most citedCounterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome

2 citations · 4 across the 5 of their papers we have counts for

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5 papers

cs.MM20242 cited

Counterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome

Donghuo Zeng, Roberto S. Legaspi, Yuewen Sun +4

Customizing persuasive conversations related to the outcome of interest for specific users achieves better persuasion results. However, existing persuasive conversation systems rel…

cs.SD20241 cited

Anchor-aware Deep Metric Learning for Audio-visual Retrieval

Donghuo Zeng, Yanan Wang, Kazushi Ikeda +1

Metric learning minimizes the gap between similar (positive) pairs of data points and increases the separation of dissimilar (negative) pairs, aiming at capturing the underlying da…

cs.SD20231 cited

Two-Stage Triplet Loss Training with Curriculum Augmentation for Audio-Visual Retrieval

Donghuo Zeng, Kazushi Ikeda

The cross-modal retrieval model leverages the potential of triple loss optimization to learn robust embedding spaces. However, existing methods often train these models in a singul…

cs.MM2023

TV-watching partner robot: Analysis of User's Experience

Donghuo Zeng, Jianming Wu, Gen Hattori +1

Watching TV not only provides news information but also gives an opportunity for different generations to communicate. With the proliferation of smartphones, PC, and the Internet,…

cs.CL2023

Topic-switch adapted Japanese Dialogue System based on PLATO-2

Donghuo Zeng, Jianming Wu, Yanan Wang +3

Large-scale open-domain dialogue systems such as PLATO-2 have achieved state-of-the-art scores in both English and Chinese. However, little work explores whether such dialogue syst…