Search Results for author: Yulan He

Found 85 papers, 27 papers with code

Multi-Modal Sarcasm Detection via Cross-Modal Graph Convolutional Network

1 code implementation ACL 2022 Bin Liang, Chenwei Lou, Xiang Li, Min Yang, Lin Gui, Yulan He, Wenjie Pei, Ruifeng Xu

Then, the descriptions of the objects are served as a bridge to determine the importance of the association between the objects of image modality and the contextual words of text modality, so as to build a cross-modal graph for each multi-modal instance.

Sarcasm Detection

Implicit Sentiment Analysis with Event-centered Text Representation

no code implementations EMNLP 2021 Deyu Zhou, Jianan Wang, Linhai Zhang, Yulan He

Implicit sentiment analysis, aiming at detecting the sentiment of a sentence without sentiment words, has become an attractive research topic in recent years.

Representation Learning Sentiment Analysis

JointCL: A Joint Contrastive Learning Framework for Zero-Shot Stance Detection

1 code implementation ACL 2022 Bin Liang, Qinglin Zhu, Xiang Li, Min Yang, Lin Gui, Yulan He, Ruifeng Xu

In this paper, we propose a joint contrastive learning (JointCL) framework, which consists of stance contrastive learning and target-aware prototypical graph contrastive learning.

Contrastive Learning Stance Detection

Document-Level Multi-Event Extraction with Event Proxy Nodes and Hausdorff Distance Minimization

no code implementations30 May 2023 Xinyu Wang, Lin Gui, Yulan He

By directly minimizing Hausdorff distance, the model is trained towards the global optimum directly, which improves performance and reduces training time.

Event Extraction

OverPrompt: Enhancing ChatGPT Capabilities through an Efficient In-Context Learning Approach

no code implementations24 May 2023 Jiazheng Li, Runcong Zhao, Yulan He, Lin Gui

The exceptional performance of pre-trained large language models has revolutionised various applications, but their adoption in production environments is hindered by prohibitive costs and inefficiencies, particularly when utilising long prompts.

Data Augmentation Fact Checking +1

Distilling ChatGPT for Explainable Automated Student Answer Assessment

no code implementations22 May 2023 Jiazheng Li, Lin Gui, Yuxiang Zhou, David West, Cesare Aloisi, Yulan He

Traditional methods of automating student answer assessment through text classification often suffer from issues such as lack of trustworthiness, transparency, and the ability to provide a rationale for the automated assessment process.

Language Modelling text-classification +1

BERTTM: Leveraging Contextualized Word Embeddings from Pre-trained Language Models for Neural Topic Modeling

no code implementations16 May 2023 Zheng Fang, Yulan He, Rob Procter

Contextualized word embeddings from pre-trained language models show superiority in the ability of word sense disambiguation and prove to be effective in dealing with OOV words.

Document Classification Language Modelling +5

Explainable Recommender with Geometric Information Bottleneck

no code implementations9 May 2023 Hanqi Yan, Lin Gui, Menghan Wang, Kun Zhang, Yulan He

Explainable recommender systems can explain their recommendation decisions, enhancing user trust in the systems.

Explanation Generation Recommendation Systems

Cone: Unsupervised Contrastive Opinion Extraction

1 code implementation8 May 2023 Runcong Zhao, Lin Gui, Yulan He

Contrastive opinion extraction aims to extract a structured summary or key points organised as positive and negative viewpoints towards a common aspect or topic.

Contrastive Learning

Event Knowledge Incorporation with Posterior Regularization for Event-Centric Question Answering

1 code implementation8 May 2023 Junru Lu, Gabriele Pergola, Lin Gui, Yulan He

In particular, we define event-related knowledge constraints based on the event trigger annotations in the QA datasets, and subsequently use them to regularize the posterior answer output probabilities from the backbone pre-trained language models used in the QA setting.

