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20172021
most citedSupervised Contrastive Learning for Multimodal Unreliable News Detection in COVID-19 Pandemic

43 citations · 69 across the 7 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.CL202143 cited

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

Wenjia Zhang, Lin Gui, Yulan He

As the digital news industry becomes the main channel of information dissemination, the adverse impact of fake news is explosively magnified. The credibility of a news report shoul…

cs.AI20211 cited

A new neighborhood structure for job shop scheduling problems

Jin Xie, Xinyu Li, Liang Gao +1

Job shop scheduling problem (JSP) is a widely studied NP-complete combinatorial optimization problem. Neighborhood structures play a critical role in solving JSP. At present, there…

cs.CL202111 cited

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

Lixing Zhu, Gabriele Pergola, Lin Gui +2

Emotion detection in dialogues is challenging as it often requires the identification of thematic topics underlying a conversation, the relevant commonsense knowledge, and the intr…

cs.CL20211 cited

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

Gabriele Pergola, Elena Kochkina, Lin Gui +2

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

cs.LG2021

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

Runcong Zhao, Lin Gui, Gabriele Pergola +1

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