Han Zhou

PhD student in NLP

University of Cambridge

Biography

I am a second-year PhD student in Computation, Cognition, and Language (NLP) at Language Technology Lab, University of Cambridge. I am supervised by Prof. Anna Korhonen and Dr. Ivan Vulić. Previously, I interned at Gemini (RADML) and Context in AI Research (CAIR) Teams at Google DeepMind (formerly Google Research).

Before starting my PhD, I was an undergraduate student reading Engineering Science at University of Oxford. I received my second Master degree in MSc Machine Learning, UCL NLP Lab. I graduated top of my class.

I am always interested in modular, efficient, and reward-driven responsible intelligence.

Recent News

Apr 2024: I will be joining Google Cloud AI Research as a Student Researcher this summer.
Jan 2024: AutoPEFT was accepted at TACL 2024! We will present this work at ACL 2024.
Jan 2024: Batch Calibration is accepted to ICLR 2024! Batch Calibration has been featured in Google AI blog and presented as a spotlight at NeurIPS 2023 R0-FoMo.
Dec 2023: Attended EMNLP 2023 in-person. Glad to meet folks in Singapore.
Oct 2023: ClaPS and Multilingual Disparity were accepted at EMNLP 2023!
Jul 2023: Multi3WOZ was accepted at TACL 2023! We will present it at EMNLP 2023.
Jun 2023: Start as Student Researcher at Google Research.

Interests

Large Language Models
Parameter-Efficient Fine-Tuning
Prompt Optimization
Modularity

Education

PhD in Computation, Cognition, and Language, Oct 2022 -

University of Cambridge
MSc in Machine Learning, 2020 - 2021

University College London
BA, MEng in Engineering Science, 2015 - 2019

University of Oxford

Featured Publications

Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine Heller, Subhrajit Roy

January, 2024 International Conference on Learning Representations (ICLR)

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Mitigating prompt biases and unifying existing calibration approaches without labeled data.

Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen

January, 2024 Transactions of the Association for Computational Linguistics (TACL)

AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning

Automatic discovery of families of high-performing PEFT configurations.

Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen

October, 2023 Findings of the Association for Computational Linguistics (EMNLP)

Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning

Efficient prompt optimization via influential search space pruning.

Publications

Quickly discover relevant content by filtering publications.

Yinhong Liu, Han Zhou, Zhijiang Guo, Ehsan Shareghi, Ivan Vulić, Anna Korhonen, Nigel Collier (2024). Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators. arXiv preprint arXiv:2403.16950.

PDF Cite Code Abstract

Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine Heller, Subhrajit Roy (2024). Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering. International Conference on Learning Representations (ICLR).

PDF Cite Abstract (Google Research) OpenReview Blog (Google AI) Talk (NeurIPS Spotlight)

Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen (2024). AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning. Transactions of the Association for Computational Linguistics (TACL).

PDF Cite Code Abstract MIT Press ACL Anthology

Chengzu Li, Han Zhou, Goran Glavaš, Anna Korhonen, Ivan Vulić (2023). Can Large Language Models Retain Calibration with In-Context Learning?. ICLR 2024 Workshop on Reliable and Responsible Foundation Models.

PDF Cite Code Abstract

Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen (2023). Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning. Findings of the Association for Computational Linguistics (EMNLP).

PDF Cite Code Abstract OpenReview ACL Anthology

Songbo Hu, Han Zhou, Zhangdie Yuan, Milan Gritta, Guchun Zhang, Ignacio Iacobacci, Anna Korhonen, Ivan Vulić (2023). A Systematic Study of Performance Disparities in Multilingual Task-Oriented Dialogue Systems. The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP).

PDF Cite Code Abstract OpenReview ACL Anthology

Songbo Hu, Han Zhou, Mete Hergul, Milan Gritta, Guchun Zhang, Ignacio Iacobacci, Ivan Vulić, Anna Korhonen (2023). Multi3WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems. Transactions of the Association for Computational Linguistics (TACL).

PDF Cite Dataset Abstract MIT Press ACL Anthology

Qingcheng Zeng, Lucas Garay, Peilin Zhou, Dading Chong, Yining Hua, Jiageng Wu, Yikang Pan, Han Zhou, Rob Voigt, Jie Yang (2023). GreenPLM: Cross-Lingual Transfer of Monolingual Large Language Models at Almost No Cost. The 32nd International Joint Conference on Artificial Intelligence (IJCAI).

PDF Cite Code Abstract IJCAI 2023

Han Zhou, Ignacio Iacobacci, Pasquale Minervini (2023). XQA-DST: Multi-Domain and Multi-Lingual Dialogue State Tracking. Findings of the Association for Computational Linguistics (EACL).

PDF Cite Code Abstract ACL Anthology