5 citations · 7 across the 5 of their papers we have counts for
6 papers
Worth Their Weights? Evaluating Generative Models for Discourse Parsing
Luke Gessler, Amir Zeldes
Rhetorical Structure Theory (RST) parsing has historically been dominated by discriminative models based on pretrained encoder-only language models. The recent availability of high…
eRST: A Signaled Graph Theory of Discourse Relations and Organization
Amir Zeldes, Tatsuya Aoyama, Yang Janet Liu +3
In this article we present Enhanced Rhetorical Structure Theory (eRST), a new theoretical framework for computational discourse analysis, based on an expansion of Rhetorical Struct…
GENTLE: A Genre-Diverse Multilayer Challenge Set for English NLP and Linguistic Evaluation
Tatsuya Aoyama, Shabnam Behzad, Luke Gessler +6
We present GENTLE, a new mixed-genre English challenge corpus totaling 17K tokens and consisting of 8 unusual text types for out-of domain evaluation: dictionary entries, esports c…
MicroBERT: Effective Training of Low-resource Monolingual BERTs through Parameter Reduction and Multitask Learning
Luke Gessler, Amir Zeldes
Transformer language models (TLMs) are critical for most NLP tasks, but they are difficult to create for low-resource languages because of how much pretraining data they require. I…
DisCoDisCo at the DISRPT2021 Shared Task: A System for Discourse Segmentation, Classification, and Connective Detection
Luke Gessler, Shabnam Behzad, Yang Janet Liu +3
This paper describes our submission to the DISRPT2021 Shared Task on Discourse Unit Segmentation, Connective Detection, and Relation Classification. Our system, called DisCoDisCo,…
AMALGUM -- A Free, Balanced, Multilayer English Web Corpus
Luke Gessler, Siyao Peng, Yang Liu +3
We present a freely available, genre-balanced English web corpus totaling 4M tokens and featuring a large number of high-quality automatic annotation layers, including dependency t…