3 papers
cs.LG2026
Consistency-Driven Calibration and Matching for Few-Shot Class-Incremental Learning
Qinzhe Wang, Zixuan Chen, Keke Huang +3
Few-Shot Class Incremental Learning (FSCIL) is crucial for adapting to the complex open-world environments. Contemporary prospective learning-based space construction methods strug…
cs.LG2025
DeCoP: Enhancing Self-Supervised Time Series Representation with Dependency Controlled Pre-training
Yuemin Wu, Zhongze Wu, Xiu Su +6
Modeling dynamic temporal dependencies is a critical challenge in time series pre-training, which evolve due to distribution shifts and multi-scale patterns. This temporal variabil…
cs.LG2025
Identify, Isolate, and Purge: Mitigating Hallucinations in LVLMs via Self-Evolving Distillation
Wenhao Li, Xiu Su, Jingyi Wu +5
Large Vision-Language Models (LVLMs) have demonstrated remarkable advancements in numerous areas such as multimedia. However, hallucination issues significantly limit their credibi…