Timothy Baldwin

is this you? claim profile

∙ 0 followers
The University of Melbourne

Professor, School of Computing and Information Systems at The University of Melbourne

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

We present COVID-SEE, a system for medical literature discovery based on...
08/18/2020 ∙ by Karin Verspoor, et al. ∙ 0 ∙ share

read it
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...
05/27/2020 ∙ by Kobi Leins, et al. ∙ 0 ∙ share

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

We present our work on aligning the Unified Medical Language System (UML...
05/04/2020 ∙ by Afshin Rahimi, et al. ∙ 0 ∙ share

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

The world is facing the challenge of climate crisis. Despite the consens...
04/30/2020 ∙ by Shraey Bhatia, et al. ∙ 0 ∙ share

read it
SemEval-2017 Task 3: Community Question Answering

We describe SemEval-2017 Task 3 on Community Question Answering. This ye...
12/02/2019 ∙ by Preslav Nakov, et al. ∙ 11 ∙ share

read it
Improved Document Modelling with a Neural Discourse Parser

Despite the success of attention-based neural models for natural languag...
11/16/2019 ∙ by Fajri Koto, et al. ∙ 0 ∙ share

read it
Deep Ordinal Regression for Pledge Specificity Prediction

Many pledges are made in the course of an election campaign, forming imp...
08/31/2019 ∙ by Shivashankar Subramanian, et al. ∙ 0 ∙ share

read it
Evaluating the Utility of Document Embedding Vector Difference for Relation Learning

Recent work has demonstrated that vector offsets obtained by subtracting...
07/18/2019 ∙ by Jingyuan Zhang, et al. ∙ 0 ∙ share

read it
Semi-supervised Stochastic Multi-Domain Learning using Variational Inference

Supervised models of NLP rely on large collections of text which closely...
06/07/2019 ∙ by Yitong Li, et al. ∙ 0 ∙ share

read it
Target Based Speech Act Classification in Political Campaign Text

We study pragmatics in political campaign text, through analysis of spee...
05/20/2019 ∙ by Shivashankar Subramanian, et al. ∙ 0 ∙ share

read it
Contextualization of Morphological Inflection

Critical to natural language generation is the production of correctly i...
05/04/2019 ∙ by Ekaterina Vylomova, et al. ∙ 0 ∙ share

read it
A Joint Model for Multimodal Document Quality Assessment

The quality of a document is affected by various factors, including gram...
01/04/2019 ∙ by Aili Shen, et al. ∙ 26 ∙ share

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

In this paper, we propose a joint architecture that captures language, r...
07/10/2018 ∙ by Jey Han Lau, et al. ∙ 0 ∙ share

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

Online petitions are a cost-effective way for citizens to collectively e...
05/17/2018 ∙ by Shivashankar Subramanian, et al. ∙ 0 ∙ share

read it
Narrative Modeling with Memory Chains and Semantic Supervision

Story comprehension requires a deep semantic understanding of the narrat...
05/16/2018 ∙ by Fei Liu, et al. ∙ 0 ∙ share

read it
Towards Robust and Privacy-preserving Text Representations

Written text often provides sufficient clues to identify the author, the...
05/16/2018 ∙ by Yitong Li, et al. ∙ 0 ∙ share

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

Most real world language problems require learning from heterogenous cor...
05/16/2018 ∙ by Yitong Li, et al. ∙ 0 ∙ share

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

Election manifestos document the intentions, motives, and views of polit...
05/08/2018 ∙ by Shivashankar Subramanian, et al. ∙ 0 ∙ share

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

While neural networks have been shown to achieve impressive results for ...
04/30/2018 ∙ by Fei Liu, et al. ∙ 0 ∙ share

read it
Automatic Language Identification in Texts: A Survey

Language identification (LI) is the problem of determining the natural l...
04/22/2018 ∙ by Tommi Jauhiainen, et al. ∙ 0 ∙ share

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

Despite successful applications across a broad range of NLP tasks, condi...
09/12/2017 ∙ by Fei Liu, et al. ∙ 0 ∙ share

read it
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...
08/14/2017 ∙ by Afshin Rahimi, et al. ∙ 0 ∙ share

read it
An Automatic Approach for Document-level Topic Model Evaluation

Topic models jointly learn topics and document-level topic distribution....
06/16/2017 ∙ by Shraey Bhatia, et al. ∙ 0 ∙ share

read it
Topically Driven Neural Language Model

Language models are typically applied at the sentence level, without acc...
04/26/2017 ∙ by Jey Han Lau, et al. ∙ 0 ∙ share

read it
A Neural Model for User Geolocation and Lexical Dialectology

We propose a simple yet effective text- based user geolocation model bas...
04/13/2017 ∙ by Afshin Rahimi, et al. ∙ 0 ∙ share

read it
Context-Aware Prediction of Derivational Word-forms

Derivational morphology is a fundamental and complex characteristic of l...
02/22/2017 ∙ by Ekaterina Vylomova, et al. ∙ 0 ∙ share

read it
Automatic Labelling of Topics with Neural Embeddings

Topics generated by topic models are typically represented as list of te...
12/16/2016 ∙ by Shraey Bhatia, et al. ∙ 0 ∙ share

read it
Named Entity Recognition for Novel Types by Transfer Learning

In named entity recognition, we often don't have a large in-domain train...
10/31/2016 ∙ by Lizhen Qu, et al. ∙ 0 ∙ share

read it
An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation

Recently, Le and Mikolov (2014) proposed doc2vec as an extension to word...
07/19/2016 ∙ by Jey Han Lau, et al. ∙ 0 ∙ share

read it
From Incremental Meaning to Semantic Unit (phrase by phrase)

This paper describes an experimental approach to Detection of Minimal Se...
04/17/2016 ∙ by Andreas Scherbakov, et al. ∙ 0 ∙ share

read it
Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility of Vector Differences for Lexical Relation Learning

Recent work on word embeddings has shown that simple vector subtraction ...
09/05/2015 ∙ by Ekaterina Vylomova, et al. ∙ 0 ∙ share

read it
Twitter User Geolocation Using a Unified Text and Network Prediction Model

We propose a label propagation approach to geolocation prediction based ...
06/27/2015 ∙ by Afshin Rahimi, et al. ∙ 0 ∙ share

read it
Big Data Small Data, In Domain Out-of Domain, Known Word Unknown Word: The Impact of Word Representation on Sequence Labelling Tasks

Word embeddings -- distributed word representations that can be learned ...
04/21/2015 ∙ by Lizhen Qu, et al. ∙ 0 ∙ share

read it

Timothy Baldwin

Featured Co-authors