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Related papers: MULTISCRIPT: Multimodal Script Learning for Suppor…

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Visual texts embedded in videos carry rich semantic information, which is crucial for both holistic video understanding and fine-grained reasoning about local human actions. However, existing video understanding benchmarks largely overlook…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Zhoufaran Yang , Yan Shu , Jing Wang , Zhifei Yang , Yan Zhang , Yu Li , Keyang Lu , Gangyan Zeng , Shaohui Liu , Yu Zhou , Nicu Sebe

While Alexa can perform over 100,000 skills on paper, its capability covers only a fraction of what is possible on the web. To reach the full potential of an assistant, it is desirable that individuals can create skills to automate their…

Human-Computer Interaction · Computer Science 2020-09-01 Michael H. Fischer , Giovanni Campagna , Euirim Choi , Monica S. Lam

Bridging vision and natural language is a longstanding goal in computer vision and multimedia research. While earlier works focus on generating a single-sentence description for visual content, recent works have studied paragraph…

Multimedia · Computer Science 2020-05-15 Junnan Li , Yongkang Wong , Qi Zhao , Mohan S. Kankanhalli

Large language models, trained on extensive corpora, successfully unify diverse linguistic tasks within a single generative framework. Inspired by this, recent works like Large Vision Model (LVM) extend this paradigm to vision by organizing…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Lan Chen , Yuchao Gu , Qi Mao

Automatically generating training supervision for embodied tasks is crucial, as manual designing is tedious and not scalable. While prior works use large language models (LLMs) or vision-language models (VLMs) to generate rewards, these…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Xiaowen Qiu , Yian Wang , Jiting Cai , Zhehuan Chen , Chunru Lin , Tsun-Hsuan Wang , Chuang Gan

Instruction-based speech processing is becoming popular. Studies show that training with multiple tasks boosts performance, but collecting diverse, large-scale tasks and datasets is expensive. Thus, it is highly desirable to design a…

Computation and Language · Computer Science 2024-08-27 Chien-yu Huang , Min-Han Shih , Ke-Han Lu , Chi-Yuan Hsiao , Hung-yi Lee

Interactive articles help readers engage with complex ideas through exploration, yet creating them remains costly, requiring both domain expertise and web development skills. Recent LLM-based agents can automate content creation, but…

Computation and Language · Computer Science 2026-03-03 Yinghao Tang , Yupeng Xie , Yingchaojie Feng , Tingfeng Lan , Wei Chen

Interactive documents help readers engage with complex ideas through dynamic visualization, interactive animations, and exploratory interfaces. However, creating such documents remains costly, as it requires both domain expertise and web…

Human-Computer Interaction · Computer Science 2026-03-31 Yinghao Tang , Yupeng Xie , Yingchaojie Feng , Tingfeng Lan , Jiale Lao , Yue Cheng , Wei Chen

We introduce a large dataset of narrative texts and questions about these texts, intended to be used in a machine comprehension task that requires reasoning using commonsense knowledge. Our dataset complements similar datasets in that we…

Computation and Language · Computer Science 2018-03-15 Simon Ostermann , Ashutosh Modi , Michael Roth , Stefan Thater , Manfred Pinkal

Generating long, cohesive video stories with consistent characters is a significant challenge for current text-to-video AI. We introduce a method that approaches video generation in a filmmaker-like manner. Instead of creating a video in…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Chayan Jain , Rishant Sharma , Archit Garg , Ishan Bhanuka , Pratik Narang , Dhruv Kumar

The rapid growth of visual tokens in multimodal large language models (MLLMs) leads to excessive memory consumption and inference latency, especially when handling high-resolution images and videos. Token pruning is a technique used to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Zhongyu Yang , Dannong Xu , Wei Pang , Yingfang Yuan

With the rapid development of Multi-modal Large Language Models (MLLMs), a number of diagnostic benchmarks have recently emerged to evaluate the comprehension capabilities of these models. However, most benchmarks predominantly assess…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Kunchang Li , Yali Wang , Yinan He , Yizhuo Li , Yi Wang , Yi Liu , Zun Wang , Jilan Xu , Guo Chen , Ping Luo , Limin Wang , Yu Qiao

Script knowledge consists of detailed information on everyday activities. Such information is often taken for granted in text and needs to be inferred by readers. Therefore, script knowledge is a central component to language comprehension.…

Computation and Language · Computer Science 2019-06-11 Lilian D. A. Wanzare , Michael Roth , Manfred Pinkal

Narrative videos, such as movies, pose significant challenges in video understanding due to their rich contexts (characters, dialogues, storylines) and diverse demands (identify who, relationship, and reason). In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Kevin Qinghong Lin , Pengchuan Zhang , Difei Gao , Xide Xia , Joya Chen , Ziteng Gao , Jinheng Xie , Xuhong Xiao , Mike Zheng Shou

Recent great advances in video generation models have demonstrated their potential to produce high-quality videos, bringing challenges to effective evaluation. Unlike human evaluation, existing automated evaluation metrics lack highlevel…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Zhun Mou , Bin Xia , Zhengchao Huang , Wenming Yang , Jiaya Jia

We are committed to learning human skill generators at key-step levels. The generation of skills is a challenging endeavor, but its successful implementation could greatly facilitate human skill learning and provide more experience for…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Yilu Wu , Chenhui Zhu , Shuai Wang , Hanlin Wang , Jing Wang , Zhaoxiang Zhang , Limin Wang

Schemata are structured representations of complex tasks that can aid artificial intelligence by allowing models to break down complex tasks into intermediate steps. We propose a novel system that induces schemata from web videos and…

Computer Vision and Pattern Recognition · Computer Science 2021-11-18 Yue Yang , Joongwon Kim , Artemis Panagopoulou , Mark Yatskar , Chris Callison-Burch

In an era defined by the explosive growth of data and rapid technological advancements, Multimodal Large Language Models (MLLMs) stand at the forefront of artificial intelligence (AI) systems. Designed to seamlessly integrate diverse data…

Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks ranging from software engineering development to general-purpose reasoning. While current benchmarks have…

YouTube users looking for instructions for a specific task may spend a long time browsing content trying to find the right video that matches their needs. Creating a visual summary (abridged version of a video) provides viewers with a quick…

Computer Vision and Pattern Recognition · Computer Science 2022-08-16 Medhini Narasimhan , Arsha Nagrani , Chen Sun , Michael Rubinstein , Trevor Darrell , Anna Rohrbach , Cordelia Schmid