3 papers
cs.CL2024
Unsupervised Morphological Tree Tokenizer
Qingyang Zhu, Xiang Hu, Pengyu Ji +2
As a cornerstone in language modeling, tokenization involves segmenting text inputs into pre-defined atomic units. Conventional statistical tokenizers often disrupt constituent bou…
cs.CL2024
Generative Pretrained Structured Transformers: Unsupervised Syntactic Language Models at Scale
Xiang Hu, Pengyu Ji, Qingyang Zhu +2
A syntactic language model (SLM) incrementally generates a sentence with its syntactic tree in a left-to-right manner. We present Generative Pretrained Structured Transformers (GPS…
cs.CL2023
Augmenting Transformers with Recursively Composed Multi-grained Representations
Xiang Hu, Qingyang Zhu, Kewei Tu +1
We present ReCAT, a recursive composition augmented Transformer that is able to explicitly model hierarchical syntactic structures of raw texts without relying on gold trees during…