Papers by Zhongkai Sun
A New View of Multi-modal Language Analysis: Audio and Video Features as Text “Styles” (2021.eacl-main)
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| Challenge: | Fig. 1 shows how style-transferred multi-modal features can be used in sentiment analysis and emotion recognition. |
| Approach: | They propose to use adaptive normalization to impose style onto text to learn richer representations for multi-modal utterances. |
| Outcome: | The proposed model achieves performance on par with state-of-the-art but using less than a third of the model parameters. |
CL-QR: Cross-Lingual Enhanced Query Reformulation for Multi-lingual Conversational AI Agents (2023.emnlp-industry)
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| Challenge: | Existing QR systems that reformulate defective user queries are limited in English due to the scarcity of non-English QR labels. |
| Approach: | They propose a query reformulation method which reformulates defective user queries to improve non-English QR performance. |
| Outcome: | The proposed framework improves non-English QR performance by leveraging abundant reformulation resources in English. |
Improving Contextual Query Rewrite for Conversational AI Agents through User-preference Feedback Learning (2023.emnlp-industry)
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| Challenge: | Contextual query rewriting (CQR) is a crucial component in Conversational AI agents, leveraging contextual information from previous user-agent conversations to improve comprehension of current user intent. |
| Approach: | They propose a framework to enhance the CQR model's capability in generating user preference-aligned rewrites. |
| Outcome: | The proposed framework improves the CQR model's ability to generate user preference-aligned rewrites. |