Language Modelling Question Answering

NewsQuote: A Dataset Built on Quote Extraction and Attribution for Expert Recommendation in Fact-Checking

no code implementations5 May 2023 Wenjia Zhang, Lin Gui, Rob Procter, Yulan He

To enhance the ability to find credible evidence in news articles, we propose a novel task of expert recommendation, which aims to identify trustworthy experts on a specific news topic.

Fact Checking Question Answering +1

A User-Centered, Interactive, Human-in-the-Loop Topic Modelling System

no code implementations4 Apr 2023 Zheng Fang, Lama Alqazlan, Du Liu, Yulan He, Rob Procter

Human-in-the-loop topic modelling incorporates users' knowledge into the modelling process, enabling them to refine the model iteratively.

Topic Models

PANACEA: An Automated Misinformation Detection System on COVID-19

no code implementations28 Feb 2023 Runcong Zhao, Miguel Arana-Catania, Lixing Zhu, Elena Kochkina, Lin Gui, Arkaitz Zubiaga, Rob Procter, Maria Liakata, Yulan He

In this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection.

Fact Checking Misinformation +2

Distinguishability Calibration to In-Context Learning

1 code implementation13 Feb 2023 Hongjing Li, Hanqi Yan, Yanran Li, Li Qian, Yulan He, Lin Gui

When using prompt-based learning for text classification, the goal is to use a pre-trained language model (PLM) to predict a missing token in a pre-defined template given an input text, which can be mapped to a class label.

Language Modelling Metric Learning +2

NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization

1 code implementation11 Feb 2023 Junru Lu, Jiazheng Li, Byron C. Wallace, Yulan He, Gabriele Pergola

In this work, we propose a summarize-then-simplify two-stage strategy, which we call NapSS, identifying the relevant content to simplify while ensuring that the original narrative flow is preserved.

Semantic Similarity Semantic Textual Similarity +1

Event Temporal Relation Extraction with Bayesian Translational Model

no code implementations10 Feb 2023 Xingwei Tan, Gabriele Pergola, Yulan He

Existing models to extract temporal relations between events lack a principled method to incorporate external knowledge.

Bayesian Inference Temporal Relation Extraction

Tracking Brand-Associated Polarity-Bearing Topics in User Reviews

1 code implementation3 Jan 2023 Runcong Zhao, Lin Gui, Hanqi Yan, Yulan He

Monitoring online customer reviews is important for business organisations to measure customer satisfaction and better manage their reputations.


CAMANet: Class Activation Map Guided Attention Network for Radiology Report Generation

no code implementations2 Nov 2022 Jun Wang, Abhir Bhalerao, Terry Yin, Simon See, Yulan He

Radiology report generation (RRG) has gained increasing research attention because of its huge potential to mitigate medical resource shortages and aid the process of disease decision making by radiologists.

Decision Making

Event-Centric Question Answering via Contrastive Learning and Invertible Event Transformation

1 code implementation24 Oct 2022 Junru Lu, Xingwei Tan, Gabriele Pergola, Lin Gui, Yulan He

Our proposed model utilizes an invertible transformation matrix to project semantic vectors of events into a common event embedding space, trained with contrastive learning, and thus naturally inject event semantic knowledge into mainstream QA pipelines.

Contrastive Learning Question Answering +1

PHEE: A Dataset for Pharmacovigilance Event Extraction from Text

1 code implementation22 Oct 2022 Zhaoyue Sun, Jiazheng Li, Gabriele Pergola, Byron C. Wallace, Bino John, Nigel Greene, Joseph Kim, Yulan He

The primary goal of drug safety researchers and regulators is to promptly identify adverse drug reactions.

Event Extraction

Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling

no code implementations11 Oct 2022 Yuanhang Yang, shiyi qi, Cuiyun Gao, Zenglin Xu, Yulan He, Qifan Wang, Chuanyi Liu

Transformer-based models have achieved great success on sentence pair modeling tasks, such as answer selection and natural language inference (NLI).

Answer Selection Natural Language Inference +1

Addressing Token Uniformity in Transformers via Singular Value Transformation

1 code implementation24 Aug 2022 Hanqi Yan, Lin Gui, Wenjie Li, Yulan He

In this paper, we propose to use the distribution of singular values of outputs of each transformer layer to characterise the phenomenon of token uniformity and empirically illustrate that a less skewed singular value distribution can alleviate the `token uniformity' problem.

