Papers by Fajie Yuan
Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking (2021.acl-short)
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| Challenge: | Existing methods to learn consecutive tasks without forgetting how to perform previously trained problems are lacking. |
| Approach: | They propose a continual learning method which preserves performance on previously encountered tasks while accelerating learning progress on subsequent tasks. |
| Outcome: | The proposed method preserves performance on previously encountered tasks while accelerating learning progress on subsequent tasks. |
Batch IS NOT Heavy: Learning Word Representations From All Samples (P18-1)
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| Challenge: | Stochastic Gradient Descent with negative sampling is the most prevalent approach to learn word representations. |
| Approach: | They propose a method that uses batch gradient learning to generate word representations from all training samples. |
| Outcome: | The proposed method outperforms sampling-based methods on several benchmark tasks. |
U-Fold: Dynamic Intent-Aware Context Folding for User-Centric Agents (2026.findings-acl)
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| Challenge: | Existing context-folding methods are designed for single-query or single-intent scenarios. |
| Approach: | They propose a dynamic context-folding framework tailored to user-centric tasks that preserves fine-grained information through dynamic context folding. |
| Outcome: | The proposed framework outperforms ReAct and previous folding frameworks on long, noisy tasks. |