25 citations · 29 across the 7 of their papers we have counts for
9 papers · 1 filter
HGRN2: Gated Linear RNNs with State Expansion
Zhen Qin, Songlin Yang, Weixuan Sun +4
Hierarchically gated linear RNN (HGRN, \citealt{HGRN}) has demonstrated competitive training speed and performance in language modeling while offering efficient inference. However,…
Hierarchically Gated Recurrent Neural Network for Sequence Modeling
Zhen Qin, Songlin Yang, Yiran Zhong
Transformers have surpassed RNNs in popularity due to their superior abilities in parallel training and long-term dependency modeling. Recently, there has been a renewed interest i…
Joint Entity and Relation Extraction with Span Pruning and Hypergraph Neural Networks
Zhaohui Yan, Songlin Yang, Wei Liu +1
Entity and Relation Extraction (ERE) is an important task in information extraction. Recent marker-based pipeline models achieve state-of-the-art performance, but still suffer from…
Simple Hardware-Efficient PCFGs with Independent Left and Right Productions
Wei Liu, Songlin Yang, Yoon Kim +1
Scaling dense PCFGs to thousands of nonterminals via a low-rank parameterization of the rule probability tensor has been shown to be beneficial for unsupervised parsing. However, P…
Dynamic Programming in Rank Space: Scaling Structured Inference with Low-Rank HMMs and PCFGs
Songlin Yang, Wei Liu, Kewei Tu
Hidden Markov Models (HMMs) and Probabilistic Context-Free Grammars (PCFGs) are widely used structured models, both of which can be represented as factor graph grammars (FGGs), a p…
Nested Named Entity Recognition as Latent Lexicalized Constituency Parsing
Chao Lou, Songlin Yang, Kewei Tu
Nested named entity recognition (NER) has been receiving increasing attention. Recently, (Fu et al, 2021) adapt a span-based constituency parser to tackle nested NER. They treat ne…