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Multimodal Large Language Models (MLLMs) show promise for image-based regression tasks, but current approaches face key limitations. Recent methods fine-tune MLLMs using preset output vocabularies and generic task-level prompts (e.g., "How…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Roy H. Jennings , Genady Paikin , Roy Shaul , Evgeny Soloveichik

Video generation has advanced rapidly, with recent methods producing increasingly convincing animated results. However, existing benchmarks-largely designed for realistic videos-struggle to evaluate animation-style generation with its…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Leyi Wu , Pengjun Fang , Kai Sun , Yazhou Xing , Yinwei Wu , Songsong Wang , Ziqi Huang , Dan Zhou , Yingqing He , Ying-Cong Chen , Qifeng Chen

Vision-language models (VLMs) have demonstrated remarkable capabilities in understanding and reasoning about visual content, but significant challenges persist in tasks requiring cross-viewpoint understanding and spatial reasoning. We…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Dingming Li , Hongxing Li , Zixuan Wang , Yuchen Yan , Hang Zhang , Siqi Chen , Guiyang Hou , Shengpei Jiang , Wenqi Zhang , Yongliang Shen , Weiming Lu , Yueting Zhuang

Text-video retrieval is a critical multi-modal task to find the most relevant video for a text query. Although pretrained models like CLIP have demonstrated impressive potential in this area, the rising cost of fully finetuning these models…

Computer Vision and Pattern Recognition · Computer Science 2024-01-22 Xiangpeng Yang , Linchao Zhu , Xiaohan Wang , Yi Yang

Multimodal Large Language Models (MLLMs) are set to transform how machines process and generate human-like responses by integrating diverse modalities such as text, images, and code. Yet, effectively harnessing their capabilities hinges on…

Artificial Intelligence · Computer Science 2025-04-15 Anwesha Mohanty , Venkatesh Balavadhani Parthasarathy , Arsalan Shahid

Text-to-image generative models have demonstrated remarkable capabilities in generating high-quality images based on textual prompts. However, crafting prompts that accurately capture the user's creative intent remains challenging. It often…

Human-Computer Interaction · Computer Science 2023-04-20 Stephen Brade , Bryan Wang , Mauricio Sousa , Sageev Oore , Tovi Grossman

Text-to-video models have made remarkable advancements through optimization on high-quality text-video pairs, where the textual prompts play a pivotal role in determining quality of output videos. However, achieving the desired output often…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Yatai Ji , Jiacheng Zhang , Jie Wu , Shilong Zhang , Shoufa Chen , Chongjian GE , Peize Sun , Weifeng Chen , Wenqi Shao , Xuefeng Xiao , Weilin Huang , Ping Luo

Recent advances in video generation can produce realistic, minute-long single-shot videos with scalable diffusion transformers. However, real-world narrative videos require multi-shot scenes with visual and dynamic consistency across shots.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Yuwei Guo , Ceyuan Yang , Ziyan Yang , Zhibei Ma , Zhijie Lin , Zhenheng Yang , Dahua Lin , Lu Jiang

Traditional benchmarks for large language models (LLMs) typically rely on static evaluations through storytelling or opinion expression, which fail to capture the dynamic requirements of real-time information processing in contemporary…

Machine Learning · Computer Science 2025-06-27 Jingyao Li , Hao Sun , Zile Qiao , Yong Jiang , Pengjun Xie , Fei Huang , Hong Xu , Jiaya Jia

Real-time video commentary generation provides textual descriptions of ongoing events in videos. It supports accessibility and engagement in domains such as sports, esports, and livestreaming. Commentary generation involves two essential…

Computation and Language · Computer Science 2026-03-04 Anum Afzal , Yuki Saito , Hiroya Takamura , Katsuhito Sudoh , Shinnosuke Takamichi , Graham Neubig , Florian Matthes , Tatsuya Ishigaki

Large Multimodal Models (LMMs) have achieved remarkable progress across various capabilities; however, complex video reasoning in the scientific domain remains a significant and challenging frontier. Current video benchmarks predominantly…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Andong Deng , Taojiannan Yang , Shoubin Yu , Lincoln Spencer , Mohit Bansal , Chen Chen , Serena Yeung-Levy , Xiaohan Wang

Text-to-image generative models are a new and powerful way to generate visual artwork. However, the open-ended nature of text as interaction is double-edged; while users can input anything and have access to an infinite range of…

Human-Computer Interaction · Computer Science 2023-09-29 Vivian Liu , Lydia B. Chilton

Prompt engineering is crucial for achieving reliable and effective outputs from large language models (LLMs), but its design requires specialized knowledge of prompting techniques and a deep understanding of target tasks. To address this…

Computation and Language · Computer Science 2025-10-22 Yohei Ikenoue , Hitomi Tashiro , Shigeru Kuroyanagi

Image search is an essential and user-friendly method to explore vast galleries of digital images. However, existing image search methods heavily rely on proximity measurements like tag matching or image similarity, requiring precise user…

Information Retrieval · Computer Science 2023-12-06 Yilin Ye , Qian Zhu , Shishi Xiao , Kang Zhang , Wei Zeng

The recent surge in video generation has shown the growing demand for high-quality video synthesis using large vision models. Existing video generation models are predominantly based on the video diffusion transformer (vDiT), however, they…

Hardware Architecture · Computer Science 2025-11-18 Wenxuan Miao , Yulin Sun , Aiyue Chen , Jing Lin , Yiwu Yao , Yiming Gan , Jieru Zhao , Jingwen Leng , Mingyi Guo , Yu Feng

The "one-shot" technique represents a distinct and sophisticated aesthetic in filmmaking. However, its practical realization is often hindered by prohibitive costs and complex real-world constraints. Although emerging video generation…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jiawei Liu , Junqiao Li , Jiangfan Deng , Gen Li , Siyu Zhou , Zetao Fang , Shanshan Lao , Zengde Deng , Jianing Zhu , Tingting Ma , Jiayi Li , Yunqiu Wang , Qian He , Xinglong Wu

The rapid advancement of generative AI has revolutionized image creation, enabling high-quality synthesis from text prompts while raising critical challenges for media authenticity. We present Ai-GenBench, a novel benchmark designed to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Lorenzo Pellegrini , Davide Cozzolino , Serafino Pandolfini , Davide Maltoni , Matteo Ferrara , Luisa Verdoliva , Marco Prati , Marco Ramilli

Multimodal Large Language Models (MLLMs) have advanced VQA and now support Vision-DeepResearch systems that use search engines for complex visual-textual fact-finding. However, evaluating these visual and textual search abilities is still…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yu Zeng , Wenxuan Huang , Zhen Fang , Shuang Chen , Yufan Shen , Yishuo Cai , Xiaoman Wang , Zhenfei Yin , Lin Chen , Zehui Chen , Shiting Huang , Yiming Zhao , Xu Tang , Yao Hu , Philip Torr , Wanli Ouyang , Shaosheng Cao

In today's digitally driven world, dialogue systems play a pivotal role in enhancing user interactions, from customer service to virtual assistants. In these dialogues, it is important to identify user's goals automatically to resolve their…

Computation and Language · Computer Science 2024-11-19 Juan A. Rodriguez , Nicholas Botzer , David Vazquez , Christopher Pal , Marco Pedersoli , Issam Laradji

With the rapid development of foundation video generation technologies, long video generation models have exhibited promising research potential thanks to expanded content creation space. Recent studies reveal that the goal of long video…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 X. Feng , H. Yu , M. Wu , S. Hu , J. Chen , C. Zhu , J. Wu , X. Chu , K. Huang