no code implementations • TACL 2018 • Swapna Somasundaran, Michael Flor, Martin Chodorow, Hillary Molloy, Binod Gyawali, Laura McCulla
This work lays the foundation for automated assessments of narrative quality in student writing.
no code implementations • WS 2017 • Michael Flor, Swapna Somasundaran
Our lexical cohesion system achieves accuracy comparable to previously published baseline results.
no code implementations • COLING 2016 • Swapna Somasundaran, Brian Riordan, Binod Gyawali, Su-Youn Yoon
This work investigates whether the development of ideas in writing can be captured by graph properties derived from the text.
no code implementations • WS 2019 • Michael Flor, Swapna Somasundaran
This study explores the relation between lexical concreteness and narrative text quality.
no code implementations • WS 2020 • Swapna Somasundaran, Xianyang Chen, Michael Flor
This paper studies emotion arcs in student narratives.
no code implementations • EACL (BEA) 2021 • Goran Glavaš, Ananya Ganesh, Swapna Somasundaran
In this work, we focus on the domain transfer performance of supervised neural text segmentation in the educational domain.
no code implementations • 28 Oct 2022 • Sophia Chan, Swapna Somasundaran, Debanjan Ghosh, Mengxuan Zhao
We describe the AGReE system, which takes user-submitted passages as input and automatically generates grammar practice exercises that can be completed while reading.
no code implementations • 23 Apr 2024 • Kevin Stowe, Benny Longwill, Alyssa Francis, Tatsuya Aoyama, Debanjan Ghosh, Swapna Somasundaran
Natural language generation tools are powerful and effective for generating content.
1 code implementation • 3 Jan 2020 • Goran Glavaš, Swapna Somasundaran
Breaking down the structure of long texts into semantically coherent segments makes the texts more readable and supports downstream applications like summarization and retrieval.