Papers with lightweight techniques
A Cause-Effect Look at Alleviating Hallucination of Knowledge-grounded Dialogue Generation (2024.lrec-main)
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| Challenge: | Existing dialogue systems have demonstrated impressive performance conducting fluent and natural-sounding conversations, but they are plagued by the Knowledge Hallucination problem. |
| Approach: | They propose a method that exploits the dialogue-knowledge interaction to reduce hallucination by using external knowledge resources to generate more informative responses. |
| Outcome: | The proposed method reduces hallucination without disrupting other dialogue performance while keeping adaptive to different generation models. |
Modular Domain Adaptation (2022.findings-acl)
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| Challenge: | Existing models for sentiment analysis and hate speech detection are difficult to account for domain shift without access to source data. |
| Approach: | They propose to treat domain adaptation as a modular process that involves separate model producers and model consumers . they demonstrate that they can independently cooperate to facilitate more accurate measurements of text . |
| Outcome: | The proposed methods improve out-of-domain accuracy on four multi-domain text classification datasets. |