Papers by Hengtong Lu

3 papers
Slot Transferability for Cross-domain Slot Filling (2021.findings-acl)

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Challenge: Existing work on slot filling uses labeled data from source domains to train a model for target domains.
Approach: They propose a model-agnostic Slot Transferability Measure (STM) to evaluate the transferability from a source slot to a target slot.
Outcome: The proposed method outperforms state-of-the-art models on multiple datasets and models.
Task-Oriented Clustering for Dialogues (2021.findings-emnlp)

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Challenge: Existing methods for task-oriented dialogue clustering are difficult to apply directly due to inherent differences between them.
Approach: They propose a Dialogue Task Clustering Network model for task-oriented clustering . they use context-aware utterance representations and cross-dialogue utterrance cluster representations .
Outcome: The proposed model outperforms baselines on three public datasets on all metrics.
Profanity-Avoiding Training Framework for Seq2seq Models with Certified Robustness (2021.emnlp-main)

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Challenge: a recent study shows that inappropriate language can cause models to output profanity . authors propose a training framework to prevent such outputs from hurting the usability of models .
Approach: proposed training framework eliminates the causes that trigger the generation of profanity . authors propose a framework that leverages a short list of profans to prevent this .
Outcome: a proposed training framework can prevent models from generating profanity . the proposed framework leverages a short list of profanities examples .

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