Semantic Textual Similarity

Cross-modal Prototype Driven Network for Radiology Report Generation

1 code implementation11 Jul 2022 Jun Wang, Abhir Bhalerao, Yulan He

Radiology report generation (RRG) aims to describe automatically a radiology image with human-like language and could potentially support the work of radiologists, reducing the burden of manual reporting.

RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generators

no code implementations NAACL 2022 Rilwan A. Adewoyin, Ritabrata Dutta, Yulan He

In this paper, we study the task of improving the cohesion and coherence of long-form text generated by language models.

Story Generation

Disentangled Learning of Stance and Aspect Topics for Vaccine Attitude Detection in Social Media

1 code implementation NAACL 2022 Lixing Zhu, Zheng Fang, Gabriele Pergola, Rob Procter, Yulan He

Building models to detect vaccine attitudes on social media is challenging because of the composite, often intricate aspects involved, and the limited availability of annotated data.

Aspect-Based Sentiment Analysis (ABSA) Stance Detection

Hierarchical Interpretation of Neural Text Classification

1 code implementation20 Feb 2022 Hanqi Yan, Lin Gui, Yulan He

Neural models developed in NLP however often compose word semantics in a hierarchical manner and text classification requires hierarchical modelling to aggregate local information in order to deal with topic and label shifts more effectively.

text-classification Text Classification

Evaluating the application of NLP tools in mainstream participatory budgeting processes in Scotland

no code implementations23 Nov 2021 Jonathan Davies, Miguel Arana-Catania, Rob Procter, Felix-Anselm van Lier, Yulan He

In recent years participatory budgeting (PB) in Scotland has grown from a handful of community-led processes to a movement supported by local and national government.

A mixed-methods ethnographic approach to participatory budgeting in Scotland

no code implementations20 Sep 2021 Jonathan Davies, M. Arana-Catania, Rob Procter, F. A. Van Lier, Yulan He

Participatory budgeting (PB) is already well established in Scotland in the form of community led grant-making yet has recently transformed from a grass-roots activity to a mainstream process or embedded 'policy instrument'.

Extracting Event Temporal Relations via Hyperbolic Geometry

1 code implementation EMNLP 2021 Xingwei Tan, Gabriele Pergola, Yulan He

Recent neural approaches to event temporal relation extraction typically map events to embeddings in the Euclidean space and train a classifier to detect temporal relations between event pairs.

Natural Language Understanding Temporal Relation Extraction

Supervised Contrastive Learning for Multimodal Unreliable News Detection in COVID-19 Pandemic

1 code implementation4 Sep 2021 Wenjia Zhang, Lin Gui, Yulan He

Rather, previously published news articles on the similar event could be used to assess the credibility of a news report.

Contrastive Learning

Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction

1 code implementation ACL 2021 Hanqi Yan, Lin Gui, Gabriele Pergola, Yulan He

To investigate the degree of reliance of existing ECE models on clause relative positions, we propose a novel strategy to generate adversarial examples in which the relative position information is no longer the indicative feature of cause clauses.

Emotion Cause Extraction

Topic-Aware Evidence Reasoning and Stance-Aware Aggregation for Fact Verification

1 code implementation ACL 2021 Jiasheng Si, Deyu Zhou, Tongzhe Li, Xingyu Shi, Yulan He

To alleviate the above issues, we propose a novel topic-aware evidence reasoning and stance-aware aggregation model for more accurate fact verification, with the following four key properties: 1) checking topical consistency between the claim and evidence; 2) maintaining topical coherence among multiple pieces of evidence; 3) ensuring semantic similarity between the global topic information and the semantic representation of evidence; 4) aggregating evidence based on their implicit stances to the claim.

