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Chao-Hong Tan (谭超鸿)Ph.D. StudentNational Engineering Research Center of Speech and Language Information Processing Department of Electronic Engineering and Information Science University of Science and Technology of China Email: chtan@mail.ustc.edu.cn ![]() ![]() ![]() |
Hi there! My name is Chao-Hong Tan.
I am currently a 5th-year Ph.D. student at University of Science and Technology of China, supervised by Prof. Zhen-Hua Ling.
My main research interests lie within deep learning for natural language processing. I am particularly interested in natural language generation, including text generation with unstructured knowledge, empathetic dialogue, multi-party conversation, and text diffusion.
Additionally, my interests extend to natural language understanding, with a focus on spoken language intent recognition and efficient modeling of long sequences.
[U/R] |
Construct and Constrain the Latent Style Space of Listeners for Empathetic Dialogue Generation.
Chao-Hong Tan, Jia-Chen Gu, Zhen-Hua Ling, Quan Liu, Si Wei, Cong Liu IEEE Transactions on Affective Computing [paper] [code] |
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[U/R] |
Towards Multi-Granularity Knowledge Retrieval and Integration for Task-Oriented Dialogue Systems.
Chao-Hong Tan, Jia-Chen Gu, Quan Liu, Dan Liu, Zhen-Hua Ling Transactions on Audio, Speech and Language Processing [paper] [code] |
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[Preprint] |
DiffuSIA: Spiral Interaction Architecture for Encoder-Decoder Text Diffusion.
Chao-Hong Tan, Jia-Chen Gu, Zhen-Hua Ling [paper] [code] |
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2023 |
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[EMNLP] |
Is ChatGPT a Good Multi-Party Conversation Solver?
Chao-Hong Tan, Jia-Chen Gu, Zhen-Hua Ling In Findings of the Association for Computational Linguistics: EMNLP 2023, 2023. [paper] [code] |
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[EMNLP] |
MADNet: Maximizing Addressee Deduction Expectation for Multi-Party Conversation Generation.
Jia-Chen Gu*, Chao-Hong Tan*, Caiyuan Chu, Zhen-Hua Ling, Chongyang Tao, Quan Liu, Cong Liu, Guoping Hu In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023. [*Equal contribution] [paper] [code] |
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2022 |
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[ICLR] |
PoNet: Pooling Network for Efficient Token Mixing in Long Sequences.
Chao-Hong Tan, Qian Chen, Wen Wang, Qinglin Zhang, Siqi Zheng, Zhen-Hua Ling In The Tenth International Conference on Learning Representations, ICLR 2022, 2022. [paper] [code] [slide] [poster] |
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[ACL] |
TegTok: Augmenting Text Generation via Task-specific and Open-world Knowledge.
Chao-Hong Tan, Jia-Chen Gu, Chongyang Tao, Zhen-Hua Ling, Can Xu, Huang Hu, Xiubo Geng, Daxin Jiang In Findings of the Association for Computational Linguistics: ACL 2022, 2022. [paper] [code] |
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[ACL] |
HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversations.
Jia-Chen Gu*, Chao-Hong Tan*, Chongyang Tao, Zhen-Hua Ling, Huang Hu, Xiubo Geng, Daxin Jiang In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022. [*Equal contribution] [paper] [code] |
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[ICASSP] |
Neural Grapheme-to-Phoneme Conversion with Pre-trained Grapheme Models.
Lu Dong, Zhi-Qiang Guo, Chao-Hong Tan, Ya-Jun Hu, Yuan Jiang, Zhen-Hua Ling In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2022, 2022. [paper] |
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2021 |
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[DSTC] |
Learning to Retrieve Entity-Aware Knowledge and Generate Responses with Copy Mechanism for Task-Oriented Dialogue Systems.
Chao-Hong Tan, Xiaoyu Yang, Zi'ou Zheng, Tianda Li, Yufei Feng, Jia-Chen Gu, Quan Liu, Dan Liu, Zhen-Hua Ling, Xiaodan Zhu In Proceedings of the 35th AAAI Conference on Artificial Intelligence Workshop on the 9th Dialog System Technology Challenge, 2021. [paper] [code] [poster] |
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2019 |
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[ICMI] |
Multi-Classification Model for Spoken Language Understanding.
Chaohong Tan, Zhen-Hua Ling In International Conference on Multimodal Interaction, ICMI 2019, 2019. [paper] [code] [slide] |