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07/17/2023
On the application of Large Language Models for language teaching and assessment technology
The recent release of very large language models such as PaLM and GPT-4 ...
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03/14/2023
Finding the Needle in a Haystack: Unsupervised Rationale Extraction from Long Text Classifiers
Long-sequence transformers are designed to improve the representation of...
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02/17/2023
CK-Transformer: Commonsense Knowledge Enhanced Transformers for Referring Expression Comprehension
The task of multimodal referring expression comprehension (REC), aiming ...
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01/25/2023
FewShotTextGCN: K-hop neighborhood regularization for few-shot learning on graphs
We present FewShotTextGCN, a novel method designed to effectively utiliz...
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11/28/2022
Scientific and Creative Analogies in Pretrained Language Models
This paper examines the encoding of analogy in large-scale pretrained la...
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10/31/2022
Learning New Tasks from a Few Examples with Soft-Label Prototypes
It has been experimentally demonstrated that humans are able to learn in...
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06/10/2021
Ruddit: Norms of Offensiveness for English Reddit Comments
On social media platforms, hateful and offensive language negatively imp...
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04/10/2021
Meta-learning for fast cross-lingual adaptation in dependency parsing
Meta-learning, or learning to learn, is a technique that can help to ove...
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03/31/2021
The User behind the Abuse: A Position on Ethics and Explainability
Abuse on the Internet is an important societal problem of our time. Mill...
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03/26/2021
Turning transformer attention weights into zero-shot sequence labelers
We demonstrate how transformer-based models can be redesigned in order t...
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01/27/2021
Multilingual and cross-lingual document classification: A meta-learning approach
The great majority of languages in the world are considered under-resour...
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12/23/2020
A Multimodal Framework for the Detection of Hateful Memes
An increasingly common expression of online hate speech is multimodal in...
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11/13/2020
The Teacher-Student Chatroom Corpus
The Teacher-Student Chatroom Corpus (TSCC) is a collection of written co...
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11/12/2020
Analyzing Neural Discourse Coherence Models
In this work, we systematically investigate how well current models of c...
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10/15/2020
Grammatical Error Correction in Low Error Density Domains: A New Benchmark and Analyses
Evaluation of grammatical error correction (GEC) systems has primarily f...
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09/10/2020
Meta-Learning with Sparse Experience Replay for Lifelong Language Learning
Lifelong learning requires models that can continuously learn from seque...
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08/14/2020
Graph-based Modeling of Online Communities for Fake News Detection
Over the past few years, there has been substantial effort towards autom...
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05/28/2020
Joint Modelling of Emotion and Abusive Language Detection
The rise of online communication platforms has been accompanied by some ...
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04/29/2020
Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation
Deep learning methods typically rely on large amounts of annotated data ...
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08/13/2019
Tackling Online Abuse: A Survey of Automated Abuse Detection Methods
Abuse on the Internet represents an important societal problem of our ti...
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07/04/2019
Multi-Task Learning for Coherence Modeling
We address the task of assessing discourse coherence, an aspect of text ...
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06/15/2019
Context is Key: Grammatical Error Detection with Contextual Word Representations
Grammatical error detection (GED) in non-native writing requires systems...
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04/05/2019
Abusive Language Detection with Graph Convolutional Networks
Abuse on the Internet represents a significant societal problem of our t...
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04/03/2019
Learning Outside the Box: Discourse-level Features Improve Metaphor Identification
Most current approaches to metaphor identification use restricted lingui...
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02/14/2019
Author Profiling for Hate Speech Detection
The rapid growth of social media in recent years has fed into some highl...
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09/02/2018
Neural Character-based Composition Models for Abuse Detection
The advent of social media in recent years has fed into some highly unde...
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04/18/2018
Neural Automated Essay Scoring and Coherence Modeling for Adversarially Crafted Input
We demonstrate that current state-of-the-art approaches to Automated Ess...
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07/17/2017
Auxiliary Objectives for Neural Error Detection Models
We investigate the utility of different auxiliary objectives and trainin...
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07/20/2016
Compositional Sequence Labeling Models for Error Detection in Learner Writing
In this paper, we present the first experiments using neural network mod...
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06/14/2016
