Papers by Shilin Qu

2 papers
NormMark: A Weakly Supervised Markov Model for Socio-cultural Norm Discovery (2023.findings-acl)

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Challenge: Existing methods for norm recognition focus only on surface-level features of dialogues and do not take into account the interactions within a conversation.
Approach: They propose a probabilistic generative Markov model to carry latent features throughout a dialogue and trainable on weakly annotated data using the variational technique.
Outcome: The proposed model outperforms current state-of-the-art methods on a weakly annotated dataset, outperforming existing methods, including GPT3.
RENOVI: A Benchmark Towards Remediating Norm Violations in Socio-Cultural Conversations (2024.findings-naacl)

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Challenge: Norm violations occur when individuals fail to conform to culturally accepted behaviors, which may lead to potential conflicts.
Approach: They propose to use a large corpus of 9,258 multi-turn dialogues annotated with social norms to equip AI systems with a remediation ability.
Outcome: The proposed system can understand and remediate norm violations step by step.

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