University of Oxford Department of Computer Science, University of Oxford Wolfson College, Oxford ELLIS Society
Hazel Kim

Hazel Kim

Interpretable and Controllable Language Models Research →

{firstname}.kimh [AT] gmail

I am a DPhil student in computer science at the University of Oxford, conducting research in Natural Language Processing and Machine Learning. I am grateful to be advised by Philip Torr and Yarin Gal from Oxford and Hinrich Schütze from LMU Munich as a student of the European Laboratory for Learning and Intelligent Systems (ELLIS Society). Full bio →

Study nook at night — desk, books, and armchair
Portrait of Hazel Kim
News
Google Gemma Academic Program Award (Google Cloud Credit)
Google Gemma Academic Program Award (Google Cloud Credit)
LMU Munich Research Visit - Hinrich Schuetze (July - September 2024)
ELSA Mobility Grant, 2024
G-Research Grant for Early Career Researchers, 2024
Started DPhil in Computer Science at Oxford
Publications
View with summaries →

  1. Single LLM Debate, MoLaCE: Mixture of Latent Concept Experts Against Confirmation Bias

    Hazel Kim, Philip Torr

    Preprint

    PDF

  2. Measuring what Matters: Construct Validity in Large Language Model Benchmarks

    Andrew M. Bean, Ryan Othniel Kearns, Angelika Romanou, Franziska Sofia Hafner, Harry Mayne, Jan Batzner, Negar Foroutan, Chris Schmitz, Karolina Korgul, Hunar Batra, Oishi Deb, Emma Beharry, Cornelius Emde, Thomas Foster, Anna Gausen, María Grandury, Simeng Han, Valentin Hofmann, Lujain Ibrahim, Hazel Kim, Hannah Rose Kirk, Fangru Lin, Gabrielle Kaili-May Liu, Lennart Luettgau, Jabez Magomere, Jonathan Rystrøm, Anna Sotnikova, Yushi Yang, Yilun Zhao, Adel Bibi, Antoine Bosselut, Ronald Clark, Arman Cohan, Jakob Nicolaus Foerster, Yarin Gal, Scott A. Hale, Inioluwa Deborah Raji, Christopher Summerfield, Philip Torr, Cozmin Ududec, Luc Rocher, Adam Mahdi

    NeurIPS 2025 Datasets & Benchmarks

    PDF

  3. Detecting LLM Hallucination through Layer-wise Information Deficiency

    Hazel Kim, Tom A. Lamb, Adel Bibi, Philip Torr, Yarin Gal

    EMNLP 2025

    PDF

  4. How Ambiguous Are the Rationales For Natural Language Reasoning?

    Hazel Kim

    COLING 2025

    PDF

  5. ATHENA: Mathematical Reasoning with Thought Expansion

    JB. Kim, Hazel Kim, Joonghyuk Hahn, Yo-Sub Han

    EMNLP 2023

    PDF

  6. ALP: Data Augmentation Using Lexicalized PCFGs for Few-Shot Text Classification

    Hazel Kim, Daecheol Woo, Seong Joon Oh, Jeong-Won Cha, Yo-Sub Han

    AAAI 2022

    PDF

  7. LST: Lexicon-Guided Self-Training for Few-Shot Text Classification

    Hazel Kim*, Jaeman Son*, Yo-Sub Han

    Arxiv

    PDF
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