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Related papers: Gemini in Reasoning: Unveiling Commonsense in Mult…

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Mathematical reasoning, a core aspect of human cognition, is vital across many domains, from educational problem-solving to scientific advancements. As artificial general intelligence (AGI) progresses, integrating large language models…

Computation and Language · Computer Science 2025-05-21 Yibo Yan , Jiamin Su , Jianxiang He , Fangteng Fu , Xu Zheng , Yuanhuiyi Lyu , Kun Wang , Shen Wang , Qingsong Wen , Xuming Hu

Large Language Models (LLMs) have shown impressive performance on a range of educational tasks, but are still understudied for their potential to solve mathematical problems. In this study, we compare three prominent LLMs, including GPT-4o,…

Artificial Intelligence · Computer Science 2025-07-01 Ruonan Wang , Runxi Wang , Yunwen Shen , Chengfeng Wu , Qinglin Zhou , Rohitash Chandra

The exponential growth of information presents a significant challenge for researchers and professionals seeking to remain at the forefront of their fields and this paper introduces an innovative framework for automatically generating…

Computational Engineering, Finance, and Science · Computer Science 2025-10-30 Andrei Lazarev , Dmitrii Sedov

The explorations and applications of Artificial Intelligence (AI) in various domains becomes increasingly vital as it continues to evolve. While much attention has been focused on Large Language Models (LLMs) such as ChatGPT, this research…

Computers and Society · Computer Science 2025-02-28 Julius Sechang Mboli , John G. O. Marko , Rose Anazin Yemson

While large multi-modal models (LMM) have shown notable progress in multi-modal tasks, their capabilities in tasks involving dense textual content remains to be fully explored. Dense text, which carries important information, is often found…

Computation and Language · Computer Science 2024-05-14 Shuo Zhang , Biao Yang , Zhang Li , Zhiyin Ma , Yuliang Liu , Xiang Bai

Understanding the limitations of Large Language Models, or LLMs, in mathematical reasoning has been the focus of several recent studies. However, the majority of these studies use the same datasets for benchmarking, which limits the…

Artificial Intelligence · Computer Science 2026-01-01 Samuel Golladay , Majid Bani-Yaghoub

Multimodal large language models (MLLMs) are expected to jointly interpret vision, audio, and language, yet existing video benchmarks rarely assess fine-grained reasoning about human speech. Many tasks remain visually solvable or only…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Le Thien Phuc Nguyen , Zhuoran Yu , Samuel Low Yu Hang , Subin An , Jeongik Lee , Yohan Ban , SeungEun Chung , Thanh-Huy Nguyen , JuWan Maeng , Soochahn Lee , Yong Jae Lee

Commonsense reasoning is a difficult task for a computer, but a critical skill for an artificial intelligence (AI). It can enhance the explainability of AI models by enabling them to provide intuitive and human-like explanations for their…

Artificial Intelligence · Computer Science 2024-07-08 Stefanie Krause , Frieder Stolzenburg

The recent swift development of LLMs like GPT-4, Gemini, and GPT-3.5 offers a transformative opportunity in medicine and healthcare, especially in digital diagnostics. This study evaluates each model diagnostic abilities by interpreting a…

Computation and Language · Computer Science 2024-05-14 Gaurav Kumar Gupta , Aditi Singh , Sijo Valayakkad Manikandan , Abul Ehtesham

In recent years, large language models (LLMs) have driven major advances in language understanding, marking a significant step toward artificial general intelligence (AGI). With increasing demands for higher-level semantics and cross-modal…

Computation and Language · Computer Science 2025-09-30 Yuntao Shou , Tao Meng , Wei Ai , Keqin Li

Recent advances in Multi-Modal Large Language Models (MLLMs) have enabled unified processing of language, vision, and structured inputs, opening the door to complex tasks such as logical deduction, spatial reasoning, and scientific…

Artificial Intelligence · Computer Science 2025-07-03 Guiyao Tie , Xueyang Zhou , Tianhe Gu , Ruihang Zhang , Chaoran Hu , Sizhe Zhang , Mengqu Sun , Yan Zhang , Pan Zhou , Lichao Sun

With the rapid advancement of Artificial Intelligence (AI), Large Language Models (LLMs) have significantly impacted a wide array of domains, including healthcare, engineering, science, education, and mathematical reasoning. Among these,…

Machine Learning · Computer Science 2025-05-20 Afrar Jahin , Arif Hassan Zidan , Wei Zhang , Yu Bao , Tianming Liu

The pursuit of artificial general intelligence (AGI) has been accelerated by Multimodal Large Language Models (MLLMs), which exhibit superior reasoning, generalization capabilities, and proficiency in processing multimodal inputs. A crucial…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Yi Chen , Yuying Ge , Yixiao Ge , Mingyu Ding , Bohao Li , Rui Wang , Ruifeng Xu , Ying Shan , Xihui Liu

We introduce VisualQuest, a novel dataset designed to rigorously evaluate multimodal large language models (MLLMs) on abstract visual reasoning tasks that require the integration of symbolic, cultural, and linguistic knowledge. Unlike…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Kelaiti Xiao , Liang Yang , Dongyu Zhang , Paerhati Tulajiang , Hongfei Lin

Multimodal Large Language Models (MLLMs) promise advanced vision language capabilities, yet their effectiveness in visually presented mathematics remains underexplored. This paper analyzes the development and evaluation of MLLMs for…

Multimodal large language models (MLLMs) have achieved remarkable success across a broad range of vision tasks. However, constrained by the capacity of their internal world knowledge, prior work has proposed augmenting MLLMs by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Wenxuan Huang , Yu Zeng , Qiuchen Wang , Zhen Fang , Shaosheng Cao , Zheng Chu , Qingyu Yin , Shuang Chen , Zhenfei Yin , Lin Chen , Zehui Chen , Xu Tang , Yao Hu , Shaohui Lin , Philip Torr , Feng Zhao , Wanli Ouyang

Reasoning is central to human intelligence, enabling structured problem-solving across diverse tasks. Recent advances in large language models (LLMs) have greatly enhanced their reasoning abilities in arithmetic, commonsense, and symbolic…

The goal of achieving Artificial General Intelligence (AGI) is to imitate humans and surpass them. Models such as OpenAI's o1, o3, and DeepSeek's R1 have demonstrated that large language models (LLMs) with human-like reasoning capabilities…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Yansheng Qiu , Li Xiao , Zhaopan Xu , Pengfei Zhou , Zheng Wang , Kaipeng Zhang

This paper investigates the mathematical reasoning capabilities of large language models (LLMs) using 50 newly constructed high-school-level word problems. Unlike prior studies that focus solely on answer correctness, we rigorously analyze…

Artificial Intelligence · Computer Science 2025-02-24 Johan Boye , Birger Moell