4 papers
Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey and Benchmark
Yi Xin, Jianjiang Yang, Siqi Luo +10
Pre-trained vision models (PVMs) have demonstrated remarkable adaptability across a wide range of downstream vision tasks, showcasing exceptional performance. However, as these mod…
Enhancing Test Time Adaptation with Few-shot Guidance
Siqi Luo, Yi Xin, Yuntao Du +3
Deep neural networks often encounter significant performance drops while facing with domain shifts between training (source) and test (target) data. To address this issue, Test Tim…
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…