Fact Verification Semantic Similarity +1

Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection

1 code implementation ACL 2021 Lixing Zhu, Gabriele Pergola, Lin Gui, Deyu Zhou, Yulan He

Emotion detection in dialogues is challenging as it often requires the identification of thematic topics underlying a conversation, the relevant commonsense knowledge, and the intricate transition patterns between the affective states.

Emotion Recognition in Conversation

A Query-Driven Topic Model

no code implementations Findings (ACL) 2021 Zheng Fang, Yulan He, Rob Procter

Topic modeling is an unsupervised method for revealing the hidden semantic structure of a corpus.

Topic Models

Code Structure Guided Transformer for Source Code Summarization

no code implementations19 Apr 2021 Shuzheng Gao, Cuiyun Gao, Yulan He, Jichuan Zeng, Lun Yiu Nie, Xin Xia, Michael R. Lyu

Code summaries help developers comprehend programs and reduce their time to infer the program functionalities during software maintenance.

Code Summarization Inductive Bias +1

Citizen Participation and Machine Learning for a Better Democracy

no code implementations28 Feb 2021 M. Arana-Catania, F. A. Van Lier, Rob Procter, Nataliya Tkachenko, Yulan He, Arkaitz Zubiaga, Maria Liakata

The development of democratic systems is a crucial task as confirmed by its selection as one of the Millennium Sustainable Development Goals by the United Nations.

BIG-bench Machine Learning Decision Making

Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies

no code implementations EACL 2021 Gabriele Pergola, Elena Kochkina, Lin Gui, Maria Liakata, Yulan He

Biomedical question-answering (QA) has gained increased attention for its capability to provide users with high-quality information from a vast scientific literature.

Domain Adaptation Question Answering +1

Adversarial Learning of Poisson Factorisation Model for Gauging Brand Sentiment in User Reviews

no code implementations EACL 2021 Runcong Zhao, Lin Gui, Gabriele Pergola, Yulan He

In this paper, we propose the Brand-Topic Model (BTM) which aims to detect brand-associated polarity-bearing topics from product reviews.

A Disentangled Adversarial Neural Topic Model for Separating Opinions from Plots in User Reviews

1 code implementation NAACL 2021 Gabriele Pergola, Lin Gui, Yulan He

The flexibility of the inference process in Variational Autoencoders (VAEs) has recently led to revising traditional probabilistic topic models giving rise to Neural Topic Models (NTMs).

Disentanglement Sentiment Analysis +2

TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall

1 code implementation20 Aug 2020 Rilwan Adewoyin, Peter Dueben, Peter Watson, Yulan He, Ritabrata Dutta

Experiments show that our model consistently attains lower RMSE and MAE scores than a DL model prevalent in short term precipitation prediction and improves upon the rainfall predictions of a state-of-the-art dynamical weather model.

A Neural Generative Model for Joint Learning Topics and Topic-Specific Word Embeddings

1 code implementation11 Aug 2020 Lixing Zhu, Yulan He, Deyu Zhou

We propose a novel generative model to explore both local and global context for joint learning topics and topic-specific word embeddings.

Sentiment Analysis Sentiment Classification +4

Neural Temporal Opinion Modelling for Opinion Prediction on Twitter

no code implementations ACL 2020 Lixing Zhu, Yulan He, Deyu Zhou

Opinion prediction on Twitter is challenging due to the transient nature of tweet content and neighbourhood context.

Neural Topic Modeling with Bidirectional Adversarial Training

1 code implementation ACL 2020 Rui Wang, Xuemeng Hu, Deyu Zhou, Yulan He, Yuxuan Xiong, Chenchen Ye, Haiyang Xu

Recent years have witnessed a surge of interests of using neural topic models for automatic topic extraction from text, since they avoid the complicated mathematical derivations for model inference as in traditional topic models such as Latent Dirichlet Allocation (LDA).

Text Clustering Topic Models

What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process

no code implementations10 Feb 2020 Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, Irwin King

In our world with full of uncertainty, debates and argumentation contribute to the progress of science and society.

Topical Phrase Extraction from Clinical Reports by Incorporating both Local and Global Context

no code implementations22 Nov 2019 Gabriele Pergola, Yulan He, David Lowe

Making sense of words often requires to simultaneously examine the surrounding context of a term as well as the global themes characterizing the overall corpus.

