activity
20142022
most citedMemory Augmented Policy Optimization for Program Synthesis and Semantic Parsing

96 citations · 317 across the 17 of their papers we have counts for

collaborators

17 papers

cs.CL2022★ 13 cited

RARR: Researching and Revising What Language Models Say, Using Language Models

Luyu Gao, Zhuyun Dai, Panupong Pasupat +8

Language models (LMs) now excel at many tasks such as few-shot learning, question answering, reasoning, and dialog. However, they sometimes generate unsupported or misleading conte…

cs.CL2021★ 6 cited

Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions

Gengchen Mai, Krzysztof Janowicz, Rui Zhu +2

As an important part of Artificial Intelligence (AI), Question Answering (QA) aims at generating answers to questions phrased in natural language. While there has been substantial…

cs.CL2020

Pivot Through English: Reliably Answering Multilingual Questions without Document Retrieval

Ivan Montero, Shayne Longpre, Ni Lao +2

Existing methods for open-retrieval question answering in lower resource languages (LRLs) lag significantly behind English. They not only suffer from the shortcomings of non-Englis…

cs.DB2020★ 87 cited

SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting

Gengchen Mai, Krzysztof Janowicz, Ling Cai +5

Learning knowledge graph (KG) embeddings is an emerging technique for a variety of downstream tasks such as summarization, link prediction, information retrieval, and question answ…

cs.IR2020★ 1 cited

Semantically-Enriched Search Engine for Geoportals: A Case Study with ArcGIS Online

Gengchen Mai, Krzysztof Janowicz, Sathya Prasad +5

Many geoportals such as ArcGIS Online are established with the goal of improving geospatial data reusability and achieving intelligent knowledge discovery. However, according to pr…

cs.CV2020★ 15 cited

Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells

Gengchen Mai, Krzysztof Janowicz, Bo Yan +3

Unsupervised text encoding models have recently fueled substantial progress in NLP. The key idea is to use neural networks to convert words in texts to vector space representations…