Papers with contrastive learning module

2 papers
Contrastive Learning enhanced Author-Style Headline Generation (2022.emnlp-main)

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Challenge: Current work only uses the article itself in the headline generation, but have not taken the writing style of headlines into account.
Approach: They propose a model which takes historical headlines into account to integrate the stylistic features of the author into the model and integrate them into the decoder.
Outcome: The proposed model can integrate the stylistic features of the author into the model and generate a headline that is appropriate for the article and consistent with the author’s style.
Improving Radiology Summarization with Radiograph and Anatomy Prompts (2023.findings-acl)

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Challenge: Recent studies focus on automatic impression generation, but this task is time-consuming and in high demand.
Approach: They propose to use an anatomy-enhanced multimodal model to generate automatic impressions by combining radiology images with textual features.
Outcome: The proposed model achieves state-of-the-art on two benchmark datasets and compares with existing models.

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