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In computer simulation of the learning process is usually assumed that all elements of the training material are assimilated equally durable. But in practice, the knowledge, which a student uses in its operations, are remembered much…

Computers and Society · Computer Science 2013-12-20 Robert V Mayer

Massive Open Online Courses (MOOCs) are the road that led to a revolution and a new era of learning environments. Educational institutions have come under pressure to adopt new models that assure openness in their education distribution.…

Computers and Society · Computer Science 2016-06-21 Mohammad Khalil , Martin Ebner

Multimodal Large Language Models (MLLMs) utilize multimodal contexts consisting of text, images, or videos to solve various multimodal tasks. However, we find that changing the order of multimodal input can cause the model's performance to…

Artificial Intelligence · Computer Science 2024-10-23 Zhijie Tan , Xu Chu , Weiping Li , Tong Mo

Topical Segmentation poses a great role in reducing search space of the topics taught in a lecture video specially when the video metadata lacks topic wise segmentation information. This segmentation information eases user efforts of…

Computation and Language · Computer Science 2020-12-15 Ananda Das , Partha Pratim Das

Human perception of the empirical world involves recognizing the diverse appearances, or 'modalities', of underlying objects. Despite the longstanding consideration of this perspective in philosophy and cognitive science, the study of…

Machine Learning · Computer Science 2023-12-19 Zhou Lu

The recent pandemic has changed the way we see education. It is not surprising that children and college students are not the only ones using online education. Millions of adults have signed up for online classes and courses during last…

Computers and Society · Computer Science 2022-01-19 Manuel J. Gomez , Mario Calderón , Victor Sánchez , Félix J. García Clemente , José A. Ruipérez-Valiente

Multimodal large language models (MLLMs) have demonstrated strong performance in understanding videos holistically, yet their ability to process streaming videos-videos are treated as a sequence of visual events-remains underexplored.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Gengyuan Zhang , Mingcong Ding , Tong Liu , Yao Zhang , Volker Tresp

Multimodal Machine Learning has emerged as a prominent research direction across various applications such as Sentiment Analysis, Emotion Recognition, Machine Translation, Hate Speech Recognition, and Movie Genre Classification. This…

Computation and Language · Computer Science 2023-06-13 Abdelhamid Haouhat , Slimane Bellaouar , Attia Nehar , Hadda Cherroun

Existing dense or paragraph video captioning approaches rely on holistic representations of videos, possibly coupled with learned object/action representations, to condition hierarchical language decoders. However, they fundamentally lack…

Computer Vision and Pattern Recognition · Computer Science 2024-01-10 Shih-Han Chou , James J. Little , Leonid Sigal

Thumbnail is the face of online videos. The explosive growth of videos both in number and variety underpins the importance of a good thumbnail because it saves potential viewers time to choose videos and even entice them to click on them. A…

Computer Vision and Pattern Recognition · Computer Science 2021-01-05 Zhifeng Yu , Nanchun Shi

Multimodal video understanding plays a crucial role in tasks such as action recognition and emotion classification by combining information from different modalities. However, multimodal models are prone to overfitting strong modalities,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Xiaoyu Ma , Ding Ding , Hao Chen

The increasing popularity of e-learning has created demand for improving online education through techniques such as predictive analytics and content recommendations. In this paper, we study learner outcome predictions, i.e., predictions of…

Machine Learning · Computer Science 2020-01-24 Yuwei Tu , Weiyu Chen , Christopher G. Brinton

Multimodal recommendation systems are increasingly popular for their potential to improve performance by integrating diverse data types. However, the actual benefits of this integration remain unclear, raising questions about when and how…

Information Retrieval · Computer Science 2025-08-08 Hongyu Zhou , Yinan Zhang , Aixin Sun , Zhiqi Shen

As Massive Open Online Courses (MOOCs) become increasingly popular, it is promising to automatically provide extracurricular knowledge for MOOC users. Suffering from semantic drifts and lack of knowledge guidance, existing methods can not…

Computation and Language · Computer Science 2019-09-18 Jifan Yu , Chenyu Wang , Gan Luo , Lei Hou , Juanzi Li , Jie Tang , Zhiyuan Liu

Multi-modal learning, particularly among imaging and linguistic modalities, has made amazing strides in many high-level fundamental visual understanding problems, ranging from language grounding to dense event captioning. However, much of…

Computer Vision and Pattern Recognition · Computer Science 2019-10-28 Tanzila Rahman , Bicheng Xu , Leonid Sigal

Video caption refers to generating a descriptive sentence for a specific short video clip automatically, which has achieved remarkable success recently. However, most of the existing methods focus more on visual information while ignoring…

Computer Vision and Pattern Recognition · Computer Science 2017-12-12 Wangli Hao , Zhaoxiang Zhang , He Guan , Guibo Zhu

YouTube Kids (YTK) is one of the most popular kids' applications used by millions of kids daily. However, various studies have highlighted concerns about the videos on the platform, like the over-presence of entertaining and commercial…

Computers and Society · Computer Science 2024-02-07 Sumeet Kumar , Mallikarjuna T. , Ashiqur Khudabukhsh

Knowledge tracing models have enabled a range of intelligent tutoring systems to provide feedback to students. However, existing methods for knowledge tracing in learning sciences are predominantly reliant on statistical data and…

Computation and Language · Computer Science 2025-07-08 Hyeongdon Moon , Richard Davis , Seyed Parsa Neshaei , Pierre Dillenbourg

Informed machine learning methods allow the integration of prior knowledge into learning systems. This can increase accuracy and robustness or reduce data needs. However, existing methods often assume hard constraining knowledge, that does…

Machine Learning · Computer Science 2024-10-10 Christian Schlauch , Nadja Klein , Christian Wirth

As an emerging type of user-generated content, micro-video drastically enriches people's entertainment experiences and social interactions. However, the popularity pattern of an individual micro-video still remains elusive among the…

Machine Learning · Computer Science 2022-01-11 Yaochen Zhu , Jiayi Xie , Zhenzhong Chen
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