System-2 Reasoning via Generality and Adaptation
Kim, S. & Kim, S. (2024). System-2 Reasoning via Generality and Adaptation. NeurIPS Workshop S2R.
Curriculum Vitae
Education
- 2009.02 - 2013.08 B.S. in Computer Science, KAIST
- 2013.09 - 2016.08 M.S. in School of Computing, KAIST
- 2017.03 - 2023.02 Ph.D in School of Computing, KAIST
Work Experience
- 2016.09 - 2017.02 Postmaster Researcher in School of Computing, KAIST
- 2017.05 - 2023.03 Programming Lecturer in WITLab
- 2023.02 - 2023.03 Programming Engineer in GraphAI
- 2023.04 - 2025.08 Postdoctoral Researcher in AI Graduate School, GIST
Publications
Reasoning Abilities of Large Language Models through the Lens of Abstraction and Reasoning
Lee, S., Sim, W., Shin, D., Kim, S., & Kim, S. (2024). Reasoning Abilities of Large Language Models through the Lens of Abstraction and Reasoning. NeurIPS Workshop S2R.
Diffusion-Based Offline RL for Improved Decision-Making in Augmented ARC Task
Kim, Y., Park, J., Kim, H., Kim, S., Lee, B., & Kim, S. (2024). Diffusion-Based Offline RL for Improved Decision-Making in Augmented ARC Task. arXiv.
DIAR: Diffusion-model-guided Implicit Q-learning with Adaptive Revaluation
Park, J., Kim, Y., Kim, S., Lee, B., & Kim, S. (2024). DIAR: Diffusion-model-guided Implicit Q-learning with Adaptive Revaluation. arXiv.
O2ARC 3.0: A Platform for Solving and Creating ARC Tasks
Shim, S., Ko, D., Lee, H., Lee, S., Song, D., Hwang, S., Kim, S., & Kim, S. (2024). O2ARC 3.0: A Platform for Solving and Creating ARC Tasks. IJCAI Demo.
Enhancing Analogical Reasoning in the Abstraction and Reasoning Corpus via Model-Based RL
Lee, J., Sim, W., Kim, S., & Kim, S. (2024). Enhancing Analogical Reasoning in the Abstraction and Reasoning Corpus via Model-Based RL. IJCAI Workshop IARML.
ARCLE: The Abstraction and Reasoning Corpus Learning Environment for Reinforcement Learning
Lee, H., Kim, S., Lee, S., Hwang, S., Lee, J., Lee, B., & Kim, S. (2024). ARCLE: The Abstraction and Reasoning Corpus Learning Environment for Reinforcement Learning. CoLLAs.
Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus
Lee, S., Sim, W., Shin, D., Hwang, S., Seo, W., Park, J., Lee, S., Kim, S., & Kim, S. (2024). Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus. ACM TIST (under review).
ARC 문제 해결을 위한 프롬프트 엔지니어링의 가능성
Sim, W., Jin, H., Kim, S., & Kim, S. (2023). The Possibility of Prompt Engineering for ARC Problem Solving. KIISE Transactions on Computing Practices.
월드모델을 통한 ARC의 핵심 지식 추출
Lee. J., Lee, S., Kim, S., & Kim, S. (2023). Extracting the Core Knowledge of ARC with the World Model. Korea Software Congress.
추상화 및 추론 문제 해결을 위한 대조학습
Gu, G., Sim, W., Im, J., Kim, S., & Kim, S. (2023). Using Contrastive Learning for Abstraction and Reasoning Task. Korea Software Congress.
ARCLE: 추상화 및 추론을 위한 강화학습 환경
Lee. H., Kim, S., & Kim, S. (2023). ARCLE: Gymnasium Environment for Abstraction and Reasoning Corpus. Korea Software Congress.
Unraveling the ARC Puzzle: Mimicking Human Solutions with Object-Centric Decision Transformer
Park, J., Im, J., Hwang, S., Lim, M., Ualibekova, S., Kim, S., & Kim, S. (2023). Unraveling the ARC Puzzle: Mimicking Human Solutions with Object-Centric Decision Transformer. ICML Workshop ILHF.
의사결정 트랜스포머를 사용한 추상화와 추론
Park., J., Im., J., Lee, Y., Shin, D., Kim, S., & Kim, S. (2023). Abstraction and Reasoning Challenge with Decision Transformer. Korea Computer Congress.
준지도 시계열 분류를 위한 세그먼트 대조학습
Shin, Y., Park, D., Kang, J., & Kim, S. (2022). Contrastive Learning with Segment Supervision for Semi-Supervised Time Series Classification. Korea Software Congress.
Autoencoder ODEs for Time Series Anomaly Detection
Kim, B., Na, J., Byun, Y., Kim, S., & Lee., J.-G. (2022). Autoencoder ODEs for Time Series Anomaly Detection. Korea Software Congress.
AWS DeepRacer 를 활용한 라이다 센서 유무에 따른 강화학습 기반 자율주행 모델 성능 비교
Kim, J., Kim, D., Kim, S., Kang, J., Park, D., & Lee., J.-G. (2022). Performance Comparison of Self-Driving Models With and Without LIDAR Sensors Based on Reinforcement Learning in AWS DeepRacer Platform . Korea Computer Congress.
Generating a Machine Learning Model with a Few Sentences
Trirat, P., Shin, Y., Kim, S., & Kim, M. (2021). Generating a Machine Learning Model with a Few Sentences. Korea Software Congress.
Revisit Prediction by Deep Survival Analysis
Kim, S., Song, H., Kim, S., & Lee, J.-G. (2020). Revisit Prediction by Deep Survival Analysis. PAKDD.
Building Social Networking Services Systems Using the Relational Shared-Nothing Parallel DBMS
Whang, K.Y., Na, I., Yun, T., Park, J., Cho, K., Kim, S., Yi, I., & Lee, B. (2020). Building Social Networking Services Systems Using the Relational Shared-Nothing Parallel DBMS. DKE.
거시적 동선 정보에 기반한 고객 재방문 예측
Kim, B., Kim, S., Kim, S., & Lee, J.-G. (2019). Customer Revisit Prediction Using Macroscale Mobility Information. Korea Software Congress.
Spatial OLAP 에서 공간 연산자의 구현 기법 비교
Kim, S. (2018). A Comparison of Implementation Method of Spatial Operator in Spatial OLAP. Korea Computer Congress.
SentiWorld: Understanding Emotions between Countries Based on Tweets
Yea, S.-J., Kim, S., TO, J.-M., & Lee, J.-G. (2016). SentiWorld: Understanding Emotions between Countries Based on Tweets. ICWSM Demo.