5 papers
Sparse CLIP: Co-Optimizing Interpretability and Performance in Contrastive Learning
Chuan Qin, Constantin Venhoff, Sonia Joseph +2
Contrastive Language-Image Pre-training (CLIP) has become a cornerstone in vision-language representation learning, powering diverse downstream tasks and serving as the default vis…
FACE: A General Framework for Mapping Collaborative Filtering Embeddings into LLM Tokens
Chao Wang, Yixin Song, Jinhui Ye +5
Recently, large language models (LLMs) have been explored for integration with collaborative filtering (CF)-based recommendation systems, which are crucial for personalizing user e…
TransLLM: A Unified Multi-Task Foundation Framework for Urban Transportation via Learnable Prompting
Jiaming Leng, Yunying Bi, Chuan Qin +3
Urban transportation systems encounter diverse challenges across multiple tasks, such as traffic forecasting, electric vehicle (EV) charging demand prediction, and taxi dispatch. E…
Think Hierarchically, Act Dynamically: Hierarchical Multi-modal Fusion and Reasoning for Vision-and-Language Navigation
Junrong Yue, Yifan Zhang, Chuan Qin +5
Vision-and-Language Navigation (VLN) aims to enable embodied agents to follow natural language instructions and reach target locations in real-world environments. While prior metho…
Diffusion Features to Bridge Domain Gap for Semantic Segmentation
Yuxiang Ji, Boyong He, Chenyuan Qu +3
Pre-trained diffusion models have demonstrated remarkable proficiency in synthesizing images across a wide range of scenarios with customizable prompts, indicating their effective…