← Authors

Jinwoo Shin

150 papers · 2012–2025 · 15 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (12) πŸƒ Academic Marathon (13) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (15) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (29) 🏠 Conference Loyalist (43) πŸ”¬ Deep Specialist (16) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ† Keyword Champion πŸ† Grand Slam 🀝 Dynamic Duo (26) πŸ“ˆ Trend Setter ❓ The Questioner πŸš€ Conference Pioneer ⚑ Prolific Year (20) πŸ”₯ Unstoppable (11) πŸ—ƒοΈ Keyword Collector (80) πŸ’Ž Century Club (150)

Conferences

NIPS (43) ICLR (31) ICML (29) CVPR (17) EMNLP (6) AAAI (5) AISTATS (5) ECCV (4) ACL (2) ICCV (2) IJCAI (2) COLT (1) CORL (1) NSDI (1) OSDI (1)

Top co-authors

Kimin Lee (26) Jongheon Jeong (19) Jihoon Tack (17) Jaehyung Kim (16) Sungsoo Ahn (15) Jaeho Lee (14) Younggyo Seo (14) Honglak Lee (14) Hankook Lee (13) Sung Ju Hwang (13)

Research topics

Optimization (1) Privacy (1) Core AI (1)

Keywords

self-supervised learning (15) representation learning (13) contrastive learning (10) knowledge distillation (8) graphical model (8) data augmentation (7) adversarial robustness (7) image classification (6) neural network (6) belief propagation (6) large language model (6) deep neural network (6) partition function (5) variational inference (5) diffusion model (5) feature learning (4) randomized smoothing (4) domain generalization (4) certified robustness (4) combinatorial optimization (3)

Papers

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
RΓ©nyiCL: Contrastive Representation Learning with Skew RΓ©nyi 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