no code implementations • 16 Feb 2024 • Lingzi Zhang, Xin Zhou, Zhiwei Zeng, Zhiqi Shen
Recent sequential recommendation models have combined pre-trained text embeddings of items with item ID embeddings to achieve superior recommendation performance.
no code implementations • 18 Jan 2024 • He Zhao, Zhiwei Zeng, Yongwei Wang, Deheng Ye, Chunyan Miao
Heterogeneous Graph Neural Networks (HGNNs) are increasingly recognized for their performance in areas like the web and e-commerce, where resilience against adversarial attacks is crucial.
no code implementations • 23 Oct 2023 • Yige Xu, Zhiwei Zeng, Zhiqi Shen
Emotion Recognition in Conversation (ERC) has been widely studied due to its importance in developing emotion-aware empathetic machines.
Computational Efficiency Emotion Recognition in Conversation
2 code implementations • 9 Feb 2023 • HongYu Zhou, Xin Zhou, Zhiwei Zeng, Lingzi Zhang, Zhiqi Shen
Recommendation systems have become popular and effective tools to help users discover their interesting items by modeling the user preference and item property based on implicit interactions (e. g., purchasing and clicking).
no code implementations • 2 Feb 2023 • Tong Zhang, Yong liu, Boyang Li, Zhiwei Zeng, Pengwei Wang, Yuan You, Chunyan Miao, Lizhen Cui
HAHT maintains a long-term memory of history conversations and utilizes history information to understand current conversation context and generate well-informed and context-relevant responses.
2 code implementations • 13 Jul 2022 • Xin Zhou, HongYu Zhou, Yong liu, Zhiwei Zeng, Chunyan Miao, Pengwei Wang, Yuan You, Feijun Jiang
Besides the user-item interaction graph, existing state-of-the-art methods usually use auxiliary graphs (e. g., user-user or item-item relation graph) to augment the learned representations of users and/or items.
no code implementations • 23 Jan 2016 • Zhiwei Zeng
With higher level of abstraction, the reusability of the quantitative model is also improved.