2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2022
Linear RNNs Provably Learn Linear Dynamic Systems
Lifu Wang, Tianyu Wang, Shengwei Yi +3
We study the learning ability of linear recurrent neural networks with Gradient Descent. We prove the first theoretical guarantee on linear RNNs to learn any stable linear dynamic…
cs.LG2021★ 1 cited
On the Provable Generalization of Recurrent Neural Networks
Lifu Wang, Bo Shen, Bo Hu +1
Recurrent Neural Network (RNN) is a fundamental structure in deep learning. Recently, some works study the training process of over-parameterized neural networks, and show that ove…
cs.CL2021★ 2 cited
Coarse-grained decomposition and fine-grained interaction for multi-hop question answering
Xing Cao, Yun Liu
Recent advances regarding question answering and reading comprehension have resulted in models that surpass human performance when the answer is contained in a single, continuous p…