A Dependency Treebank of Spoken Second Language English

no code implementations • NAACL (BEA) 2022 • Kristopher Kyle, Masaki Eguchi, Aaron Miller, Theodore Sither

In this paper, we introduce a dependency treebank of spoken second language (L2) English that is annotated with part of speech (Penn POS) tags and syntactic dependencies (Universal Dependencies).

POS

GPT4All: An Ecosystem of Open Source Compressed Language Models

1 code implementation • 6 Nov 2023 • Yuvanesh Anand, Zach Nussbaum, Adam Treat, Aaron Miller, Richard Guo, Ben Schmidt, GPT4All Community, Brandon Duderstadt, Andriy Mulyar

It is our hope that this paper acts as both a technical overview of the original GPT4All models as well as a case study on the subsequent growth of the GPT4All open source ecosystem.

SymForce: Symbolic Computation and Code Generation for Robotics

1 code implementation • 17 Apr 2022 • Hayk Martiros, Aaron Miller, Nathan Bucki, Bradley Solliday, Ryan Kennedy, Jack Zhu, Tung Dang, Dominic Pattison, Harrison Zheng, Teo Tomic, Peter Henry, Gareth Cross, Josiah VanderMey, Alvin Sun, Samuel Wang, Kristen Holtz

We present SymForce, a library for fast symbolic computation, code generation, and nonlinear optimization for robotics applications like computer vision, motion planning, and controls.

Code Generation Math +1

Towards Text Processing Pipelines to Identify Adverse Drug Events-related Tweets: University of Michigan @ SMM4H 2019 Task 1

no code implementations • WS 2019 • V.G.Vinod Vydiswaran, Grace Ganzel, Bryan Romas, Deahan Yu, Amy Austin, Neha Bhomia, Socheatha Chan, Stephanie Hall, Van Le, Aaron Miller, Olawunmi Oduyebo, Aulia Song, Radhika Sondhi, Danny Teng, Hao Tseng, Kim Vuong, Stephanie Zimmerman

We participated in Task 1 of the Social Media Mining for Health Applications (SMM4H) 2019 Shared Tasks on detecting mentions of adverse drug events (ADEs) in tweets.

BIG-bench Machine Learning