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Multimodal Large Language Models (MLLMs) have achieved significant advances in integrating visual and linguistic information, yet their ability to reason about complex and real-world scenarios remains limited. The existing benchmarks are…

PowerPoint presentations combine rich textual content with structured visual layouts, making them a natural testbed for evaluating the multimodal reasoning and layout understanding abilities of modern MLLMs. However, existing benchmarks…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Zheng Huang , Xukai Liu , Tianyu Hu , Kai Zhang , Ye Liu

The progress of Large Language Models (LLMs) like ChatGPT raises the question of how they can be integrated into education. One hope is that they can support mathematics learning, including word-problem solving. Since LLMs can handle…

Computation and Language · Computer Science 2025-08-12 Anselm R. Strohmaier , Wim Van Dooren , Kathrin Seßler , Brian Greer , Lieven Verschaffel

Large language models (LLMs) have made significant progress in various domains, including healthcare. However, the specialized nature of clinical language understanding tasks presents unique challenges and limitations that warrant further…

Computation and Language · Computer Science 2023-08-01 Yuqing Wang , Yun Zhao , Linda Petzold

Although large language models (LLMs) demonstrate impressive performance for many language tasks, most of them can only handle texts a few thousand tokens long, limiting their applications on longer sequence inputs, such as books, reports,…

Computation and Language · Computer Science 2024-06-21 Yushi Bai , Xin Lv , Jiajie Zhang , Hongchang Lyu , Jiankai Tang , Zhidian Huang , Zhengxiao Du , Xiao Liu , Aohan Zeng , Lei Hou , Yuxiao Dong , Jie Tang , Juanzi Li

Large Language Models (LLMs) have drawn widespread attention and research due to their astounding performance in text generation and reasoning tasks. Derivative products, like ChatGPT, have been extensively deployed and highly sought after.…

Software Engineering · Computer Science 2024-12-11 Zibin Zheng , Kaiwen Ning , Qingyuan Zhong , Jiachi Chen , Wenqing Chen , Lianghong Guo , Weicheng Wang , Yanlin Wang

Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of general-domain tasks. However, their effectiveness in specialized fields, such as construction, remains underexplored. In this paper, we introduce…

Computation and Language · Computer Science 2025-08-25 Yanzhao Wu , Lufan Wang , Rui Liu

Nowadays, pretrained language models (PLMs) have dominated the majority of NLP tasks. While, little research has been conducted on systematically evaluating the language abilities of PLMs. In this paper, we present a large-scale empirical…

Computation and Language · Computer Science 2022-05-04 Junyi Li , Tianyi Tang , Zheng Gong , Lixin Yang , Zhuohao Yu , Zhipeng Chen , Jingyuan Wang , Wayne Xin Zhao , Ji-Rong Wen

Large Language Models (LLMs) are increasingly deployed in applications that interact with the physical world, such as navigation, robotics, or mapping, making robust geospatial reasoning a critical capability. Despite that, LLMs' ability to…

Artificial Intelligence · Computer Science 2026-02-19 Thinh Hung Truong , Jey Han Lau , Jianzhong Qi

Identifying anomalous human spatial trajectory patterns can indicate dynamic changes in mobility behavior with applications in domains like infectious disease monitoring and elderly care. Recent advancements in large language models (LLMs)…

Machine Learning · Computer Science 2023-10-10 Zheng Zhang , Hossein Amiri , Zhenke Liu , Andreas Züfle , Liang Zhao

Multimodal language analysis is a rapidly evolving field that leverages multiple modalities to enhance the understanding of high-level semantics underlying human conversational utterances. Despite its significance, little research has…

Computation and Language · Computer Science 2025-04-25 Hanlei Zhang , Zhuohang Li , Yeshuang Zhu , Hua Xu , Peiwu Wang , Haige Zhu , Jie Zhou , Jinchao Zhang

We present a new approach for benchmarking Large Language Model (LLM) capabilities on research-level mathematics. Existing benchmarks largely rely on static, hand-curated sets of contest or textbook-style problems as proxies for…

Artificial Intelligence · Computer Science 2026-03-02 Antoine Peyronnet , Fabian Gloeckle , Amaury Hayat

Multimodal large language models (MLLMs) have demonstrated powerful capabilities in general spatial understanding and reasoning. However, their fine-grained spatial understanding and reasoning capabilities in complex urban scenarios have…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Jun Zhang , Jie Feng , Long Chen , Junhui Wang , Zhicheng Liu , Depeng Jin , Yong Li

Large Language Models (LLMs) have demonstrated exceptional capabilities in various natural language tasks, often achieving performances that surpass those of humans. Despite these advancements, the domain of mathematics presents a…

Computation and Language · Computer Science 2024-04-02 Ankit Satpute , Noah Giessing , Andre Greiner-Petter , Moritz Schubotz , Olaf Teschke , Akiko Aizawa , Bela Gipp

The rapid evolution of large language models (LLMs) and their capacity to simulate human cognition and behavior has given rise to LLM-based frameworks and tools that are evaluated and applied based on their ability to perform tasks…

Computation and Language · Computer Science 2024-12-03 Jing Yi Wang , Nicholas Sukiennik , Tong Li , Weikang Su , Qianyue Hao , Jingbo Xu , Zihan Huang , Fengli Xu , Yong Li

The potential of Large Language Model (LLM) as agents has been widely acknowledged recently. Thus, there is an urgent need to quantitatively \textit{evaluate LLMs as agents} on challenging tasks in interactive environments. We present…

Multimodal Large Language Models (MLLMs) have demonstrated significant potential to advance a broad range of domains. However, current benchmarks for evaluating MLLMs primarily emphasize general knowledge and vertical step-by-step reasoning…

The recent rapid development of Large Vision-Language Models (LVLMs) has indicated their potential for embodied tasks.However, the critical skill of spatial understanding in embodied environments has not been thoroughly evaluated, leaving…

Artificial Intelligence · Computer Science 2024-06-11 Mengfei Du , Binhao Wu , Zejun Li , Xuanjing Huang , Zhongyu Wei

Large language model (LLM) agents have demonstrated remarkable potential in advancing scientific discovery. However, their capability in the fundamental yet crucial task of reproducing code from research papers, especially in the NLP…

Large Language Models (LLMs) have demonstrated significant promise in automating software development tasks, yet their capabilities with respect to software design tasks remains largely unclear. This study investigates the capabilities of…

Software Engineering · Computer Science 2025-03-11 L. P. Franciscatto Guerra , N. Ernst