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← Authors

Jaesik Choi

38 papers · 2015–2025 · 10 conferences · across top CS/AI conferences

Achievements

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+12 more ↓ 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (10) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (10)
πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (5) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (11) πŸ”₯ Unstoppable (8) πŸ’Ž Century Club (38) ⚑ Prolific Year (6) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (189) ❓ The Questioner

Conferences

AAAI (10) ICML (6) EMNLP (5) IJCAI (5) ICLR (3) NIPS (3) CVPR (2) ICCV (2) ACL (1) AISTATS (1)

Top co-authors

Anh Tong (7) Jiyeon Han (6) Kyowoon Lee (5) Haedong Jeong (5) Cheongwoong Kang (3) Giyoung Jeon (3) Dahee Kwon (3) Hwanil Choi (3) Wonjoon Chang (3) Seong-Whan Lee (3)

Keywords

image generation (5) large language model (4) neural network (4) gaussian process (4) generative adversarial network (4) deep neural network (3) representation learning (3) input attribution (2) unsupervised learning (2) attribution method (2) convolutional neural network (2) generative model (2) reinforcement learning (2) domain adaptation (2) neural network interpretability (2) feature learning (2) feature attribution (2) time series (2) diffusion model (2) integrated gradient (2)

Papers

Deontological Keyword Bias: The Impact of Modal Expressions on Normative Judgments of Language Models ACL 2025 Enhancing Creative Generation on Stable Diffusion-based Models CVPR 2025 Rethinking Shapley Value for Negative Interactions in Non-convex Games ICLR 2025 Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations ICCV 2025 When Format Changes Meaning: Investigating Semantic Inconsistency of Large Language Models EMNLP 2025 Diverse Rare Sample Generation with Pretrained GANs AAAI 2025 xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition AAAI 2025 Local Manifold Approximation and Projection for Manifold-Aware Diffusion Planning ICML 2025 Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning ICLR 2025 Memorizing Documents with Guidance in Large Language Models IJCAI 2024 Towards Dynamic Trend Filtering through Trend Point Detection with Reinforcement Learning IJCAI 2024 Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision AAAI 2024 Pathwise Explanation of ReLU Neural Networks AISTATS 2024 Towards Diverse Perspective Learning with Selection over Multiple Temporal Poolings AAAI 2024 CR-COPEC: Causal Rationale of Corporate Performance Changes to learn from Financial Reports EMNLP 2023 Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans NIPS 2023 Impact of Co-occurrence on Factual Knowledge of Large Language Models EMNLP 2023 Beyond Single Path Integrated Gradients for Reliable Input Attribution via Randomized Path Sampling ICCV 2023 Rarity Score : A New Metric to Evaluate the Uncommonness of Synthesized Images ICLR 2023 Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills ICML 2023 Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks? IJCAI 2022 An Unsupervised Way to Understand Artifact Generating Internal Units in Generative Neural Networks AAAI 2022 Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Network NIPS 2022 Learning Fractional White Noises in Neural Stochastic Differential Equations NIPS 2022 The Global Banking Standards QA Dataset (GBS-QA) EMNLP 2021 Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior AAAI 2021 Automatic Correction of Internal Units in Generative Neural Networks CVPR 2021 Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations AAAI 2021 Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems AAAI 2021 Conditional Temporal Neural Processes with Covariance Loss ICML 2021 Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks AAAI 2020 An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks AAAI 2020 Discovering Latent Covariance Structures for Multiple Time Series ICML 2019 Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes IJCAI 2019 Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling ICML 2018 Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series ICML 2016 A Deterministic Partition Function Approximation for Exponential Random Graph Models IJCAI 2015 Reading Documents for Bayesian Online Change Point Detection EMNLP 2015