Papers with contrastive framework
BootTOD: Bootstrap Task-oriented Dialogue Representations by Aligning Diverse Responses (2024.lrec-main)
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| Challenge: | Existing pre-trained language models lack diversity and linguistic challenges in task-oriented dialogues. |
| Approach: | They propose a self-bootstrapping dialogue pre-training model called BootTOD . it learns task-oriented dialogue representations via a framework . |
| Outcome: | The proposed model outperforms strong TOD baselines on diverse dialogue tasks. |
A Simple Angle-based Approach for Contrastive Learning of Unsupervised Sentence Representation (2024.findings-emnlp)
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| Challenge: | a promising baseline SimCSE has made notable breakthroughs in unsupervised SRL . however, there is still room for designing a novel contrastive framework specifically targeted for SRL. |
| Approach: | They propose an angle-based similarity function for a contrastive objective and propose a new approach for SRL. |
| Outcome: | The proposed approach shows better training dynamics on SRL than the standard cosine similarity function. |
FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue (2023.acl-long)
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| Challenge: | Existing pre-trained language models rely on a contrastive framework and are difficult to use in practice. |
| Approach: | They propose a dialogue pre-training model which distills future knowledge to the representation of the previous dialogue context using a self-training framework. |
| Outcome: | The proposed model can be applied to various downstream dialogue tasks. |