787 citations · 1.2k across the 12 of their papers we have counts for
15 papers
Learning World Graphs to Accelerate Hierarchical Reinforcement Learning
Wenling Shang, Alex Trott, Stephan Zheng +2
In many real-world scenarios, an autonomous agent often encounters various tasks within a single complex environment. We propose to build a graph abstraction over the environment s…
Explain Yourself! Leveraging Language Models for Commonsense Reasoning
Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong +1
Deep learning models perform poorly on tasks that require commonsense reasoning, which often necessitates some form of world-knowledge or reasoning over information not immediately…
SParC: Cross-Domain Semantic Parsing in Context
Tao Yu, Rui Zhang, Michihiro Yasunaga +16
We present SParC, a dataset for cross-domainSemanticParsing inContext that consists of 4,298 coherent question sequences (12k+ individual questions annotated with SQL queries). It…
On the Generalization Gap in Reparameterizable Reinforcement Learning
Huan Wang, Stephan Zheng, Caiming Xiong +1
Understanding generalization in reinforcement learning (RL) is a significant challenge, as many common assumptions of traditional supervised learning theory do not apply. We focus…
XLDA: Cross-Lingual Data Augmentation for Natural Language Inference and Question Answering
Jasdeep Singh, Bryan McCann, Nitish Shirish Keskar +2
While natural language processing systems often focus on a single language, multilingual transfer learning has the potential to improve performance, especially for low-resource lan…
Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems
Chien-Sheng Wu, Andrea Madotto, Ehsan Hosseini-Asl +3
Over-dependence on domain ontology and lack of knowledge sharing across domains are two practical and yet less studied problems of dialogue state tracking. Existing approaches gene…