1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2023★ 1 cited
Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study
Boxin Wang, Wei Ping, Peng Xu +9
Large decoder-only language models (LMs) can be largely improved in terms of perplexity by retrieval (e.g., RETRO), but its impact on text generation quality and downstream task ac…
cs.CL2022★ 1 cited
CoRRPUS: Code-based Structured Prompting for Neurosymbolic Story Understanding
Yijiang River Dong, Lara J. Martin, Chris Callison-Burch
Story generation and understanding -- as with all NLG/NLU tasks -- has seen a surge in neurosymbolic work. Researchers have recognized that, while large language models (LLMs) have…
cs.CL2022
Informative Text Generation from Knowledge Triples
Zihao Fu, Yijiang River Dong, Lidong Bing +1
As the development of the encoder-decoder architecture, researchers are able to study the text generation tasks with broader types of data. Among them, KB-to-text aims at convertin…