no code implementations • 21 Mar 2024 • Qingwen Lin, Boyan Xu, Zhengting Huang, Ruichu Cai
In light of these challenges, we introduce an innovative two-stage framework that adeptly transfers mathematical Expertise from large to tiny language models.
no code implementations • 14 Feb 2024 • Xuexin Chen, Ruichu Cai, Kaitao Zheng, Zhifan Jiang, Zhengting Huang, Zhifeng Hao, Zijian Li
Under mild conditions, we show that the invariant subgraph can be extracted by minimizing an upper bound, which is built on the theoretical advance of probability of necessity and sufficiency.
no code implementations • 13 Feb 2024 • Xuexin Chen, Ruichu Cai, Zhengting Huang, Yuxuan Zhu, Julien Horwood, Zhifeng Hao, Zijian Li, Jose Miguel Hernandez-Lobato
In order to enhance the ability of FAMs to distinguish different features' contributions in this challenging setting, we propose to utilize the Probability of Necessity and Sufficiency (PNS) that perturbing a feature is a necessary and sufficient cause for the prediction to change as a measure of feature importance.