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In recent years, multimodal large language models (MLLMs) have achieved significant breakthroughs, enhancing understanding across text and vision. However, current MLLMs still face challenges in effectively integrating knowledge across…

Computation and Language · Computer Science 2025-03-10 Boyu Jia , Junzhe Zhang , Huixuan Zhang , Xiaojun Wan

Large Language Models (LLMs) excel in linguistic tasks but struggle with mathematical reasoning, particularly in non English languages like Hindi. This research aims to enhance the mathematical reasoning skills of smaller, resource…

Computation and Language · Computer Science 2024-12-25 Avinash Anand , Kritarth Prasad , Chhavi Kirtani , Ashwin R Nair , Manvendra Kumar Nema , Raj Jaiswal , Rajiv Ratn Shah

Clinical document classification is essential for converting unstructured medical texts into standardised ICD-10 diagnoses, yet it faces challenges due to complex medical language, privacy constraints, and limited annotated datasets. Large…

Computation and Language · Computer Science 2026-02-03 Akram Mustafa , Usman Naseem , Mostafa Rahimi Azghadi

Multimodal scientific reasoning remains a significant challenge for large language models (LLMs), particularly in chemistry, where problem-solving relies on symbolic diagrams, molecular structures, and structured visual data. Here, we…

Computation and Language · Computer Science 2025-12-18 Yiming Cui , Xin Yao , Yuxuan Qin , Xin Li , Shijin Wang , Guoping Hu

While Multimodal Large Language Models (MLLMs) show immense promise for achieving truly human-like interactions, progress is hindered by the lack of fine-grained evaluation frameworks for human-centered scenarios, encompassing both the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Zheng Qin , Ruobing Zheng , Yabing Wang , Tianqi Li , Yi Yuan , Jingdong Chen , Le Wang

Large multimodal language models (MLLMs) such as GPT-4V and GPT-4o have achieved remarkable advancements in understanding and generating multimodal content, showcasing superior quality and capabilities across diverse tasks. However, their…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Xuelu Feng , Yunsheng Li , Dongdong Chen , Mei Gao , Mengchen Liu , Junsong Yuan , Chunming Qiao

In this paper, we assess the visualization literacy of two prominent Large Language Models (LLMs): OpenAI's Generative Pretrained Transformers (GPT), the backend of ChatGPT, and Google's Gemini, previously known as Bard, to establish…

Performance · Computer Science 2025-01-28 Jiayi Hong , Christian Seto , Arlen Fan , Ross Maciejewski

The rapid advancement of Large Language Models (LLMs) in the realm of mathematical reasoning necessitates comprehensive evaluations to gauge progress and inspire future directions. Existing assessments predominantly focus on problem-solving…

Computation and Language · Computer Science 2024-06-05 Xiaoyuan Li , Wenjie Wang , Moxin Li , Junrong Guo , Yang Zhang , Fuli Feng

The rapid advancement of multimodal large language models (MLLMs) has profoundly impacted the document domain, creating a wide array of application scenarios. This progress highlights the need for a comprehensive benchmark to evaluate these…

Computation and Language · Computer Science 2025-05-23 Siqi Li , Yufan Shen , Xiangnan Chen , Jiayi Chen , Hengwei Ju , Haodong Duan , Song Mao , Hongbin Zhou , Bo Zhang , Bin Fu , Pinlong Cai , Licheng Wen , Botian Shi , Yong Liu , Xinyu Cai , Yu Qiao

Big Language Models (LLMs) are changing the way businesses use software, the way people live their lives and the way industries work. Companies like Google, High-Flyer, Anthropic, OpenAI and Meta are making better LLMs. So, it's crucial to…

Artificial Intelligence · Computer Science 2025-10-28 Urja Kohli , Aditi Singh , Arun Sharma

We present GLM-4.1V-Thinking, GLM-4.5V, and GLM-4.6V, a family of vision-language models (VLMs) designed to advance general-purpose multimodal understanding and reasoning. In this report, we share our key findings in the development of the…

Scientific reasoning, the process through which humans apply logic, evidence, and critical thinking to explore and interpret scientific phenomena, is essential in advancing knowledge reasoning across diverse fields. However, despite…

Computation and Language · Computer Science 2026-04-21 Yibo Yan , Shen Wang , Jiahao Huo , Jingheng Ye , Zhendong Chu , Xuming Hu , Philip S. Yu , Carla Gomes , Bart Selman , Qingsong Wen

Recently, Multimodal Large Language Model (MLLM) represented by GPT-4V has been a new rising research hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform multimodal tasks. The surprising emergent capabilities of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Shukang Yin , Chaoyou Fu , Sirui Zhao , Ke Li , Xing Sun , Tong Xu , Enhong Chen

Multimodal Large Language Models (MLLMs) have exhibited remarkable advancements in integrating different modalities, excelling in complex understanding and generation tasks. Despite their success, MLLMs remain vulnerable to conversational…

Computation and Language · Computer Science 2025-10-09 Bin Zhu , Yinxuan Gui , Huiyan Qi , Jingjing Chen , Chong-Wah Ngo , Ee-Peng Lim

This paper examines the reasoning capabilities of Large Language Models (LLMs) from a novel perspective, focusing on their ability to operate within formally specified, rule-governed environments. We evaluate four LLMs (Gemini 2.5 Pro and…

Artificial Intelligence · Computer Science 2026-02-24 Maciej Świechowski , Adam Żychowski , Jacek Mańdziuk

Medical images and radiology reports are crucial for diagnosing medical conditions, highlighting the importance of quantitative analysis for clinical decision-making. However, the diversity and cross-source heterogeneity of these data…

Image and Video Processing · Electrical Eng. & Systems 2024-07-09 Yutong Zhang , Yi Pan , Tianyang Zhong , Peixin Dong , Kangni Xie , Yuxiao Liu , Hanqi Jiang , Zhengliang Liu , Shijie Zhao , Tuo Zhang , Xi Jiang , Dinggang Shen , Tianming Liu , Xin Zhang

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) exhibit expert-level performance in tasks across a wide range of different domains. Ethical issues raised by LLMs and the need to align future versions makes it important to know how state of the art models…

Artificial Intelligence · Computer Science 2024-05-24 Guilherme F. C. F. Almeida , José Luiz Nunes , Neele Engelmann , Alex Wiegmann , Marcelo de Araújo

Large Language Models (LLMs) like GPT-4 and Gemini have significantly advanced artificial intelligence by enabling machines to generate and comprehend human-like text. Despite their impressive capabilities, LLMs are not immune to…

Computation and Language · Computer Science 2024-12-19 Jiaxu Lou , Yifan Sun

As a prominent direction of Artificial General Intelligence (AGI), Multimodal Large Language Models (MLLMs) have garnered increased attention from both industry and academia. Building upon pre-trained LLMs, this family of models further…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Chaoyou Fu , Yi-Fan Zhang , Shukang Yin , Bo Li , Xinyu Fang , Sirui Zhao , Haodong Duan , Xing Sun , Ziwei Liu , Liang Wang , Caifeng Shan , Ran He