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Agentic systems, AI architectures that autonomously execute multi-step workflows to achieve complex goals, are often built using repeated large language model (LLM) calls for closed-set decision tasks such as routing, shortlisting, gating,…

Computation and Language · Computer Science 2026-02-19 Ido Levy , Eilam Shapira , Yinon Goldshtein , Avi Yaeli , Nir Mashkif , Segev Shlomov

Acquiring high-quality instance segmentation data is challenging due to the labor-intensive nature of the annotation process and significant class imbalances within datasets. Recent studies have utilized the integration of Copy-Paste and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Xianbao Hou , Yonghao He , Zeyd Boukhers , John See , Hu Su , Wei Sui , Cong Yang

Diffusion models have revitalized the image generation domain, playing crucial roles in both academic research and artistic expression. With the emergence of new diffusion models, assessing the performance of text-to-image models has become…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Chutian Meng , Fan Ma , Jiaxu Miao , Chi Zhang , Yi Yang , Yueting Zhuang

The rapid development of diffusion models has triggered diverse applications. Identity-preserving text-to-image generation (ID-T2I) particularly has received significant attention due to its wide range of application scenarios like AI…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Weifeng Chen , Jiacheng Zhang , Jie Wu , Hefeng Wu , Xuefeng Xiao , Liang Lin

Advancements in large language models (LLMs) allow them to address diverse questions using human-like interfaces. Still, limitations in their training prevent them from answering accurately in scenarios that could benefit from multiple…

Artificial Intelligence · Computer Science 2025-04-09 Yoshitaka Inoue , Tianci Song , Xinling Wang , Augustin Luna , Tianfan Fu

Large Language Models (LLMs) increasingly act as function-call agents that invoke external tools to tackle tasks beyond their static knowledge. However, they typically invoke tools one at a time without a global view of task structure. As…

Artificial Intelligence · Computer Science 2026-05-22 Yan Jiang , Hao Zhou , Lizhong GU , Tianlong Li , Ruinan Jin , Wanqi Zhou , Ai Han

Despite advancements in text-to-image generation (T2I), prior methods often face text-image misalignment problems such as relation confusion in generated images. Existing solutions involve cross-attention manipulation for better…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Leigang Qu , Wenjie Wang , Yongqi Li , Hanwang Zhang , Liqiang Nie , Tat-Seng Chua

Recent advancements in text-to-image (T2I) generation have enabled models to produce high-quality images from textual descriptions. However, these models often struggle with complex instructions involving multiple objects, attributes, and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Yucheng Zhou , Jiahao Yuan , Qianning Wang

The recent surge in the research of diffusion models has accelerated the adoption of text-to-image models in various Artificial Intelligence Generated Content (AIGC) commercial products. While these exceptional AIGC products are gaining…

Computers and Society · Computer Science 2023-11-03 Qichao Wang , Tian Bian , Yian Yin , Tingyang Xu , Hong Cheng , Helen M. Meng , Zibin Zheng , Liang Chen , Bingzhe Wu

Despite the impressive text-to-image (T2I) synthesis capabilities of diffusion models, they often struggle to understand compositional relationships between objects and attributes, especially in complex settings. Existing solutions have…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Evans Xu Han , Linghao Jin , Xiaofeng Liu , Paul Pu Liang

Text-to-image generation (TTI) refers to the usage of models that could process text input and generate high fidelity images based on text descriptions. Text-to-image generation using neural networks could be traced back to the emergence of…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Fengxiang Bie , Yibo Yang , Zhongzhu Zhou , Adam Ghanem , Minjia Zhang , Zhewei Yao , Xiaoxia Wu , Connor Holmes , Pareesa Golnari , David A. Clifton , Yuxiong He , Dacheng Tao , Shuaiwen Leon Song

Generative modeling is widely regarded as one of the most essential problems in today's AI community, with text-to-image generation having gained unprecedented real-world impacts. Among various approaches, diffusion models have achieved…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xuyang Guo , Jiayan Huo , Yingyu Liang , Zhenmei Shi , Zhao Song , Jiahao Zhang , Zhen Zhuang

Text-to-image diffusion models (T2I) have demonstrated unprecedented capabilities in creating realistic and aesthetic images. On the contrary, text-to-video diffusion models (T2V) still lag far behind in frame quality and text alignment,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-11 Yabo Zhang , Yuxiang Wei , Xianhui Lin , Zheng Hui , Peiran Ren , Xuansong Xie , Xiangyang Ji , Wangmeng Zuo

Training AI models has always been challenging, especially when there is a need for custom models to provide personalized services. Algorithm engineers often face a lengthy process to iteratively develop models tailored to specific business…

Artificial Intelligence · Computer Science 2023-11-27 Haoyuan Li , Hao Jiang , Tianke Zhang , Zhelun Yu , Aoxiong Yin , Hao Cheng , Siming Fu , Yuhao Zhang , Wanggui He

We present DiffChat, a novel method to align Large Language Models (LLMs) to "chat" with prompt-as-input Text-to-Image Synthesis (TIS) models (e.g., Stable Diffusion) for interactive image creation. Given a raw prompt/image and a…

Computation and Language · Computer Science 2024-03-11 Jiapeng Wang , Chengyu Wang , Tingfeng Cao , Jun Huang , Lianwen Jin

Image editing aims to edit the given synthetic or real image to meet the specific requirements from users. It is widely studied in recent years as a promising and challenging field of Artificial Intelligence Generative Content (AIGC).…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Xincheng Shuai , Henghui Ding , Xingjun Ma , Rongcheng Tu , Yu-Gang Jiang , Dacheng Tao

Text-to-Image (T2I) diffusion models have achieved remarkable success in image generation. Despite their progress, challenges remain in both prompt-following ability, image quality and lack of high-quality datasets, which are essential for…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Jingkun An , Yinghao Zhu , Zongjian Li , Enshen Zhou , Haoran Feng , Xijie Huang , Bohua Chen , Yemin Shi , Chengwei Pan

Text-to-image (T2I) models have recently experienced rapid development, achieving astonishing performance in terms of fidelity and textual alignment capabilities. However, given a long paragraph (up to 512 words), these generation models…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Weijia Wu , Zhuang Li , Yefei He , Mike Zheng Shou , Chunhua Shen , Lele Cheng , Yan Li , Tingting Gao , Di Zhang

Recommender models excel at providing domain-specific item recommendations by leveraging extensive user behavior data. Despite their ability to act as lightweight domain experts, they struggle to perform versatile tasks such as providing…

Information Retrieval · Computer Science 2024-01-31 Xu Huang , Jianxun Lian , Yuxuan Lei , Jing Yao , Defu Lian , Xing Xie

Scaling up model and data size has been quite successful for the evolution of LLMs. However, the scaling law for the diffusion based text-to-image (T2I) models is not fully explored. It is also unclear how to efficiently scale the model for…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Hao Li , Yang Zou , Ying Wang , Orchid Majumder , Yusheng Xie , R. Manmatha , Ashwin Swaminathan , Zhuowen Tu , Stefano Ermon , Stefano Soatto