Timothy Baldwin

research

∙ 05/09/2022

Improving negation detection with negation-focused pre-training

Negation is a common linguistic feature that is crucial in many language...

Thinh Hung Truong, et al. ∙

research

∙ 05/05/2022

Optimising Equal Opportunity Fairness in Model Training

Real-world datasets often encode stereotypes and societal biases. Such b...

Aili Shen, et al. ∙

research

∙ 05/04/2022

fairlib: A Unified Framework for Assessing and Improving Classification Fairness

This paper presents fairlib, an open-source framework for assessing and ...

Xudong Han, et al. ∙

research

∙ 03/24/2022

One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia

NLP research is impeded by a lack of resources and awareness of the chal...

Alham Fikri Aji, et al. ∙

research

∙ 03/12/2022

Towards Equal Opportunity Fairness through Adversarial Learning

Adversarial training is a common approach for bias mitigation in natural...

Xudong Han, et al. ∙

research

∙ 02/16/2022

ITTC @ TREC 2021 Clinical Trials Track

This paper describes the submissions of the Natural Language Processing ...

Thinh Hung Truong, et al. ∙

research

∙ 09/22/2021

Contrastive Learning for Fair Representations

Trained classification models can unintentionally lead to biased represe...

Aili Shen, et al. ∙

research

∙ 09/21/2021

Fairness-aware Class Imbalanced Learning

Class imbalance is a common challenge in many NLP tasks, and has clear c...

Shivashankar Subramanian, et al. ∙

research

∙ 09/21/2021

Evaluating Debiasing Techniques for Intersectional Biases

Bias is pervasive in NLP models, motivating the development of automatic...

Shivashankar Subramanian, et al. ∙

research

∙ 09/16/2021

Balancing out Bias: Achieving Fairness Through Training Reweighting

Bias in natural language processing arises primarily from models learnin...

Xudong Han, et al. ∙

research

∙ 09/14/2021

KFCNet: Knowledge Filtering and Contrastive Learning Network for Generative Commonsense Reasoning

Pre-trained language models have led to substantial gains over a broad r...

Haonan Li, et al. ∙

research

∙ 09/10/2021

IndoBERTweet: A Pretrained Language Model for Indonesian Twitter with Effective Domain-Specific Vocabulary Initialization

We present IndoBERTweet, the first large-scale pretrained model for Indo...

Fajri Koto, et al. ∙

research

∙ 07/30/2021

Automatic Claim Review for Climate Science via Explanation Generation

There is unison is the scientific community about human induced climate ...

Shraey Bhatia, et al. ∙

research

∙ 06/02/2021

Evaluating the Efficacy of Summarization Evaluation across Languages

While automatic summarization evaluation methods developed for English a...

Fajri Koto, et al. ∙

research

∙ 05/25/2021

Impact of detecting clinical trial elements in exploration of COVID-19 literature

The COVID-19 pandemic has driven ever-greater demand for tools which ena...

Simon Šuster, et al. ∙

research

∙ 04/13/2021

Discourse Probing of Pretrained Language Models

Existing work on probing of pretrained language models (LMs) has predomi...

Fajri Koto, et al. ∙

research

∙ 03/18/2021

Evaluating Document Coherence Modelling

While pretrained language models ("LM") have driven impressive gains ove...

Aili Shen, et al. ∙

research

∙ 02/03/2021

Top-down Discourse Parsing via Sequence Labelling

We introduce a top-down approach to discourse parsing that is conceptual...

Fajri Koto, et al. ∙

research

∙ 01/25/2021

Diverse Adversaries for Mitigating Bias in Training

Adversarial learning can learn fairer and less biased models of language...

Xudong Han, et al. ∙

research

∙ 11/27/2020

FFCI: A Framework for Interpretable Automatic Evaluation of Summarization

In this paper, we propose FFCI, a framework for automatic summarization ...

Fajri Koto, et al. ∙

research

∙ 11/02/2020

Liputan6: A Large-scale Indonesian Dataset for Text Summarization

In this paper, we introduce a large-scale Indonesian summarization datas...

Fajri Koto, et al. ∙

research

∙ 11/02/2020

IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLP

Although the Indonesian language is spoken by almost 200 million people ...

Fajri Koto, et al. ∙

research

∙ 10/30/2020

Target Word Masking for Location Metonymy Resolution

Existing metonymy resolution approaches rely on features extracted from ...

Haonan Li, et al. ∙

research

∙ 10/27/2020

Learning Contextualised Cross-lingual Word Embeddings for Extremely Low-Resource Languages Using Parallel Corpora

We propose a new approach for learning contextualised cross-lingual word...

Takashi Wada, et al. ∙

research

∙ 08/18/2020

COVID-SEE: Scientific Evidence Explorer for COVID-19 Related Research

We present COVID-SEE, a system for medical literature discovery based on...

