Vivek Srikumar

EDISON: Feature Extraction for NLP, Simplified

2016

When designing Natural Language Processing (NLP) applications that use Machine Learning (ML) techniques, feature extraction becomes a significant part of the development effort, whether developing a new application or attempting to reproduce results reported for …

Adposition Supersenses v2.

2017 · arXiv (Cornell University)

This document describes an inventory of 50 semantic labels designed to characterize the use of adpositions and case markers at a somewhat coarse level of granularity. Version 2 is a revision of the supersense inventory …

A Simple Global Neural Discourse Parser

2020 · arXiv (Cornell University)

Discourse parsing is largely dominated by greedy parsers with manually-designed features, while global parsing is rare due to its computational expense. In this paper, we propose a simple chart-based neural discourse parser that does not …

DirectProbe: Studying Representations without Classifiers

2021 · arXiv (Cornell University)

Understanding how linguistic structures are encoded in contextualized embedding could help explain their impressive performance across NLP@. Existing approaches for probing them usually call for training classifiers and use the accuracy, mutual information, or complexity …