62 citations · 72 across the 11 of their papers we have counts for
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cs.LG2025
Mixture of Lookup Experts
Shibo Jie, Yehui Tang, Kai Han +4
Mixture-of-Experts (MoE) activates only a subset of experts during inference, allowing the model to maintain low inference FLOPs and latency even as the parameter count scales up.…
cs.LG2023★ 1 cited
Detachedly Learn a Classifier for Class-Incremental Learning
Ziheng Li, Shibo Jie, Zhi-Hong Deng
In continual learning, model needs to continually learn a feature extractor and classifier on a sequence of tasks. This paper focuses on how to learn a classifier based on a pretra…
cs.LG2022★ 1 cited
Bypassing Logits Bias in Online Class-Incremental Learning with a Generative Framework
Gehui Shen, Shibo Jie, Ziheng Li +1
Continual learning requires the model to maintain the learned knowledge while learning from a non-i.i.d data stream continually. Due to the single-pass training setting, online con…