Linking WordNet to 3D Shapes

no code implementations • GWC 2018 • Angel X Chang, Rishi Mago, Pranav Krishna, Manolis Savva, Christiane Fellbaum

We describe a project to link the Princeton WordNet to 3D representations of real objects and scenes.

Solving Machine Learning Problems

1 code implementation • 2 Jul 2021 • Sunny Tran, Pranav Krishna, Ishan Pakuwal, Prabhakar Kafle, Nikhil Singh, Jayson Lynch, Iddo Drori

Our system demonstrates an overall accuracy of 96% for open-response questions and 97% for multiple-choice questions, compared with MIT students' average of 93%, achieving grade A performance in the course, all in real-time.

BIG-bench Machine Learning Data Augmentation +2

DART: Open-Domain Structured Data Record to Text Generation

2 code implementations • NAACL 2021 • Linyong Nan, Dragomir Radev, Rui Zhang, Amrit Rau, Abhinand Sivaprasad, Chiachun Hsieh, Xiangru Tang, Aadit Vyas, Neha Verma, Pranav Krishna, Yangxiaokang Liu, Nadia Irwanto, Jessica Pan, Faiaz Rahman, Ahmad Zaidi, Mutethia Mutuma, Yasin Tarabar, Ankit Gupta, Tao Yu, Yi Chern Tan, Xi Victoria Lin, Caiming Xiong, Richard Socher, Nazneen Fatema Rajani

Data-to-Text annotations can be a costly process, especially when dealing with tables which are the major source of structured data and contain nontrivial structures.

Domain Generalization Semantic Parsing +2