2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.AI2023★ 1 cited
D-Separation for Causal Self-Explanation
Wei Liu, Jun Wang, Haozhao Wang +4
Rationalization is a self-explaining framework for NLP models. Conventional work typically uses the maximum mutual information (MMI) criterion to find the rationale that is most in…
cs.CV2023★ 2 cited
Transform-Equivariant Consistency Learning for Temporal Sentence Grounding
Daizong Liu, Xiaoye Qu, Jianfeng Dong +6
This paper addresses the temporal sentence grounding (TSG). Although existing methods have made decent achievements in this task, they not only severely rely on abundant video-quer…
cs.LG2023★ 1 cited
DualMix: Unleashing the Potential of Data Augmentation for Online Class-Incremental Learning
Yunfeng Fan, Wenchao Xu, Haozhao Wang +3
Online Class-Incremental (OCI) learning has sparked new approaches to expand the previously trained model knowledge from sequentially arriving data streams with new classes. Unfort…