Papers by Shuyang Dai

2 papers
GrounDial: Human-norm Grounded Safe Dialog Response Generation (2024.findings-eacl)

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Challenge: Recent conversational AI systems generate unsafe responses agreeing to offensive user input or including toxic content.
Approach: They propose a method where response safety is achieved by grounding responses to commonsense social rules without fine-tuning.
Outcome: The proposed approach is quantitatively and qualitatively safer even without additional data or tuning.
APo-VAE: Text Generation in Hyperbolic Space (2021.naacl-main)

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Challenge: Existing models that learn embeddings only in Euclidean vector space do not account for such structural property of language.
Approach: They propose a Poincare Variational Autoencoder to capture latent hierarchies in hyperbolic space . they propose enabling adversarial learning procedures to empower robust model training .
Outcome: The proposed model outperforms existing models in a hyperbolic latent space . it captures latent language hierarchies in hyperbolical space and is robust to training .

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