Yoonjoo Lee

About

I am a Ph.D. student in the School of Computing at KAIST. I work with Juho Kim as a member of KIXLAB.

My research interest lies in the intersection of human-AI interaction (HAI) and natural language processing (NLP), focusing on aligning AI systems with human cognitive processes to make them more adaptive, interpretable, and human-centered. Specifically, I (1) develop how to develop AI systems that interactively adapt their outputs to individual users by modeling human cognitive processes based on users’ tasks and contexts, and (2) design evaluation methods to assess how effectively AI systems can generate outputs aligned with human cognitive processes.

Publications

Conference Papers

Benchmarking Model Ability to Predict Preferences from Interactions (Placeholder Title)
Tae Soo Kim, Yoonjoo Lee, et al.
Under review

Mind the Blind Spots: A Focus-Level Evaluation Framework for LLM Reviews
Hyungyu Shin, Jingyu Tang, Yoonjoo Lee, Nayoung Kim, Hyunseung Lim, Ji Yong Cho, Hwajung Hong, Moontae Lee, Juho Kim
Under review

ARXIVDIGESTABLES: Synthesizing Scientific Literature into Tables using Language Models
Benjamin Newman*, Yoonjoo Lee*, Aakanksha Naik, Pao Siangliulue, Raymond Fok, Juho Kim, Daniel S. Weld, Joseph Chee Chang, Kyle Lo
EMNLP 2024 Main Track | arxiv

The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models
Seungone Kim, Juyoung Suk, Ji Yong Cho, [18 authors], Yoonjoo Lee, [5 authors], Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, Minjoon Seo
NAACL 2025 | arxiv | Best Paper Award

One vs. Many: Comprehending Accurate Information from Multiple Erroneous and Inconsistent AI Generations
Yoonjoo Lee, Kihoon Son, Tae Soo Kim, Jisu Kim, John Joon Young Chung, Eytan Adar, Juho Kim
FAccT 2024 | arxiv

PaperWeaver: Enriching Topical Paper Alerts by Contextualizing Recommended Papers with User-collected Papers
Yoonjoo Lee, Hyeonsu B Kang, Matt Latzke, Juho Kim, Jonathan Bragg, Joseph Chee Chang, and Pao Siangliulue
CHI2024 | arxiv

EvalLM: Interactive Evaluation of Large Language Model Prompts on User-Defined Criteria
Tae Soo Kim, Yoonjoo Lee, Jamin Shin, Young-Ho Kim, and Juho Kim
CHI2024 | arxiv | video

VIVID: Human-AI Collaborative Authoring of Vicarious Dialogues from Lecture Videos
Seulgi Choi, Hyewon Lee, Yoonjoo Lee, and Juho Kim
CHI2024 | arxiv

QASA: Answering Advanced Questions on Scientific Articles
Yoonjoo Lee*, Kyungjae Lee*, Sunghyun Park, Dasol Hwang, Jaehyeon Kim, Hong-in Lee, and Moontae Lee
ICML 2023 | data link

Cells, Generators, and Lenses: Design Framework for Object-Oriented Interaction with Large Language Models
Tae Soo Kim, Yoonjoo Lee, Minsuk Chang, and Juho Kim
UIST 2023 | project website

DAPIE: Interactive Step-by-Step Explanatory Dialogues to Answer Children’s Why and How Questions
Yoonjoo Lee, Tae Soo Kim, Sungdong Kim, Yohan Yun, and Juho Kim
CHI 2023 | acm dl | video presentation | project website

Personalizing Ambience and Illusionary Presence: How People Use “Study with Me” Videos to Create Effective Studying Environments
Yoonjoo Lee, John Joon Young Chung, Jean Y. Song, Minsuk Chang, and Juho Kim
CHI 2021 | acm dl | video presentation

A Machine Learning Approach that meets Axiomatic Properties in Probabilistic Analysis of LTE Spectral Efficiency
Yoonjoo Lee, Yunbae Kim, and Seungken Park
ICTC, Oct. 2019 | ieee dl

Journal Articles

Forecasting realized volatility using data normalization and recurrent neural network
Yoonjoo Lee, Dong Wan Shin, and Ji Eun Choi
Communications for Statistical Applications and Methods, Vol. 31, No. 1, 1–23, 2024

Probabilistic Analysis of Spectral Efficiency for LTE based on PDCCH Measurement Data
Yoonjoo Lee, Yunbae Kim, Yeongyu Park, and Seungken Park
IEEE Communications Letters, vol. 23, no. 9, Sep. 2019 | ieee dl

Posters, Workshop Papers

How to Reflect Diverse People’s Perspectives in Large-Scale LLM-based Evaluations?
Yoonjoo Lee, Tae Soo Kim, and Juho Kim
CHI 2024 Workshop on Human-centered Evaluation and Auditing of Language Models

LMCanvas: Object-Oriented Interaction to Personalize Large Language Model-Powered Writing Environments
Tae Soo Kim, Arghya Sarkar, Yoonjoo Lee, Minsuk Chang, and Juho Kim
CHI 2023 Workshop on Generative AI and HCI

Interactive Children’s Story Rewriting Through Parent-Children Interaction
Yoonjoo Lee, Tae Soo Kim, Minsuk Chang, and Juho Kim
ACL 2022 workshop on In2Writing

XDesign: Integrating Interface Design into Explainable AI Education
Hyungyu Shin, Nabila Sindi, Yoonjoo Lee, Jaeryoung Ka, Jean Y. Song, and Juho Kim
SIGCSE TS 2022 Posters

A Study on the Distribution Analysis of LTE Resource Block Usage from TSME Measurement Data
Yoonjoo Lee, Yunbae Kim, and Seungken Park
KICS, Jun. 2018 | dbpia dl

A Study on the Estimation of Probability Distribution of the Spectral Efficiency of LTE based on TSME Measurement Data
Yunbae Kim, Yoonjoo Lee, and Seungken Park
KICS, Jun. 2018 | PDF

Research Experience

Adobe Research
Research Intern (Mentor: Alexa F Siu, Tong Sun)
^{May 2024 -}

Allen Institute for AI (AI2)
Research Intern (Mentor: Pao Siangliulue, Joseph Chee Chang, Jonathan Bragg, Kyle Lo)
^{May 2023 - Oct. 2023}

LG AI Research
Research Intern (Mentor: Moontae Lee)
^{Nov. 2022 - Mar. 2023}

Electronics and Telecommunications Research Institute(ETRI)
Graduate Research Assistant (Mentor: Yunbae Kim and Seungken Park)
^{Jan. 2018 - Dec. 2019}

Services

Reviewer: EMNLP 2023, CHI 2022-2023, UIST 2022-2023, ACL 2023, CSCW 2023, C&C 2022, IEEE TLT
Program Committee: CHI LBW 2023
Student Volunteer: CHI 2022