Search Results for author: Stephen Wan

Found 21 papers, 6 papers with code

Demonstrating the Reliability of Self-Annotated Emotion Data

no code implementations NAACL (CLPsych) 2021 Anton Malko, Cecile Paris, Andreas Duenser, Maria Kangas, Diego Molla, Ross Sparks, Stephen Wan

Vent is a specialised iOS/Android social media platform with the stated goal to encourage people to post about their feelings and explicitly label them.

Investigating Metric Diversity for Evaluating Long Document Summarisation

1 code implementation sdp (COLING) 2022 Cai Yang, Stephen Wan

Long document summarisation, a challenging summarisation scenario, is the focus of the recently proposed LongSumm shared task.

Text Generation

Mention Flags (MF): Constraining Transformer-based Text Generators

1 code implementation ACL 2021 YuFei Wang, Ian Wood, Stephen Wan, Mark Dras, Mark Johnson

In this paper, we propose Mention Flags (MF), which traces whether lexical constraints are satisfied in the generated outputs in an S2S decoder.

Common Sense Reasoning Text Generation

Neural Rule-Execution Tracking Machine For Transformer-Based Text Generation

no code implementations NeurIPS 2021 YuFei Wang, Can Xu, Huang Hu, Chongyang Tao, Stephen Wan, Mark Dras, Mark Johnson, Daxin Jiang

Sequence-to-Sequence (S2S) neural text generation models, especially the pre-trained ones (e. g., BART and T5), have exhibited compelling performance on various natural language generation tasks.

Text Generation

Integrating Lexical Information into Entity Neighbourhood Representations for Relation Prediction

1 code implementation NAACL 2021 Ian Wood, Mark Johnson, Stephen Wan

OpenKi[1] addresses this task through extraction of named entities and predicates via OpenIE tools then learning relation embeddings from the resulting entity-relation graph for relation prediction, outperforming previous approaches.

Knowledge Graph Completion Relation Extraction

ECOL-R: Encouraging Copying in Novel Object Captioning with Reinforcement Learning

no code implementations EACL 2021 YuFei Wang, Ian D. Wood, Stephen Wan, Mark Johnson

In this paper, we focus on this challenge and propose the ECOL-R model (Encouraging Copying of Object Labels with Reinforced Learning), a copy-augmented transformer model that is encouraged to accurately describe the novel object labels.

Image Captioning reinforcement-learning +1

Towards Generating Stylized Image Captions via Adversarial Training

no code implementations8 Aug 2019 Omid Mohamad Nezami, Mark Dras, Stephen Wan, Cecile Paris, Len Hamey

While most image captioning aims to generate objective descriptions of images, the last few years have seen work on generating visually grounded image captions which have a specific style (e. g., incorporating positive or negative sentiment).

Image Captioning

Image Captioning using Facial Expression and Attention

no code implementations8 Aug 2019 Omid Mohamad Nezami, Mark Dras, Stephen Wan, Cecile Paris

An analysis of the generated captions finds that, perhaps unexpectedly, the improvement in caption quality appears to come not from the addition of adjectives linked to emotional aspects of the images, but from more variety in the actions described in the captions.

Image Captioning

How to best use Syntax in Semantic Role Labelling

1 code implementation ACL 2019 Yufei Wang, Mark Johnson, Stephen Wan, Yifang Sun, Wei Wang

There are many different ways in which external information might be used in an NLP task.

Semantic Role Labeling

Red-faced ROUGE: Examining the Suitability of ROUGE for Opinion Summary Evaluation

no code implementations ALTA 2019 Wenyi Tay, Aditya Joshi, Xiuzhen Zhang, Sarvnaz Karimi, Stephen Wan

Opinion summarisation requires to correctly pair two types of semantic information: (1) aspect or opinion target; and (2) polarity of candidate and reference summaries.

Senti-Attend: Image Captioning using Sentiment and Attention

no code implementations24 Nov 2018 Omid Mohamad Nezami, Mark Dras, Stephen Wan, Cecile Paris

However, such models typically have difficulty in balancing the semantic aspects of the image and the non-factual dimensions of the caption; in addition, it can be observed that humans may focus on different aspects of an image depending on the chosen sentiment or style of the caption.

Image Captioning

Automatic Recognition of Student Engagement using Deep Learning and Facial Expression

3 code implementations7 Aug 2018 Omid Mohamad Nezami, Mark Dras, Len Hamey, Deborah Richards, Stephen Wan, Cecile Paris

This paper presents a deep learning model to improve engagement recognition from images that overcomes the data sparsity challenge by pre-training on readily available basic facial expression data, before training on specialised engagement data.

Facial Expression Recognition Facial Expression Recognition (FER)

Demographic Inference on Twitter using Recursive Neural Networks

no code implementations ACL 2017 Sunghwan Mac Kim, Qiongkai Xu, Lizhen Qu, Stephen Wan, C{\'e}cile Paris

In social media, demographic inference is a critical task in order to gain a better understanding of a cohort and to facilitate interacting with one{'}s audience.

Network Embedding

CSIRO Data61 at the WNUT Geo Shared Task

no code implementations WS 2016 Gaya Jayasinghe, Brian Jin, James Mchugh, Bella Robinson, Stephen Wan

In this paper, we describe CSIRO Data61{'}s participation in the Geolocation shared task at the Workshop for Noisy User-generated Text.

Information Retrieval Retrieval

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