Papers with 2-step approach

3 papers
E2E Spoken Entity Extraction for Virtual Agents (2023.emnlp-industry)

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Challenge: Extensive research has been done to recognize entities in spoken input.
Approach: They propose to fine-tune pre-trained speech encoders to extract spoken entities directly from speech without the need for text transcription.
Outcome: The proposed approach outperforms the 2-step approach for extracting spoken entities from human-computer conversations.
Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Texts (P19-1)

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Challenge: Emotion cause extraction (ECE) aims at extracting potential causes behind certain emotions in text.
Approach: They propose a 2-step task to extract potential pairs of emotions and corresponding causes in a document.
Outcome: The proposed task is based on a benchmark emotion cause corpus.
Reflective Decoding: Beyond Unidirectional Generation with Off-the-Shelf Language Models (2021.acl-long)

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Challenge: Existing methods for generating text are unsupervised and require supervision.
Approach: They propose an unsupervised method that uses two off-the-shelf pretrained LMs in opposite directions to apply them to non-sequential tasks.
Outcome: The proposed method outperforms strong unsupervised baselines on paraphrasing and abductive text infilling.

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