4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CV2026
Better Rigs, Not Bigger Networks: A Body Model Ablation for Gaussian Avatars
Derek Austin
Recent 3D Gaussian splatting methods built atop SMPL achieve remarkable visual fidelity while continually increasing the complexity of the overall training architecture. We demonst…
cs.CL2024★ 1 cited
GRAD-SUM: Leveraging Gradient Summarization for Optimal Prompt Engineering
Derek Austin, Elliott Chartock
Prompt engineering for large language models (LLMs) is often a manual time-intensive process that involves generating, evaluating, and refining prompts iteratively to ensure high-q…
cs.LG2022★ 4 cited
From Human Days to Machine Seconds: Automatically Answering and Generating Machine Learning Final Exams
Iddo Drori, Sarah J. Zhang, Reece Shuttleworth +13
A final exam in machine learning at a top institution such as MIT, Harvard, or Cornell typically takes faculty days to write, and students hours to solve. We demonstrate that large…