I am an assistant professor at the Department of Data Science, City University of Hong Kong.
I got my Ph.D. from the Department of Statistics, Oxford, supervised by Prof. Tom Rainforth and Prof. Yee Whye Teh.
Before that, I got my BS and MS degrees from Peking University and worked as a researcher at Bytedance AI lab.
My research interests include machine reasoning (mainly LLM reasoning), generative models, and, more generally, machine learning.
News
* Oct. 2024: I'm looking for self-motivated Ph.D. students (starting in 2025) and research assistants! Please drop me an email if you are interested.
Publications
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SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Ning Miao, Yee Whye Teh, Tom Rainforth
In ICLR, 2024.
[pdf]
[code]
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Learning Instance-Specific Augmentations by Capturing Local Invariances
Ning Miao, Tom Rainforth, Emile Mathieu, Yann Dubois, Yee Whye Teh, Adam Foster, Hyunjik Kim
In ICML, 2023.
[bib]
[pdf]
[code]
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On Incorporating Inductive Biases into VAEs
Ning Miao, Emile Mathieu, Siddharth N, Yee Whye Teh, Tom Rainforth
In ICLR, 2022.
[bib]
[pdf]
[code]
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Do You Have the Right Scissors? Tailoring Pre-trained Language Models via Monte-Carlo Methods
Ning Miao, YuXuan Song, Hao Zhou, Lei Li
In ACL, 2020.
[bib]
[pdf]
[code]
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Dispersed Exponential Family Mixture VAEs for Interpretable Text Generation
Wenxian Shi, Hao Zhou, Ning Miao, Shenjian Zhao, Lei Li
In ICML, 2020.
[bib]
[pdf]
[code]
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Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation
YuXuan Song, Ning Miao, Hao Zhou, Lei Li
In AISTATS, 2020.
[bib]
[pdf]
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Kernelized Bayesian Softmax for Text Generation
Ning Miao, Hao Zhou, Chengqi Zhao, Wenxian Shi, Lei Li
In NeurIPS, 2019.
[bib]
[pdf]
[code]
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Generating Fluent Adversarial Examples for Natural Languages
Huangzhao Zhang, Hao Zhou, Ning Miao, Lei Li
In ACL, 2019.
[bib]
[pdf]
[code]
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Constrained Sentence Generation via Metropolis-Hastings Sampling
Ning Miao, Hao Zhou, Lili Mou, Rui Yan, Lei Li
In AAAI, 2019.
[bib]
[pdf]
[code]
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Last updated: Sep 27, 2024