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20162022
most citedNeural Multi-task Learning in Automated Assessment

14 citations · 14 across the 8 of their papers we have counts for

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Showing cs.CLShow all

19 papers · 1 filter

cs.CL2022

Probing for targeted syntactic knowledge through grammatical error detection

Christopher Davis, Christopher Bryant, Andrew Caines +2

Targeted studies testing knowledge of subject-verb agreement (SVA) indicate that pre-trained language models encode syntactic information. We assert that if models robustly encode…

cs.CL2021

How Metaphors Impact Political Discourse: A Large-Scale Topic-Agnostic Study Using Neural Metaphor Detection

Vinodkumar Prabhakaran, Marek Rei, Ekaterina Shutova

Metaphors are widely used in political rhetoric as an effective framing device. While the efficacy of specific metaphors such as the war metaphor in political discourse has been do…

cs.CL2021

Zero-shot Sequence Labeling for Transformer-based Sentence Classifiers

Kamil Bujel, Helen Yannakoudakis, Marek Rei

We investigate how sentence-level transformers can be modified into effective sequence labelers at the token level without any direct supervision. Existing approaches to zero-shot…

cs.CL2020

Seeing Both the Forest and the Trees: Multi-head Attention for Joint Classification on Different Compositional Levels

Miruna Pislar, Marek Rei

In natural languages, words are used in association to construct sentences. It is not words in isolation, but the appropriate combination of hierarchical structures that conveys th…

cs.CL2020

GiBERT: Introducing Linguistic Knowledge into BERT through a Lightweight Gated Injection Method

Nicole Peinelt, Marek Rei, Maria Liakata

Large pre-trained language models such as BERT have been the driving force behind recent improvements across many NLP tasks. However, BERT is only trained to predict missing words…

cs.CL2020

Grammatical Error Correction in Low Error Density Domains: A New Benchmark and Analyses

Simon Flachs, Ophélie Lacroix, Helen Yannakoudakis +2

Evaluation of grammatical error correction (GEC) systems has primarily focused on essays written by non-native learners of English, which however is only part of the full spectrum…