Papers with IDRR task

2 papers
NCPrompt: NSP-Based Prompt Learning and Contrastive Learning for Implicit Discourse Relation Recognition (2024.findings-emnlp)

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Challenge: Recent prompt learning methods have demonstrated success in IDRR, but they fail to fully exploit critical semantic features shared among various forms of templates.
Approach: They propose an NSP-based prompt learning and contrastive learning method for IDRR that transforms the IDRR task into a next sentence prediction task.
Outcome: The proposed model can be used to classify the discourse relation sense between argument pairs without an explicit connective.
TEPrompt: Task Enlightenment Prompt Learning for Implicit Discourse Relation Recognition (2023.findings-acl)

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Challenge: Existing prompt learning models for IDRR use multiple-prompt decisions from three different yet much similar connective prediction templates.
Approach: They propose to fuse three related tasks to fuse the learned features of auxiliary tasks to create a prompt learning model that can be used to boost the main task.
Outcome: The proposed model outperforms the ConnPrompt in the training phase and in the testing phase.

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