24 citations · 64 across the 10 of their papers we have counts for
5 papers · 1 filter
DataComp-LM: In search of the next generation of training sets for language models
Jeffrey Li, Alex Fang, Georgios Smyrnis +56
We introduce DataComp for Language Models (DCLM), a testbed for controlled dataset experiments with the goal of improving language models. As part of DCLM, we provide a standardize…
Optimal Sparse Survival Trees
Rui Zhang, Rui Xin, Margo Seltzer +1
Interpretability is crucial for doctors, hospitals, pharmaceutical companies and biotechnology corporations to analyze and make decisions for high stakes problems that involve huma…
Optimal Sparse Regression Trees
Rui Zhang, Rui Xin, Margo Seltzer +1
Regression trees are one of the oldest forms of AI models, and their predictions can be made without a calculator, which makes them broadly useful, particularly for high-stakes app…
Exploring the Whole Rashomon Set of Sparse Decision Trees
Rui Xin, Chudi Zhong, Zhi Chen +3
In any given machine learning problem, there may be many models that could explain the data almost equally well. However, most learning algorithms return only one of these models,…
Multitask Learning for Citation Purpose Classification
Alex Oesterling, Angikar Ghosal, Haoyang Yu +4
We present our entry into the 2021 3C Shared Task Citation Context Classification based on Purpose competition. The goal of the competition is to classify a citation in a scientifi…