200 citations · 244 across the 7 of their papers we have counts for
8 papers
Measuring Learned Equivariance: An Information Theoretic Approach
Claire Schlesinger, Wolfgang Gatterbauer, Robin Walters
Learning symmetries through data augmentation offers an alternative to architectural equivariance, but does not guarantee that a network respects those symmetries. Measuring learne…
PRISMat: Policy-Driven, Permutation-Invariant Autoregressive Material Generation
Claire Schlesinger, Circe Hsu, Peter Schindler +1
Rapid identification of candidate materials with target properties has become a key task in materials science. Machine learning has emerged as an alternative to physics-based simul…
FIRE-GNN: Force-informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties
Circe Hsu, Claire Schlesinger, Karan Mudaliar +3
The work function and cleavage energy of a surface are critical properties that determine the viability of materials in electronic emission applications, semiconductor devices, and…
Creating and Repairing Robot Programs in Open-World Domains
Claire Schlesinger, Arjun Guha, Joydeep Biswas
Using Large Language Models (LLMs) to produce robot programs from natural language has allowed for robot systems that can complete a higher diversity of tasks. However, LLM-generat…
Equivariant Graph Neural Networks for Prediction of Tensor Material Properties of Crystals
Alex Heilman, Claire Schlesinger, Qimin Yan
Modern E(3)-Equivariant networks may be used to predict rotationally equivariant properties, including tensorial quantities. Three such quantities: the dielectric, piezoelectric, a…
Deploying and Evaluating LLMs to Program Service Mobile Robots
Zichao Hu, Francesca Lucchetti, Claire Schlesinger +5
Recent advancements in large language models (LLMs) have spurred interest in using them for generating robot programs from natural language, with promising initial results. We inve…
Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs
Federico Cassano, John Gouwar, Francesca Lucchetti +7
Over the past few years, Large Language Models of Code (Code LLMs) have started to have a significant impact on programming practice. Code LLMs are also emerging as building blocks…
StarCoder: may the source be with you!
Raymond Li, Loubna Ben Allal, Yangtian Zi +64
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase…