9 citations · 13 across the 5 of their papers we have counts for
5 papers · 1 filter
Long-Tailed Out-of-Distribution Detection with Refined Separate Class Learning
Shuai Feng, Yuxin Ge, Yuntao Du +3
Out-of-distribution (OOD) detection is crucial for deploying robust machine learning models. However, when training data follows a long-tailed distribution, the model's ability to…
Benchmarking Multimodal Knowledge Conflict for Large Multimodal Models
Yifan Jia, Kailin Jiang, Yuyang Liang +11
Large Multimodal Models(LMMs) face notable challenges when encountering multimodal knowledge conflicts, particularly under retrieval-augmented generation(RAG) frameworks where the…
Learning with Noisy Labels over Imbalanced Subpopulations
MingCai Chen, Yu Zhao, Bing He +3
Learning with Noisy Labels (LNL) has attracted significant attention from the research community. Many recent LNL methods rely on the assumption that clean samples tend to have "sm…
Spatial-Temporal Graph Convolutional Gated Recurrent Network for Traffic Forecasting
Le Zhao, Mingcai Chen, Yuntao Du +2
As an important part of intelligent transportation systems, traffic forecasting has attracted tremendous attention from academia and industry. Despite a lot of methods being propos…
Generation, augmentation, and alignment: A pseudo-source domain based method for source-free domain adaptation
Yuntao Du, Haiyang Yang, Mingcai Chen +3
Conventional unsupervised domain adaptation (UDA) methods need to access both labeled source samples and unlabeled target samples simultaneously to train the model. While in some s…