Research output per year
Research output per year
Personal profile
Author IDs
ORCID iD: 0009-0002-4489-2090
Scopus Author ID: 57216622967
Impact
Qualifications (Brief)
BS and MS (Peking University), PhD (University of Oxford)
Research Interests/Areas
Large language models, especially their reasoning ability; Generative models; Natural language processing
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Collaborations from the last five years
Recent external collaboration based on locations. Dive into details by clicking on the dots or
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Step-Level Sparse Autoencoder for Reasoning Process Interpretation
Yang, X. (Co-first Author), Liu, J. (Co-first Author), Lai, Y. (Co-first Author), Xu, H., Huang, Z. & Miao, N., 3 Mar 2026, arXiv.Research output: Working Papers › Preprint
1 Downloads (CityUHK Scholars) -
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Miao, N., Teh, Y. W. & Rainforth, T., Oct 2024, 12th International Conference on Learning Representations (ICLR 2024). International Conference on Learning Representations, ICLR, 16 p. (International Conference on Learning Representations, ICLR).Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
46 Link opens in a new tab Citations (Scopus) -
Learning Instance-Specific Augmentations by Capturing Local Invariances
Miao, N., Rainforth, T., Mathieu, E., Dubois, Y., Teh, Y. W., Foster, A. & Kim, H., 2023, ICML'23: Proceedings of the 40th International Conference on Machine Learning. Krause, A., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). JMLR.org, p. 24720-24736 1028. (Proceedings of Machine Learning Research; vol. 202).Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Open Access6 Link opens in a new tab Citations (Scopus) -
ON INCORPORATING INDUCTIVE BIASES INTO VAES
Miao, N., Mathieu, E., Siddharth, N., Teh, Y. W. & Rainforth, T., 2022, The Tenth International Conference on Learning Representations: ICLR 2022. International Conference on Learning Representations, ICLR, (ICLR - International Conference on Learning Representations).Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Open Access1 Link opens in a new tab Citation (Scopus) -
Dispersed exponential family mixture VAEs for interpretable text generation
Shi, W., Zhou, H., Miao, N. & Li, L., Jul 2020, 37th International Conference on Machine Learning (ICML 2020). Daumé III, H. & Singh, A. (eds.). Stroudsburg PA: International Machine Learning Society (IMLS), Vol. PART 12. p. 8799-8810 12 p. (International Conference on Machine Learning, ICML; vol. PartF168147-12)(Proceedings of Machine Learning Research; vol. 119).Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Open Access14 Link opens in a new tab Citations (Scopus)
Projects
- 2 Active
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DON: Research on A Cost-Efficient Path Towards Improving the Reasoning Ability of Large Language Models
MIAO, N. (Principal Investigator / Project Coordinator)
1/06/25 → …
Project: Research
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DON_RMG: Research on A Cost-Efficient Path Towards Improving the Reasoning Ability of Large Language Models - RMGS
MIAO, N. (Principal Investigator / Project Coordinator)
1/06/25 → …
Project: Research