Hazel Kim

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 from Oxford and Yonatan Belinkov from Technion as a student of the European Laboratory for Learning and Intelligent Systems (ELLIS Society). During this summer, I am at LMU Munich to study with Hinrich Schütze.

Research Areas:
Interpretable and Controllable Language Models

Language Acquisition from Limited Sources

Language models shape the world with given data. They work well with quality and abundant data while providing biased perspectives with scarce, poor data. However, quality data is often expensive to collect or private to get access. This challenge has inspired me to study how to encourage language models to acquire language proficiency and reasoning ability from a limited quantity or quality of resources.

Causal Inference, not Correlation

The heavy reliance on correlations between input observation and output predictions limits language models to reason about cause-and-effect relationships that are not explicitly present in the text. High correlations do not always uncover the causality of events. Causal inference is a crucial topic to control language models against biased data.

Information Quantification

Computation creates valuable information. The usable information for models varies depending on their interaction between input and output resources. Exploring how to quantify information is essential for interpreting model behaviors.

Emergent Knowledge of Language Models

Language models emerge new knowledge that is not present in smaller models when the scale grows. The emergent knowledge is a valuable yet underexplored resource. This has motivated me to investigate them regarding the model capabilities of how trustworthy they are for transparent usage in real-world scenarios.

Publications

• Selected and Recent Papers

Google Scholar

Wonderful People I've Met: I was fortunate to start researching with consistent support from Yosub Han. I got great insights into what and how to research from Seong Joon Oh. I was delighted to work with humble yet astute advice from Sangdoo Yun and lucky to have inspiring discussions with Kangmin Yoo. I was happy to mentor enthusiastic JB. Kim in writing his first paper. I enjoyed working on my first paper with Daecheol Woo's sincerity and positive mindset. I thankfully met many great people while conducting research! I appreciate all of my collaborators for supporting me in many different ways :)