Topic Models Word Embeddings

Interpretable Relevant Emotion Ranking with Event-Driven Attention

no code implementations IJCNLP 2019 Yang Yang, Deyu Zhou, Yulan He, Meng Zhang

Unveiling the hidden event information can help to understand how the emotions are evoked and provide explainable results.

Variational Conditional GAN for Fine-grained Controllable Image Generation

no code implementations22 Sep 2019 Mingqi Hu, Deyu Zhou, Yulan He

In this paper, we propose a novel variational generator framework for conditional GANs to catch semantic details for improving the generation quality and diversity.

Image Generation Variational Inference

Open Event Extraction from Online Text using a Generative Adversarial Network

no code implementations IJCNLP 2019 Rui Wang, Deyu Zhou, Yulan He

Experimental results show that our model outperforms the baseline approaches on all the datasets, with more significant improvements observed on the news article dataset where an increase of 15\% is observed in F-measure.

Event Extraction

TDAM: a Topic-Dependent Attention Model for Sentiment Analysis

no code implementations18 Aug 2019 Gabriele Pergola, Lin Gui, Yulan He

We propose a topic-dependent attention model for sentiment classification and topic extraction.

Classification General Classification +3

ATM:Adversarial-neural Topic Model

no code implementations1 Nov 2018 Rui Wang, Deyu Zhou, Yulan He

The proposed ATM models topics with Dirichlet prior and employs a generator network to capture the semantic patterns among latent topics.

Event Extraction Topic Models

Variational Autoregressive Decoder for Neural Response Generation

no code implementations EMNLP 2018 Jiachen Du, Wenjie Li, Yulan He, Ruifeng Xu, Lidong Bing, Xuan Wang

Combining the virtues of probability graphic models and neural networks, Conditional Variational Auto-encoder (CVAE) has shown promising performance in applications such as response generation.

Response Generation

Relevant Emotion Ranking from Text Constrained with Emotion Relationships

no code implementations NAACL 2018 Deyu Zhou, Yang Yang, Yulan He

As such, emotion detection, to predict multiple emotions associated with a given text, can be cast into a multi-label classification problem.

Multi-Label Classification Multi-Label Learning +1

Neural Storyline Extraction Model for Storyline Generation from News Articles

no code implementations NAACL 2018 Deyu Zhou, Linsen Guo, Yulan He

To tackle this problem, approaches based on probabilistic graphic models jointly model the generations of events and storylines without the use of annotated data.

Topic Models

Detecting Perspectives in Political Debates

1 code implementation EMNLP 2017 David Vilares, Yulan He

We explore how to detect people{'}s perspectives that occupy a certain proposition.

Topic Models

Event extraction from Twitter using Non-Parametric Bayesian Mixture Model with Word Embeddings

no code implementations EACL 2017 Deyu Zhou, Xuan Zhang, Yulan He

To extract structured representations of newsworthy events from Twitter, unsupervised models typically assume that tweets involving the same named entities and expressed using similar words are likely to belong to the same event.

Event Extraction Word Embeddings

Detecting Expressions of Blame or Praise in Text

no code implementations LREC 2016 Udochukwu Orizu, Yulan He

One of the key aspects of social computing is the ability to attribute responsibility such as blame or praise to social events.

On Stopwords, Filtering and Data Sparsity for Sentiment Analysis of Twitter

no code implementations LREC 2014 Hassan Saif, Fern, Miriam ez, Yulan He, Harith Alani

In this paper we investigate whether removing stopwords helps or hampers the effectiveness of Twitter sentiment classification methods.

Document Classification General Classification +2

Quantising Opinions for Political Tweets Analysis

no code implementations LREC 2012 Yulan He, Hassan Saif, Zhongyu Wei, Kam-Fai Wong

There have been increasing interests in recent years in analyzing tweet messages relevant to political events so as to understand public opinions towards certain political issues.

Sentiment Analysis

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