Seungone Kim

M.S. Student at KAIST AI

seungone@kaist.ac.kr

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About
Hello! I am a M.S. Student at KAIST AI, advised by Minjoon Seo.
I am also an incoming Ph.D. Student at the Carnegie Mellon University Language Technologies Institute, co-advised by Graham Neubig and Sean Welleck.

My primary research focus is to establish a science of language model behaviors. Concretely, my research interests include: (i) developing LLM Evaluation frameworks that systematically identify what specific capabilities language models lack and (ii) continuously improving language models with (human) feedback.
News
Mar 2024     Our Self-Explore and Think-and-Execute paper are released!
Mar 2024     I got admitted at Carnegie Mellon University Language Technologies Institute as a Ph.D. student.
Mar 2024     Our Prometheus-Vision, LangBridge, and Multi-Task Inference paper got accepted to ICLR 2024 ME-FoMo Workshop!
Jan 2024     Our Prometheus and Flask paper got accepted to NeurIPS 2023 Instruction Workshop and ICLR 2024!
Oct 2023     Our CoT Collection paper got accepted to EMNLP 2023!
Apr 2023     Our ExpertLM paper got accepted to ICML 2023!
Feb 2023     Our CoTEVer paper got accepted to EACL 2023 (Demo Track)!
Oct 2022     I got admitted at KAIST AI as a M.S. student. I will continue doing research at LK Lab.
Oct 2022     Our SICK paper got accepted to COLING 2022!

Education

Language Technologies Institute, Carnegie Mellon UniversitySep. 2024 - Present

Ph.D. in Computer Science (Advisors: Graham Neubig and Sean Welleck)

KAIST AIMar. 2023 - Aug. 2024

M.S. in Artificial Intelligence (Advisor: Minjoon Seo)

Yonsei UniversityMar. 2018 - Feb. 2023

B.S. in Computer Science

Publications

2024

Self-Explore to Avoid the Pit: Improving the Reasoning Capabilities of Language Models with Fine-grained Rewards

Hyeonbin Hwang, Doyoung Kim, Seungone Kim, Seonghyeon Ye, Minjoon Seo

Preprint Under Review

Paper Code

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Hyungjoo Chae, Yeonghyeon Kim, Seungone Kim, Kai Tzu-iunn Ong, Beong-woo Kwak, Moohyeon Kim, Seonghwan Kim, Taeyoon Kwon, Jiwan Chung, Youngjae Yu, Jinyoung Yeo

Preprint Under Review

Paper Code

Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging

Joel Jang, Seungone Kim, Bill Yuchen Lin, Yizhong Wang, Jack Hessel, Luke Zettlemoyer, Hannaneh Hajishirzi, Yejin Choi, Prithviraj Ammanabrolu

Preprint Under Review

Paper Code

KMMLU: Measuring Massive Multitask Language Understanding in Korean

Guijin Son, Hanwool Lee, Sungdong Kim, Seungone Kim, Niklas Muennighoff, Taekyoon Choi, Cheonbok Park, Kang Min Yoo, Stella Biderman

Preprint Under Review

Paper Code

LangBridge: Multilingual Reasoning without Multilingual Supervision

Dongkeun Yoon, Joel Jang, Sungdong Kim, Seungone Kim, Sheikh Shafayat, Minjoon Seo

ICLR 2024 ME-FoMo Workshop & Preprint Under Review

Paper Code

Prometheus-Vision: Vision-Language Model as a Judge for Fine-grained Evaluation

Seongyun Lee*, Seungone Kim*, Sue Hyun Park, Geewook Kim, Minjoon Seo

ICLR 2024 ME-FoMo Workshop & Preprint Under Review

Paper Code

Multi-Task Inference: Can Large Language Models Follow Multiple Instructions at Once?

Guijin Son*, Sangwon Baek, Sangdae Nam, Ilgyun Jeong, Seungone Kim*

ICLR 2024 ME-FoMo Workshop & Preprint Under Review

Paper Code

Prometheus: Inducing Fine-grained Evaluation Capability in Language Models

Seungone Kim*, Jamin Shin*, Yejin Cho*, Joel Jang, Shayne Longpre, Hwaran Lee, Sangdoo Yun, Seongjin Shin, Sungdong Kim, James Thorne, Minjoon Seo

ICLR 2024 & NeurIPS 2023 Instruction Workshop

Paper Code

FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets

Seonghyeon Ye, Doyoung Kim, Sungdong Kim, Hyeonbin Hwang, Seungone Kim, Yongrae Jo, James Thorne, Juho Kim, Minjoon Seo

ICLR 2024 & NeurIPS 2023 Instruction Workshop

Paper Code

2023

The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-tuning

Seungone Kim*, Se June Joo*, Doyoung Kim, Joel Jang, Seonghyeon Ye, Jamin Shin, Minjoon Seo

EMNLP 2023

Paper Code

Exploring the Benefits of Training Expert Language Models over Instruction Tuning

Joel Jang, Seungone Kim, Seonghyeon Ye, Doyoung Kim, Lajanugen Logeswaran, Moontae Lee, Kyungjae Lee, Minjoon Seo

ICML 2023

Paper Code

CoTEVer: Chain of Thought Prompting Annotation Toolkit for Explanation Verification

Seungone Kim, Se June Joo, Yul Jang, Hyungjoo Chae, Jinyoung Yeo

EACL 2023

Paper Code

2022

Mind the Gap! Injecting Commonsense Knowledge for Abstractive Dialogue Summarization

Seungone Kim*, Se June Joo*, Hyungjoo Chae*, Chaehyeong Kim, Seung-won Hwang, Jinyoung Yeo

COLING 2022

Paper Code
( * indicates equal contribution )

Vitæ

Full CV in PDF.

  • CMU LTI Sep. 2024 - Present
    Ph.D. in Computer Science (Advisors: Graham Neubig and Sean Welleck)
    To be decided
  • AML Lab @ LG AI Research Jan. 2024 - Present
    Research Intern (Mentor: Kyungjae Lee)
    Working on building a comprehensive NLG benchmark.
  • Language Lab @ Naver AI Lab Mar. 2023 - Dec. 2023
    Research Intern (Mentor: Jamin Shin)
    Worked on building an open-sourced evaluator LM & VLM that could potentially replace GPT-4 and GPT-4V Evaluation.
  • KAIST AI Mar. 2023 - Aug. 2024 (Expected)
    M.S. in Artificial Intelligence (Advisor: Minjoon Seo)
    Working on LLM Evaluation Frameworks. Early Graduation (3 semesters).
  • LK Lab @ KAIST AI Jul. 2022 - Feb. 2023
    Research Intern (Mentor: Joel Jang)
    Worked on developing LMs that can generalize to novel tasks.
  • Yonsei University Mar. 2018 - Feb. 2023
    B.S. in Computer Science
    Early Graduation (7 semesters).
Seungone Kim
Last updated on January 18, 2024