Search Results for author: Frederick Reiss

Found 5 papers, 2 papers with code

Data Cleaning Tools for Token Classification Tasks

no code implementations NAACL (DaSH) 2021 Karthik Muthuraman, Frederick Reiss, Hong Xu, Bryan Cutler, Zachary Eichenberger

We incorporated our sieve into an end-to-end system for cleaning NLP corpora, implemented as a modular collection of Jupyter notebooks built on extensions to the Pandas DataFrame library.

Classification named-entity-recognition +4

CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks

1 code implementation25 May 2021 Ruchir Puri, David S. Kung, Geert Janssen, Wei zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir Choudhury, Lindsey Decker, Veronika Thost, Luca Buratti, Saurabh Pujar, Shyam Ramji, Ulrich Finkler, Susan Malaika, Frederick Reiss

In addition to its large scale, CodeNet has a rich set of high-quality annotations to benchmark and help accelerate research in AI techniques for a variety of critical coding tasks, including code similarity and classification, code translation between a large variety of programming languages, and code performance (runtime and memory) improvement techniques.

BIG-bench Machine Learning Code Classification +1

Identifying Incorrect Labels in the CoNLL-2003 Corpus

2 code implementations CONLL 2020 Frederick Reiss, Hong Xu, Bryan Cutler, Karthik Muthuraman, Zachary Eichenberger

The CoNLL-2003 corpus for English-language named entity recognition (NER) is one of the most influential corpora for NER model research.

named-entity-recognition Named Entity Recognition +1

SystemT: Declarative Text Understanding for Enterprise

no code implementations NAACL 2018 Laura Chiticariu, Marina Danilevsky, Yunyao Li, Frederick Reiss, Huaiyu Zhu

The rise of enterprise applications over unstructured and semi-structured documents poses new challenges to text understanding systems across multiple dimensions.

Document Classification Entity Extraction using GAN +3

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