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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Sejin Kim
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publications
SentiWorld: Understanding Emotions between Countries Based on Tweets
Published in ICWSM Demo, 2016
Recommended citation: Yea, S.-J., Kim, S., TO, J.-M., & Lee, J.-G. (2016). SentiWorld: Understanding Emotions between Countries Based on Tweets. ICWSM Demo. https://ojs.aaai.org/index.php/ICWSM/article/view/14706/14555
Spatial OLAP 에서 공간 연산자의 구현 기법 비교
Published in Korea Computer Congress, 2018
Recommended citation: Kim, S. (2018). A Comparison of Implementation Method of Spatial Operator in Spatial OLAP. Korea Computer Congress. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE07502958
거시적 동선 정보에 기반한 고객 재방문 예측
Published in Korea Software Congress, 2019
Recommended citation: Kim, B., Kim, S., Kim, S., & Lee, J.-G. (2019). Customer Revisit Prediction Using Macroscale Mobility Information. Korea Software Congress. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE09301908
Building Social Networking Services Systems Using the Relational Shared-Nothing Parallel DBMS
Published in DKE, 2020
Recommended citation: 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. https://www.sciencedirect.com/science/article/pii/S0169023X18306013
Revisit Prediction by Deep Survival Analysis
Published in PAKDD, 2020
Recommended citation: Kim, S., Song, H., Kim, S., & Lee, J.-G. (2020). Revisit Prediction by Deep Survival Analysis. PAKDD. https://link.springer.com/content/pdf/10.1007/978-3-030-47436-2_39.pdf
Generating a Machine Learning Model with a Few Sentences
Published in Korea Software Congress, 2021
Recommended citation: Trirat, P., Shin, Y., Kim, S., & Kim, M. (2021). Generating a Machine Learning Model with a Few Sentences. Korea Software Congress. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11035819
AWS DeepRacer 를 활용한 라이다 센서 유무에 따른 강화학습 기반 자율주행 모델 성능 비교
Published in Korea Computer Congress, 2022
Recommended citation: 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. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11113594
Autoencoder ODEs for Time Series Anomaly Detection
Published in Korea Software Congress, 2022
Recommended citation: Kim, B., Na, J., Byun, Y., Kim, S., & Lee., J.-G. (2022). Autoencoder ODEs for Time Series Anomaly Detection. Korea Software Congress. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11224165
준지도 시계열 분류를 위한 세그먼트 대조학습
Published in Korea Software Congress, 2022
Recommended citation: Shin, Y., Park, D., Kang, J., & Kim, S. (2022). Contrastive Learning with Segment Supervision for Semi-Supervised Time Series Classification. Korea Software Congress. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11224263
의사결정 트랜스포머를 사용한 추상화와 추론
Published in Korea Computer Congress, 2023
Recommended citation: Park., J., Im., J., Lee, Y., Shin, D., Kim, S., & Kim, S. (2023). Abstraction and Reasoning Challenge with Decision Transformer. Korea Computer Congress. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11488083
Unraveling the ARC Puzzle: Mimicking Human Solutions with Object-Centric Decision Transformer
Published in ICML Workshop ILHF, 2023
Recommended citation: 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. https://arxiv.org/abs/2306.08204
ARCLE: 추상화 및 추론을 위한 강화학습 환경
Published in Korea Software Congress, 2023
Recommended citation: Lee. H., Kim, S., & Kim, S. (2023). ARCLE: Gymnasium Environment for Abstraction and Reasoning Corpus. Korea Software Congress. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11705128
추상화 및 추론 문제 해결을 위한 대조학습
Published in Korea Software Congress, 2023
Recommended citation: Gu, G., Sim, W., Im, J., Kim, S., & Kim, S. (2023). Using Contrastive Learning for Abstraction and Reasoning Task. Korea Software Congress. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11705335
월드모델을 통한 ARC의 핵심 지식 추출
Published in Korea Software Congress, 2023
Recommended citation: Lee. J., Lee, S., Kim, S., & Kim, S. (2023). Extracting the Core Knowledge of ARC with the World Model. Korea Software Congress. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11705335
ARC 문제 해결을 위한 프롬프트 엔지니어링의 가능성
Published in KIISE Transactions on Computing Practices, 2024
Recommended citation: Sim, W., Jin, H., Kim, S., & Kim, S. (2023). The Possibility of Prompt Engineering for ARC Problem Solving. KIISE Transactions on Computing Practices. https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11716261
Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus
Published in arXiv:2403.11793, 2024
Recommended citation: 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). https://arxiv.org/abs/2403.11793
ARCLE: The Abstraction and Reasoning Corpus Learning Environment for Reinforcement Learning
Published in CoLLAs, 2024
Recommended citation: 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. https://arxiv.org/abs/2407.20806
Enhancing Analogical Reasoning in the Abstraction and Reasoning Corpus via Model-Based RL
Published in IJCAI Workshop IARML, 2024
Recommended citation: 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. https://arxiv.org/abs/2408.14855
O2ARC 3.0: A Platform for Solving and Creating ARC Tasks
Published in IJCAI Demo, 2024
Recommended citation: 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. https://www.ijcai.org/proceedings/2024/1034.pdf
DIAR: Diffusion-model-guided Implicit Q-learning with Adaptive Revaluation
Published in arXiv, 2024
Recommended citation: Park, J., Kim, Y., Kim, S., Lee, B., & Kim, S. (2024). DIAR: Diffusion-model-guided Implicit Q-learning with Adaptive Revaluation. arXiv. https://arxiv.org/abs/2410.11338
Diffusion-Based Offline RL for Improved Decision-Making in Augmented ARC Task
Published in arXiv, 2024
Recommended citation: 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. https://arxiv.org/abs/2410.11338
Reasoning Abilities of Large Language Models through the Lens of Abstraction and Reasoning
Published in NeurIPS Workshop S2R, 2024
Recommended citation: 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. https://openreview.net/forum?id=getEDedhSV
System-2 Reasoning via Generality and Adaptation
Published in NeurIPS Workshop S2R, 2024
Recommended citation: Kim, S. & Kim, S. (2024). System-2 Reasoning via Generality and Adaptation. NeurIPS Workshop S2R. https://arxiv.org/abs/2410.07866