Composed Image Retrieval (CIR) presents a significant challenge as it requires jointly understanding a reference image and a modified textual instruction to find relevant target images. Some existing methods attempt to use a two-stage approach to further refine retrieval results. However, this often requires additional training of a ranking model. Despite the success of Chain-of-Thought (CoT) techniques in reducing training costs for language models, their application in CIR tasks remains limited -- compressing visual information into text or relying on elaborate prompt designs. Besides, existing works only utilize it for zero-shot CIR, as it is challenging to achieve satisfactory results in supervised CIR with a well-trained model. In this work, we proposed a framework that includes the Pyramid Matching Model with Training-Free Refinement (PMTFR) to address these challenges. Through a simple but effective module called Pyramid Patcher, we enhanced the Pyramid Matching Model's understanding of visual information at different granularities. Inspired by representation engineering, we extracted representations from COT data and injected them into the LVLMs. This approach allowed us to obtain refined retrieval scores in the Training-Free Refinement paradigm without relying on explicit textual reasoning, further enhancing performance. Extensive experiments on CIR benchmarks demonstrate that PMTFR surpasses state-of-the-art methods in supervised CIR tasks. The code will be made public.
Enhancing Vulnerability Reports with Automated and Augmented Description Summarization
Department of Computer Science at the University of Central Florida（佛罗里达中央大学计算机科学系）；Department of Computer Science at Northeastern Illinois University（北伊利诺伊大学计算机科学系）；Department of Computer Science at Qatar University（卡塔尔大学计算机科学系）；Ewha Womans University（成均馆大学）
Enhancing Robustness of Human Detection Algorithms in Maritime SAR through Augmented Aerial Images to Simulate Weather Conditions
Jakarta Intercultural School（雅加达国际学校）；Busan Foreign School（釜山外国语学校）；SMPK 8 Penabur Tanjung Duren（丹戎杜伦佩纳布尔8号初中（基督教学校））；Avon High School（雅芳高中）；Algoverse AI Research（Algoverse人工智能研究院）
ARCAS: An Augmented Reality Collision Avoidance System with SLAM-Based Tracking for Enhancing VRU Safety
Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin（德克萨斯大学奥斯汀分校土木、建筑与环境工程系）；School of Architecture, The University of Texas at Austin（德克萨斯大学奥斯汀分校建筑学院）
Tensor-Augmented Convolutional Neural Networks: Enhancing Expressivity with Generic Tensor Kernels
blueqat Inc.（blueqat公司）；Center for Quantum Science and Engineering, National Taiwan University（国立台湾大学量子科学与工程中心）；Graduate School of Science and Technology, Keio University（庆应义塾大学理工学研究科）；Keio University Sustainable Quantum Artificial Intelligence Center (KSQAIC)（庆应义塾大学可持续量子人工智能中心）
