Papers by Xiaoou Wang
Deploying Multi-task Online Server with Large Language Model (2025.coling-industry)
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| Challenge: | In the industry, numerous natural language processing tasks are deployed online . traditional approaches tackle each task separately by its own network and pipeline . |
| Approach: | They propose a three-stage multi-task learning framework for large language models . it involves task filtering, fine-tuning on high-resource tasks, and finally fine- tuning on all tasks . |
| Outcome: | The proposed framework reduces up to 90% of overhead while reducing latency and resource usage. |
FABRA: French Aggregator-Based Readability Assessment toolkit (2022.lrec-1)
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Rodrigo Wilkens, David Alfter, Xiaoou Wang, Alice Pintard, Anaïs Tack, Kevin P. Yancey, Thomas François
| Challenge: | a large number of readability predictor variables are used to predict reading difficulty of texts . the most important predictors for native texts are lexical diversity, dependency counts and text coherence . |
| Approach: | They propose a readability toolkit based on aggregation of readability predictor variables . they show which features are most predictive on two different corpora . |
| Outcome: | The proposed toolkit improves performance over standard feature-based readability prediction. |
Is Attention Explanation? An Introduction to the Debate (2022.acl-long)
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Adrien Bibal, Rémi Cardon, David Alfter, Rodrigo Wilkens, Xiaoou Wang, Thomas François, Patrick Watrin
| Challenge: | Attention has been used in various tasks of NLP and other fields of machine learning to increase performance and provide some explanations. |
| Approach: | They propose to use attention as an explanation for deep learning models to increase performance . they propose to apply attention weights to queries and queries based on scalar scores . |
| Outcome: | The proposed model can be used to increase performance while providing some explanations. |