Papers by Feifei Ma

3 papers
Domain-specific Attention with Distributional Signatures for Multi-Domain End-to-end Task-Oriented Dialogue (2023.findings-acl)

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Challenge: Existing methods to construct multi-domain task-oriented dialogue systems are difficult to extend to new domains due to high cost of data annotation and scarcity of labeled dialogue data.
Approach: They propose a domain attention module that uses distributional signatures to construct multi-domain dialogue systems with limited data.
Outcome: The proposed method outperforms baseline models on most metrics while keeping smaller model scale.
PAD: A Robustness Enhancement Ensemble Method via Promoting Attention Diversity (2024.lrec-main)

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Challenge: Existing approaches to enhance robustness of deep neural networks focus on perturbation . weak robustness is a problem for many types of adversarial attacks, authors say .
Approach: They propose a lightweight framework for enhancing robustness by perturbing parameters of a model and diversifying adversarial example distributions among different models.
Outcome: The proposed method can improve robustness against adversarial attacks while maintaining accuracy on clean data.
ConstraintLLM: A Neuro-Symbolic Framework for Industrial-Level Constraint Programming (2025.emnlp-main)

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Challenge: Constraint programming (CP) is a powerful paradigm for solving constraint optimization problems.
Approach: They propose to use an open-source LLM to generate formal modeling for COPs.
Outcome: The proposed model outperforms the baselines on the new IndusCP benchmark by 2x.

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