Web: http://arxiv.org/abs/2209.07442

Sept. 16, 2022, 1:16 a.m. | Aliva Das, Xinya Du, Barry Wang, Kejian Shi, Jiayuan Gu, Thomas Porter, Claire Cardie

cs.CL updates on arXiv.org arxiv.org

Document-level information extraction (IE) tasks have recently begun to be
revisited in earnest using the end-to-end neural network techniques that have
been successful on their sentence-level IE counterparts. Evaluation of the
approaches, however, has been limited in a number of dimensions. In particular,
the precision/recall/F1 scores typically reported provide few insights on the
range of errors the models make. We build on the work of Kummerfeld and Klein
(2013) to propose a transformation-based framework for automating error
analysis in document-level …

analysis arxiv error extraction information information extraction

More from arxiv.org / cs.CL updates on arXiv.org

Postdoctoral Fellow: ML for autonomous materials discovery

@ Lawrence Berkeley National Lab | Berkeley, CA

Research Scientists

@ ODU Research Foundation | Norfolk, Virginia

Embedded Systems Engineer (Robotics)

@ Neo Cybernetica | Bedford, New Hampshire

2023 Luis J. Alvarez and Admiral Grace M. Hopper Postdoc Fellowship in Computing Sciences

@ Lawrence Berkeley National Lab | San Francisco, CA

Senior Manager Data Scientist

@ NAV | Remote, US

Senior AI Research Scientist

@ Earth Species Project | Remote anywhere

Research Fellow- Center for Security and Emerging Technology (Multiple Opportunities)

@ University of California Davis | Washington, DC

Staff Fellow - Data Scientist

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Staff Fellow - Senior Data Engineer

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Software Engineer, Machine Learning

@ Next Insurance | Atlanta

Big Data Engineer- E4076

@ Nisum | United States

[Job-8613] Data Engineer SR.

@ CI&T | Brazil