244 citations · 389 across the 28 of their papers we have counts for
6 papers · 1 filter
Scaling and Beyond: Advancing Spatial Reasoning in MLLMs Requires New Recipes
Huanyu Zhang, Chengzu Li, Wenshan Wu +8
Multimodal Large Language Models (MLLMs) have demonstrated impressive performance in general vision-language tasks. However, recent studies have exposed critical limitations in the…
TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting
Huanyu Zhang, Chang Xu, Yi-Fan Zhang +4
Time series forecasting plays a crucial role in data mining, driving rapid advancements across numerous industries. With the emergence of large models, time series foundation model…
OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling
Yi-Fan Zhang, Qingsong Wen, Xue Wang +6
Online updating of time series forecasting models aims to address the concept drifting problem by efficiently updating forecasting models based on streaming data. Many algorithms a…
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
Yi-Fan Zhang, Xue Wang, Kexin Jin +5
Many recent machine learning tasks focus to develop models that can generalize to unseen distributions. Domain generalization (DG) has become one of the key topics in various field…
A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts
Jian Liang, Ran He, Tieniu Tan
Machine learning methods strive to acquire a robust model during the training process that can effectively generalize to test samples, even in the presence of distribution shifts.…
Free Lunch for Domain Adversarial Training: Environment Label Smoothing
YiFan Zhang, Xue Wang, Jian Liang +4
A fundamental challenge for machine learning models is how to generalize learned models for out-of-distribution (OOD) data. Among various approaches, exploiting invariant features…