5 papers
Omnimodal Dataset Distillation via High-order Proxy Alignment
Yuxuan Gao, Xiaohao Liu, Xiaobo Xia +1
Dataset distillation compresses large-scale datasets into compact synthetic sets while preserving training performance, but existing methods are largely restricted to single-modal…
Identifying Trustworthiness Challenges in Deep Learning Models for Continental-Scale Water Quality Prediction
Xiaobo Xia, Xiaofeng Liu, Jiale Liu +5
Water quality is foundational to environmental sustainability, ecosystem resilience, and public health. Deep learning offers transformative potential for large-scale water quality…
IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models
Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang +4
In-context learning is a promising paradigm that utilizes in-context examples as prompts for the predictions of large language models. These prompts are crucial for achieving stron…
DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception
Run Luo, Yunshui Li, Longze Chen +9
The development of large language models (LLMs) has significantly advanced the emergence of large multimodal models (LMMs). While LMMs have achieved tremendous success by promoting…
LaVin-DiT: Large Vision Diffusion Transformer
Zhaoqing Wang, Xiaobo Xia, Runnan Chen +4
This paper presents the Large Vision Diffusion Transformer (LaVin-DiT), a scalable and unified foundation model designed to tackle over 20 computer vision tasks in a generative fra…