Search Results for author: Lin Gui

Found 35 papers, 18 papers with code

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

Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge

2 code implementations EMNLP 2021 Bin Liang, Hang Su, Rongdi Yin, Lin Gui, Min Yang, Qin Zhao, Xiaoqi Yu, Ruifeng Xu

To be specific, we first regard each aspect as a pivot to derive aspect-aware words that are highly related to the aspect from external affective commonsense knowledge.

graph construction Sentiment Analysis

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.

Association Sarcasm Detection

Heuristics for Vehicle Routing Problem: A Survey and Recent Advances

no code implementations1 Mar 2023 Fei Liu, Chengyu Lu, Lin Gui, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

Vehicle routing is a well-known optimization research topic with significant practical importance.

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

Concept Algebra for Text-Controlled Vision Models

1 code implementation7 Feb 2023 ZiHao Wang, Lin Gui, Jeffrey Negrea, Victor Veitch

In this paper, we introduce a formalization of "what the user intended" in terms of latent concepts implicit to the data generating process that the model was trained on.

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.


Integrated Communication and Positioning Design in RIS-empowered OFDM System: a Correlation Dispersion Scheme

no code implementations1 Dec 2022 Xichao Sang, Lin Gui, Kai Ying, Xiaohao Mo, Xiaqing Diao, Shiyong Sun

The channel frequency responses on pilots (CFROPs) of places of interest are used for online mapping with the offline CFROP database.

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

Causal Estimation for Text Data with (Apparent) Overlap Violations

no code implementations30 Sep 2022 Lin Gui, Victor Veitch

To estimate a causal effect from observational data, we need to adjust for confounding aspects of the text that affect both the treatment and outcome -- e. g., the topic or writing level of the text.

Causal Identification Representation Learning

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

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

A new neighborhood structure for job shop scheduling problems

no code implementations7 Sep 2021 Jin Xie, Xinyu Li, Liang Gao, Lin Gui

According to the above finding, this paper proposes a new N8 neighborhood structure considering the movement of critical operations within a critical block and the movement of critical operations outside the critical block.

Combinatorial Optimization Job Shop Scheduling +1

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-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

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.

Jointly Learning Aspect-Focused and Inter-Aspect Relations with Graph Convolutional Networks for Aspect Sentiment Analysis

1 code implementation COLING 2020 Bin Liang, Rongdi Yin, Lin Gui, Jiachen Du, Ruifeng Xu

Besides, to interactively extract the inter-aspect relations for the specific aspect, an inter-aspect GCN is adopted to model the representations learned by aspect-focused GCN based on the inter-aspect graph which is constructed by the relative dependencies between the aspect words and other aspects.

Sentiment Analysis

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

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

Panoptic Studio: A Massively Multiview System for Social Interaction Capture

1 code implementation9 Dec 2016 Hanbyul Joo, Tomas Simon, Xulong Li, Hao liu, Lei Tan, Lin Gui, Sean Banerjee, Timothy Godisart, Bart Nabbe, Iain Matthews, Takeo Kanade, Shohei Nobuhara, Yaser Sheikh

The core challenges in capturing social interactions are: (1) occlusion is functional and frequent; (2) subtle motion needs to be measured over a space large enough to host a social group; (3) human appearance and configuration variation is immense; and (4) attaching markers to the body may prime the nature of interactions.

Detecting Multiple Replicating Signals using Adaptive Filtering Procedures

1 code implementation11 Oct 2016 Jingshu Wang, Lin Gui, Weijie J. Su, Chiara Sabatti, Art B. Owen

Replicability is a fundamental quality of scientific discoveries: we are interested in those signals that are detectable in different laboratories, study populations, across time etc.


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