337 citations · 369 across the 9 of their papers we have counts for
5 papers · 1 filter
MolXPT: Wrapping Molecules with Text for Generative Pre-training
Zequn Liu, Wei Zhang, Yingce Xia +5
Generative pre-trained Transformer (GPT) has demonstrates its great success in natural language processing and related techniques have been adapted into molecular modeling. Conside…
MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information Networks
Zequn Liu, Kefei Duan, Junwei Yang +3
Heterogeneous Information Network (HIN) is essential to study complicated networks containing multiple edge types and node types. Meta-path, a sequence of node types and edge types…
Graphine: A Dataset for Graph-aware Terminology Definition Generation
Zequn Liu, Shukai Wang, Yiyang Gu +3
Precisely defining the terminology is the first step in scientific communication. Developing neural text generation models for definition generation can circumvent the labor-intens…
When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications
Zequn Liu, Ruiyi Zhang, Yiping Song +2
Model-Agnostic Meta-Learning (MAML), a model-agnostic meta-learning method, is successfully employed in NLP applications including few-shot text classification and multi-domain low…
Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks
Yiping Song, Zequn Liu, Wei Bi +2
Training the generative models with minimal corpus is one of the critical challenges for building open-domain dialogue systems. Existing methods tend to use the meta-learning frame…