36 citations · 78 across the 9 of their papers we have counts for
12 papers
Learning Object-Language Alignments for Open-Vocabulary Object Detection
Chuang Lin, Peize Sun, Yi Jiang +5
Existing object detection methods are bounded in a fixed-set vocabulary by costly labeled data. When dealing with novel categories, the model has to be retrained with more bounding…
Simple or Complex? Complexity-Controllable Question Generation with Soft Templates and Deep Mixture of Experts Model
Sheng Bi, Xiya Cheng, Yuan-Fang Li +5
The ability to generate natural-language questions with controlled complexity levels is highly desirable as it further expands the applicability of question generation. In this pap…
Total Recall: a Customized Continual Learning Method for Neural Semantic Parsers
Zhuang Li, Lizhen Qu, Gholamreza Haffari
This paper investigates continual learning for semantic parsing. In this setting, a neural semantic parser learns tasks sequentially without accessing full training data from previ…
Neural-Symbolic Commonsense Reasoner with Relation Predictors
Farhad Moghimifar, Lizhen Qu, Yue Zhuo +2
Commonsense reasoning aims to incorporate sets of commonsense facts, retrieved from Commonsense Knowledge Graphs (CKG), to draw conclusion about ordinary situations. The dynamic na…
On Robustness of Neural Semantic Parsers
Shuo Huang, Zhuang Li, Lizhen Qu +1
Semantic parsing maps natural language (NL) utterances into logical forms (LFs), which underpins many advanced NLP problems. Semantic parsers gain performance boosts with deep neur…
Few-Shot Semantic Parsing for New Predicates
Zhuang Li, Lizhen Qu, Shuo Huang +1
In this work, we investigate the problems of semantic parsing in a few-shot learning setting. In this setting, we are provided with utterance-logical form pairs per new predicate.…