Karin Verspoor, et al. ∙

research

∙ 05/27/2020

Give Me Convenience and Give Her Death: Who Should Decide What Uses of NLP are Appropriate, and on What Basis?

As part of growing NLP capabilities, coupled with an awareness of the et...

Kobi Leins, et al. ∙

research

∙ 05/04/2020

WikiUMLS: Aligning UMLS to Wikipedia via Cross-lingual Neural Ranking

We present our work on aligning the Unified Medical Language System (UML...

Afshin Rahimi, et al. ∙

research

∙ 04/30/2020

You are right. I am ALARMED – But by Climate Change Counter Movement

The world is facing the challenge of climate crisis. Despite the consens...

Shraey Bhatia, et al. ∙

research

∙ 12/02/2019

SemEval-2017 Task 3: Community Question Answering

We describe SemEval-2017 Task 3 on Community Question Answering. This ye...

Preslav Nakov, et al. ∙

research

∙ 11/16/2019

Improved Document Modelling with a Neural Discourse Parser

Despite the success of attention-based neural models for natural languag...

Fajri Koto, et al. ∙

research

∙ 08/31/2019

Deep Ordinal Regression for Pledge Specificity Prediction

Many pledges are made in the course of an election campaign, forming imp...

Shivashankar Subramanian, et al. ∙

research

∙ 07/18/2019

Evaluating the Utility of Document Embedding Vector Difference for Relation Learning

Recent work has demonstrated that vector offsets obtained by subtracting...

Jingyuan Zhang, et al. ∙

research

∙ 06/07/2019

Semi-supervised Stochastic Multi-Domain Learning using Variational Inference

Supervised models of NLP rely on large collections of text which closely...

Yitong Li, et al. ∙

research

∙ 05/20/2019

Target Based Speech Act Classification in Political Campaign Text

We study pragmatics in political campaign text, through analysis of spee...

Shivashankar Subramanian, et al. ∙

research

∙ 05/04/2019

Contextualization of Morphological Inflection

Critical to natural language generation is the production of correctly i...

Ekaterina Vylomova, et al. ∙

research

∙ 01/04/2019

A Joint Model for Multimodal Document Quality Assessment

The quality of a document is affected by various factors, including gram...

Aili Shen, et al. ∙

research

∙ 07/10/2018

Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhyme

In this paper, we propose a joint architecture that captures language, r...

Jey Han Lau, et al. ∙

research

∙ 05/17/2018

Content-based Popularity Prediction of Online Petitions Using a Deep Regression Model

Online petitions are a cost-effective way for citizens to collectively e...

Shivashankar Subramanian, et al. ∙

research

∙ 05/16/2018

Narrative Modeling with Memory Chains and Semantic Supervision

Story comprehension requires a deep semantic understanding of the narrat...

Fei Liu, et al. ∙

research

∙ 05/16/2018

Towards Robust and Privacy-preserving Text Representations

Written text often provides sufficient clues to identify the author, the...

Yitong Li, et al. ∙

research

∙ 05/16/2018

What's in a Domain? Learning Domain-Robust Text Representations using Adversarial Training

Most real world language problems require learning from heterogenous cor...

Yitong Li, et al. ∙

research

∙ 05/08/2018

Hierarchical Structured Model for Fine-to-coarse Manifesto Text Analysis

Election manifestos document the intentions, motives, and views of polit...

Shivashankar Subramanian, et al. ∙

research

∙ 04/30/2018

Recurrent Entity Networks with Delayed Memory Update for Targeted Aspect-based Sentiment Analysis

While neural networks have been shown to achieve impressive results for ...

Fei Liu, et al. ∙

research

∙ 04/22/2018

Automatic Language Identification in Texts: A Survey

Language identification (LI) is the problem of determining the natural l...

Tommi Jauhiainen, et al. ∙

research

∙ 09/12/2017

Capturing Long-range Contextual Dependencies with Memory-enhanced Conditional Random Fields

Despite successful applications across a broad range of NLP tasks, condi...

Fei Liu, et al. ∙

research

∙ 08/14/2017

Continuous Representation of Location for Geolocation and Lexical Dialectology using Mixture Density Networks

We propose a method for embedding two-dimensional locations in a continu...

Afshin Rahimi, et al. ∙

research

∙ 06/16/2017

An Automatic Approach for Document-level Topic Model Evaluation

Topic models jointly learn topics and document-level topic distribution....

Shraey Bhatia, et al. ∙

research

∙ 04/26/2017

Topically Driven Neural Language Model

Language models are typically applied at the sentence level, without acc...

Jey Han Lau, et al. ∙

research

∙ 04/13/2017

A Neural Model for User Geolocation and Lexical Dialectology

We propose a simple yet effective text- based user geolocation model bas...

Afshin Rahimi, et al. ∙

research

∙ 02/22/2017

Context-Aware Prediction of Derivational Word-forms

Derivational morphology is a fundamental and complex characteristic of l...

Ekaterina Vylomova, et al. ∙

Timothy Baldwin

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