Le , Lei Li , Zhoujun Li

With the rapid advancement of Multimodal Large Language Models (MLLMs), a variety of benchmarks have been introduced to evaluate their capabilities. While most evaluations have focused on complex tasks such as scientific comprehension and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Huan Liu , Lingyu Xiao , Jiangjiang Liu , Xiaofan Li , Ze Feng , Sen Yang , Jingdong Wang

Multilingual large language models (LLMs) possess impressive multilingual understanding and generation capabilities. However, their performance and cross-lingual alignment often lag for non-dominant languages. A common solution is to…

Computation and Language · Computer Science 2025-09-30 Mengyu Bu , Shaolei Zhang , Zhongjun He , Hua Wu , Yang Feng

Although great progress has been made by previous table understanding methods including recent approaches based on large language models (LLMs), they rely heavily on the premise that given tables must be converted into a certain text…

Computation and Language · Computer Science 2024-06-13 Mingyu Zheng , Xinwei Feng , Qingyi Si , Qiaoqiao She , Zheng Lin , Wenbin Jiang , Weiping Wang

The rise of generative large language models (LLMs) has opened new opportunities for automating knowledge representation through concept maps, a long-standing pedagogical tool valued for fostering meaningful learning and higher-order…

Computers and Society · Computer Science 2025-09-19 Xiaoming Zhai

Although multimodal large language models (MLLMs) have achieved promising results on a wide range of vision-language tasks, their ability to perceive and understand human faces is rarely explored. In this work, we comprehensively evaluate…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Haomiao Sun , Mingjie He , Tianheng Lian , Hu Han , Shiguang Shan

Multimodal Large Language Models (MLLMs) have shown impressive abilities in interacting with visual content with myriad potential downstream tasks. However, even though a list of benchmarks has been proposed, the capabilities and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Zhelun Shi , Zhipin Wang , Hongxing Fan , Zhenfei Yin , Lu Sheng , Yu Qiao , Jing Shao

Recent advancements in Large Language Models (LLMs) have demonstrated remarkable capabilities in various domains. However, effective decision-making relies heavily on strong reasoning abilities. Reasoning is the foundation for…

Computation and Language · Computer Science 2025-06-30 Dana Alsagheer , Yang Lu , Abdulrahman Kamal , Omar Kamal , Mohammad Kamal , Nada Mansour , Cosmo Yang Wu , Rambiba Karanjai , Sen Li , Weidong Shi

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by…

Computation and Language · Computer Science 2023-10-31 Yizhe Yang , Huashan Sun , Jiawei Li , Runheng Liu , Yinghao Li , Yuhang Liu , Heyan Huang , Yang Gao

The advancement of Large Language Models (LLMs) has remarkably pushed the boundaries towards artificial general intelligence (AGI), with their exceptional ability on understanding diverse types of information, including but not limited to…

Computation and Language · Computer Science 2023-10-10 Ziwei Chai , Tianjie Zhang , Liang Wu , Kaiqiao Han , Xiaohai Hu , Xuanwen Huang , Yang Yang

The planning ability of Large Language Models (LLMs) has garnered increasing attention in recent years due to their remarkable capacity for multi-step reasoning and their ability to generalize across a wide range of domains. While some…

Artificial Intelligence · Computer Science 2025-02-19 Mohamed Aghzal , Erion Plaku , Gregory J. Stein , Ziyu Yao

Large multimodal models (LMMs) extend large language models (LLMs) with multi-sensory skills, such as visual understanding, to achieve stronger generic intelligence. In this paper, we analyze the latest model, GPT-4V(ision), to deepen the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Zhengyuan Yang , Linjie Li , Kevin Lin , Jianfeng Wang , Chung-Ching Lin , Zicheng Liu , Lijuan Wang

Large Language Models (LLMs) are rapidly transforming various fields, and their potential in Business Process Management (BPM) is substantial. This paper assesses the capabilities of LLMs on business process modeling using a framework for…

Databases · Computer Science 2024-12-03 Humam Kourani , Alessandro Berti , Daniel Schuster , Wil M. P. van der Aalst
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