Daqing
Book
Your Out-of-Distribution Detection Method is Not Robust!
Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation
This paper introduces a novel approach using Large Language Models (LLMs) integrated into an agent framework for flexible and effective personal mobility generation. LLMs overcome the limitations of previous models by effectively processing semantic data and offering versatility in modeling various tasks.
SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusion Ming Dai 1, Lingfeng Y ang
Visual grounding is a common vision task that involves grounding descriptive sentences to the corresponding regions of an image. Most existing methods use independent image-text encoding and apply complex hand-crafted modules or encoder-decoder architectures for modal interaction and query reasoning.
Few-Shot Task Learning through Inverse Generative Modeling
Learning the intents of an agent, defined by its goals or motion style, is often extremely challenging from just a few examples.
Domain Re-Modulation for Few-Shot Generative Domain Adaptation Yi Wu, Ziqiang Li University of Science and Technology of China Chaoyue Wang, Heliang Zheng, Shanshan Zhao JD Explore Academy Bin Li
In this study, we delve into the task of few-shot Generative Domain Adaptation (GDA), which involves transferring a pre-trained generator from one domain to a new domain using only a few reference images. Inspired by the way human brains acquire knowledge in new domains, we present an innovative generator structure called Domain Re-Modulation (DoRM) .