252 citations · 2k across the 56 of their papers we have counts for
6 papers · 2 filters
ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models
Jiannan Xiang, Zhengzhong Liu, Yucheng Zhou +2
Data-to-text generation is challenging due to the great variety of the input data in terms of domains (e.g., finance vs sports) or schemata (e.g., diverse predicates). Recent end-t…
Composable Text Controls in Latent Space with ODEs
Guangyi Liu, Zeyu Feng, Yuan Gao +7
Real-world text applications often involve composing a wide range of text control operations, such as editing the text w.r.t. an attribute, manipulating keywords and structure, and…
BertNet: Harvesting Knowledge Graphs with Arbitrary Relations from Pretrained Language Models
Shibo Hao, Bowen Tan, Kaiwen Tang +5
It is crucial to automatically construct knowledge graphs (KGs) of diverse new relations to support knowledge discovery and broad applications. Previous KG construction methods, ba…
RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh +6
Prompting has shown impressive success in enabling large pretrained language models (LMs) to perform diverse NLP tasks, especially when only few downstream data are available. Auto…
elBERto: Self-supervised Commonsense Learning for Question Answering
Xunlin Zhan, Yuan Li, Xiao Dong +3
Commonsense question answering requires reasoning about everyday situations and causes and effects implicit in context. Typically, existing approaches first retrieve external evide…
A Causal Lens for Controllable Text Generation
Zhiting Hu, Li Erran Li
Controllable text generation concerns two fundamental tasks of wide applications, namely generating text of given attributes (i.e., attribute-conditional generation), and minimally…