Jinwoo Shin

Test-Time Adaptation with Binary Feedback ICML 2025 Training Text-to-Molecule Models with Context-Aware Tokenization EMNLP 2025 Controllable Blur Data Augmentation Using 3D-Aware Motion Estimation ICLR 2025 Subtask-Aware Visual Reward Learning from Segmented Demonstrations ICLR 2025 Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents ICLR 2025 StarFT: Robust Fine-tuning of Zero-shot Models via Spuriosity Alignment IJCAI 2025 PRIME: Deep Imbalanced Regression with Proxies ICML 2025 ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification ICML 2025 Think Clearly: Improving Reasoning via Redundant Token Pruning EMNLP 2025 Peri-LN: Revisiting Normalization Layer in the Transformer Architecture ICML 2025 Debiasing Online Preference Learning via Preference Feature Preservation ACL 2025 DiffusionGuard: A Robust Defense Against Malicious Diffusion-based Image Editing ICLR 2025 Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think ICLR 2025 Spread Preference Annotation: Direct Preference Judgment for Efficient LLM Alignment ICLR 2025 Closest Neighbors are Harmful for Lightweight Masked Auto-encoders CVPR 2025 Controllable Human Image Generation with Personalized Multi-Garments CVPR 2025 Efficient Long Video Tokenization via Coordinate-based Patch Reconstruction CVPR 2025 Calibrated Multi-Preference Optimization for Aligning Diffusion Models CVPR 2025 Accelerated Test-Time Scaling with Model-Free Speculative Sampling EMNLP 2025 Personalized Language Models via Privacy-Preserving Evolutionary Model Merging EMNLP 2025 Mamba Drafters for Speculative Decoding EMNLP 2025 Direct Consistency Optimization for Robust Customization of Text-to-Image Diffusion models NIPS 2024 Online Adaptation of Language Models with a Memory of Amortized Contexts NIPS 2024 Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretization CVPR 2024 Discovering and Mitigating Visual Biases through Keyword Explanation CVPR 2024 Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs ICLR 2024 Querying Easily Flip-flopped Samples for Deep Active Learning ICLR 2024 Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models ICLR 2024 Safeguard Text-to-Image Diffusion Models with Human Feedback Inversion ECCV 2024 SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs ICLR 2024 Adversarial Robustification via Text-to-Image Diffusion Models ECCV 2024 Improving Diffusion Models for Authentic Virtual Try-on in the Wild ECCV 2024 Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback EMNLP 2024 DreamFlow: High-quality text-to-3D generation by Approximating Probability Flow ICLR 2024 Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition ICLR 2024 Visual Representation Learning with Stochastic Frame Prediction ICML 2024 Data-Efficient Molecular Generation with Hierarchical Textual Inversion ICML 2024 ReMoDetect: Reward Models Recognize Aligned LLM's Generations NIPS 2024 TrackIME: Enhanced Video Point Tracking via Instance Motion Estimation NIPS 2024 Conditional Synthesis of 3D Molecules with Time Correction Sampler NIPS 2024 Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning NIPS 2024 Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning ICLR 2023 Multi-View Masked World Models for Visual Robotic Manipulation ICML 2023 Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration NIPS 2023 Slimmed Asymmetrical Contrastive Learning and Cross Distillation for Lightweight Model Training NIPS 2023 Guide Your Agent with Adaptive Multimodal Rewards NIPS 2023 S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions NIPS 2023 Multi-scale Diffusion Denoised Smoothing NIPS 2023 Learning Large-scale Neural Fields via Context Pruned Meta-Learning NIPS 2023 Collaborative Score Distillation for Consistent Visual Editing NIPS 2023 Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder NIPS 2023 Modality-Agnostic Variational Compression of Implicit Neural Representations ICML 2023 Prefer to Classify: Improving Text Classifiers via Auxiliary Preference Learning ICML 2023 Confidence-Aware Training of Smoothed Classifiers for Certified Robustness AAAI 2023 infoVerse: A Universal Framework for Dataset Characterization with Multidimensional Meta-information ACL 2023 Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles AISTATS 2023 Guiding Energy-based Models via Contrastive Latent Variables ICLR 2023 STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables ICLR 2023 IFSeg: Image-Free Semantic Segmentation via Vision-Language Model CVPR 2023 Enhancing Multiple Reliability Measures via Nuisance-Extended Information Bottleneck CVPR 2023 BiasAdv: Bias-Adversarial Augmentation for Model Debiasing CVPR 2023 Video Probabilistic Diffusion Models in Projected Latent Space CVPR 2023 Imitating Graph-Based Planning with Goal-Conditioned Policies ICLR 2023 Preference Transformer: Modeling Human Preferences using Transformers for RL ICLR 2023 Self-Supervised Dense Consistency Regularization for Image-to-Image Translation CVPR 2022 NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation NIPS 2022 SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning ICLR 2022 Scalable Neural Video Representations with Learnable Positional Features NIPS 2022 Spread Spurious Attribute: Improving Worst-group Accuracy with Spurious Attribute Estimation ICLR 2022 What Makes Better Augmentation Strategies? Augment Difficult but Not too Different ICLR 2022 Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks ICLR 2022 Model-augmented Prioritized Experience Replay ICLR 2022 Meta-Learning with Self-Improving Momentum Target NIPS 2022 RényiCL: Contrastive Representation Learning with Skew Rényi Divergence NIPS 2022 Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning ICML 2022 K-Centered Patch Sampling for Efficient Video Recognition ECCV 2022 Consistency Regularization for Adversarial Robustness AAAI 2022 Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing AAAI 2022 TSPipe: Learn from Teacher Faster with Pipelines ICML 2022 Contrastive Dual Gating: Learning Sparse Features With Contrastive Learning CVPR 2022 Patch-Level Representation Learning for Self-Supervised Vision Transformers CVPR 2022 Time Is MattEr: Temporal Self-supervision for Video Transformers ICML 2022 Self-Improved Retrosynthetic Planning ICML 2021 Scaling Neural Tangent Kernels via Sketching and Random Features NIPS 2021 Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning NIPS 2021 RoMA: Robust Model Adaptation for Offline Model-based Optimization NIPS 2021 Meta-Learning Sparse Implicit Neural Representations NIPS 2021 Object-aware Contrastive Learning for Debiased Scene Representation NIPS 2021 Improving Transferability of Representations via Augmentation-Aware Self-Supervision NIPS 2021 Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning NIPS 2021 SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness NIPS 2021 Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble CORL 2021 GTA: Graph Truncated Attention for Retrosynthesis AAAI 2021 MASKER: Masked Keyword Regularization for Reliable Text Classification AAAI 2021 Provable Memorization via Deep Neural Networks using Sub-linear Parameters COLT 2021 Quality-Agnostic Image Recognition via Invertible Decoder CVPR 2021 Co2L: Contrastive Continual Learning ICCV 2021 Learning to Sample with Local and Global Contexts in Experience Replay Buffer ICLR 2021 Training GANs with Stronger Augmentations via Contrastive Discriminator ICLR 2021 Layer-adaptive Sparsity for the Magnitude-based Pruning ICLR 2021 $i$-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning ICLR 2021 Minimum Width for Universal Approximation ICLR 2021 Learning to Generate Noise for Multi-Attack Robustness ICML 2021 State Entropy Maximization with Random Encoders for Efficient Exploration ICML 2021 RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning IJCAI 2021 Elastic Resource Sharing for Distributed Deep Learning NSDI 2021 M2m: Imbalanced Classification via Major-to-Minor Translation CVPR 2020 Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning ICLR 2020 Learning What to Defer for Maximum Independent Sets ICML 2020 Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix ICML 2020 Self-supervised Label Augmentation via Input Transformations ICML 2020 Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning ICML 2020 Consistency Regularization for Certified Robustness of Smoothed Classifiers NIPS 2020 CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances NIPS 2020 Learning from Failure: De-biasing Classifier from Biased Classifier NIPS 2020 Time-Reversal Symmetric ODE Network NIPS 2020 Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning NIPS 2020 Guiding Deep Molecular Optimization with Genetic Exploration NIPS 2020 Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning NIPS 2020 Learning Bounds for Risk-sensitive Learning NIPS 2020 Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning NIPS 2020 Adversarial Neural Pruning with Latent Vulnerability Suppression ICML 2020 Regularizing Class-Wise Predictions via Self-Knowledge Distillation CVPR 2020 Lookahead: A Far-sighted Alternative of Magnitude-based Pruning ICLR 2020 Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild ICCV 2019 Iterative Bayesian Learning for Crowdsourced Regression AISTATS 2019 Learning What and Where to Transfer ICML 2019 Training CNNs with Selective Allocation of Channels ICML 2019 Robust Inference via Generative Classifiers for Handling Noisy Labels ICML 2019 Spectral Approximate Inference ICML 2019 Mining GOLD Samples for Conditional GANs NIPS 2019 InstaGAN: Instance-aware Image-to-Image Translation ICLR 2019 Neural Adaptive Content-aware Internet Video Delivery OSDI 2018 Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples ICLR 2018 A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks NIPS 2018 Stochastic Chebyshev Gradient Descent for Spectral Optimization NIPS 2018 Learning to Specialize with Knowledge Distillation for Visual Question Answering NIPS 2018 Gauged Mini-Bucket Elimination for Approximate Inference AISTATS 2018 Hierarchical Novelty Detection for Visual Object Recognition CVPR 2018 Bucket Renormalization for Approximate Inference ICML 2018 Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models AISTATS 2017 Gauging Variational Inference NIPS 2017 Confident Multiple Choice Learning ICML 2017 Faster Greedy MAP Inference for Determinantal Point Processes ICML 2017 Optimality of Belief Propagation for Crowdsourced Classification ICML 2016 Synthesis of MCMC and Belief Propagation NIPS 2016 Large-scale log-determinant computation through stochastic Chebyshev expansions ICML 2015 Minimum Weight Perfect Matching via Blossom Belief Propagation NIPS 2015 A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles NIPS 2013 Complexity of Bethe Approximation AISTATS 2012