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Making a good graphic that accurately and efficiently conveys the desired message to the audience is both an art and a science, typically not taught in the data science curriculum. Visualisation makeovers are exercises where the community…

Human-Computer Interaction · Computer Science 2025-08-11 Siddharth Gangwar , David A. Selby , Sebastian J. Vollmer

Large Language Models (LLMs) have become indispensable for evaluating writing. However, text feedback they provide is often unintelligible, generic, and not specific to user criteria. Inspired by structured rubrics in education and…

Human-Computer Interaction · Computer Science 2026-02-16 Jingwen Bai , Wei Soon Cheong , Philippe Muller , Brian Y Lim

The rapid development of Large Language Models (LLMs) has catalyzed significant advancements in video understanding technologies. This survey provides a comprehensive analysis of benchmarks and evaluation methodologies specifically designed…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Yogesh Kumar

In recent years, Large Language Models (LLMs) have emerged as transformative tools across numerous domains, impacting how professionals approach complex analytical tasks. This systematic mapping study comprehensively examines the…

Computers and Society · Computer Science 2025-08-19 Sai Sanjna Chintakunta , Nathalia Nascimento , Everton Guimaraes

Recent advances in multimodal large language models (MLLMs) have greatly improved image understanding and captioning capabilities. However, existing image captioning benchmarks typically suffer from limited diversity in caption length, the…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Zitong Xu , Huiyu Duan , Shengyao Qin , Guangyu Yang , Guangji Ma , Xiongkuo Min , Ke Gu , Guangtao Zhai , Patrick Le Callet

Connecting text and visual modalities plays an essential role in generative intelligence. For this reason, inspired by the success of large language models, significant research efforts are being devoted to the development of Multimodal…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Davide Caffagni , Federico Cocchi , Luca Barsellotti , Nicholas Moratelli , Sara Sarto , Lorenzo Baraldi , Lorenzo Baraldi , Marcella Cornia , Rita Cucchiara

The application of visual instruction tuning and other post-training techniques has significantly enhanced the capabilities of Large Language Models (LLMs) in visual understanding, enriching Vision-Language Models (VLMs) with more…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Mingjie Xu , Andrew Estornell , Hongzheng Yang , Yuzhi Zhao , Zhaowei Zhu , Qi Xuan , Jiaheng Wei

Visual Speech Recognition (VSR) transcribes speech by analyzing lip movements. Recently, Large Language Models (LLMs) have been integrated into VSR systems, leading to notable performance improvements. However, the potential of LLMs has not…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Zehua Liu , Xiaolou Li , Li Guo , Lantian Li , Dong Wang

This study addresses the challenges of tracking and analyzing students' learning trajectories, particularly the issue of inadequate knowledge coverage in course assessments. Traditional assessment tools often fail to fully cover course…

Computers and Society · Computer Science 2025-04-17 Yu-Hxiang Chen , Ju-Shen Huang , Jia-Yu Hung , Chia-Kai Chang

Large language models (LLMs) are revolutionizing education, with LLM-based agents playing a key role in simulating student behavior. A major challenge in student simulation is modeling the diverse learning patterns of students at various…

Machine Learning · Computer Science 2025-08-12 Tao Wu , Jingyuan Chen , Wang Lin , Mengze Li , Yumeng Zhu , Ang Li , Kun Kuang , Fei Wu

Psychological assessments commonly rely on rating-scale items, which require respondents to condense complex experiences into predefined categories. Although rich, unstructured text is often captured alongside these scales, it rarely…

Computation and Language · Computer Science 2026-03-20 Joe Watson , Ivan O'Connor , Chia-Wen Chen , Luning Sun , Fang Luo , David Stillwell

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across linguistic boundaries, but also represent an important…

Computation and Language · Computer Science 2024-11-20 Shaolin Zhu , Supryadi , Shaoyang Xu , Haoran Sun , Leiyu Pan , Menglong Cui , Jiangcun Du , Renren Jin , António Branco , Deyi Xiong

Large language models (LLMs), renowned for their powerful conversational abilities, are widely recognized as exceptional tools in the field of education, particularly in the context of automated intelligent instruction systems for language…

Computation and Language · Computer Science 2024-07-19 Kaiqi Fu , Linkai Peng , Nan Yang , Shuran Zhou

Many constructs that characterize language, like its complexity or emotionality, have a naturally continuous semantic structure; a public speech is not just "simple" or "complex," but exists on a continuum between extremes. Although large…

Computation and Language · Computer Science 2025-09-23 Hauke Licht , Rupak Sarkar , Patrick Y. Wu , Pranav Goel , Niklas Stoehr , Elliott Ash , Alexander Miserlis Hoyle

The rapid advancement of large language models (LLMs) has accelerated the emergence of in-context learning (ICL) as a cutting-edge approach in the natural language processing domain. Recently, ICL has been employed in visual understanding…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Dianmo Sheng , Dongdong Chen , Zhentao Tan , Qiankun Liu , Qi Chu , Jianmin Bao , Tao Gong , Bin Liu , Shengwei Xu , Nenghai Yu

How to evaluate large language models (LLMs) cleanly has been established as an important research era to genuinely report the performance of possibly contaminated LLMs. Yet, how to cleanly evaluate the visual language models (VLMs) is an…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Hongyuan Lu , Shujie Miao , Wai Lam

The rapid development and dynamic nature of large language models (LLMs) make it difficult for conventional quantitative benchmarks to accurately assess their capabilities. We propose report cards, which are human-interpretable, natural…

Machine Learning · Computer Science 2024-09-04 Blair Yang , Fuyang Cui , Keiran Paster , Jimmy Ba , Pashootan Vaezipoor , Silviu Pitis , Michael R. Zhang

Novice programmers benefit from timely, personalized support that addresses individual learning gaps, yet the availability of instructors and teaching assistants is inherently limited. Large language models (LLMs) present opportunities to…

Computers and Society · Computer Science 2025-10-07 Griffin Pitts , Anurata Prabha Hridi , Arun-Balajiee Lekshmi-Narayanan

The advent of large language models (LLMs) has significantly advanced natural language processing tasks like text summarization. However, their large size and computational demands, coupled with privacy concerns in data transmission, limit…

Computation and Language · Computer Science 2024-03-18 Pengcheng Jiang , Cao Xiao , Zifeng Wang , Parminder Bhatia , Jimeng Sun , Jiawei Han

Large language models (LLMs) have been explored in a variety of reasoning tasks including solving of mathematical problems. Each math dataset typically includes its own specially designed evaluation script, which, while suitable for its…

Computation and Language · Computer Science 2024-04-23 Boning Zhang , Chengxi Li , Kai Fan