190 citations · 238 across the 26 of their papers we have counts for
6 papers · 1 filter
A Neural Network Solves, Explains, and Generates University Math Problems by Program Synthesis and Few-Shot Learning at Human Level
Iddo Drori, Sarah Zhang, Reece Shuttleworth +15
We demonstrate that a neural network pre-trained on text and fine-tuned on code solves mathematics course problems, explains solutions, and generates new questions at a human level…
Solving Probability and Statistics Problems by Program Synthesis
Leonard Tang, Elizabeth Ke, Nikhil Singh +2
We solve university level probability and statistics questions by program synthesis using OpenAI's Codex, a Transformer trained on text and fine-tuned on code. We transform course…
Image2Lego: Customized LEGO Set Generation from Images
Kyle Lennon, Katharina Fransen, Alexander O'Brien +5
Although LEGO sets have entertained generations of children and adults, the challenge of designing customized builds matching the complexity of real-world or imagined scenes remain…
Solving Machine Learning Problems
Sunny Tran, Pranav Krishna, Ishan Pakuwal +4
Can a machine learn Machine Learning? This work trains a machine learning model to solve machine learning problems from a University undergraduate level course. We generate a new t…
Privileged Zero-Shot AutoML
Nikhil Singh, Brandon Kates, Jeff Mentch +3
This work improves the quality of automated machine learning (AutoML) systems by using dataset and function descriptions while significantly decreasing computation time from minute…
Image2Reverb: Cross-Modal Reverb Impulse Response Synthesis
Nikhil Singh, Jeff Mentch, Jerry Ng +2
Measuring the acoustic characteristics of a space is often done by capturing its impulse response (IR), a representation of how a full-range stimulus sound excites it. This work ge…