Eunho Yang

Bringing Real-World Relations into Video Generation with Graph-Structured Knowledge ACL 2026 Evaluating the Pre-Consultation Ability of LLMs using Diagnostic Guidelines EACL 2026 Instruction-Guided Lesion Segmentation for Chest X-rays with Automatically Generated Large-Scale Dataset CVPR 2026 LLM Plug-ins Are Not a Free Lunch for Clinical Time-Series Prediction EACL 2026 Progress by Pieces: Test-Time Scaling for Autoregressive Image Generation CVPR 2026 Towards Reliable Test-Time Adaptation: Style Invariance as a Correctness Likelihood WACV 2026 Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning ICLR 2025 Early Timestep Zero-Shot Candidate Selection for Instruction-Guided Image Editing ICCV 2025 Format Inertia: A Failure Mechanism of LLMs in Medical Pre-Consultation EMNLP 2025 LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding ICLR 2025 LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices NAACL 2025 Playing the Fool: Jailbreaking LLMs and Multimodal LLMs with Out-of-Distribution Strategy CVPR 2025 Preserve or Modify? Context-Aware Evaluation for Balancing Preservation and Modification in Text-Guided Image Editing CVPR 2025 REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring ICLR 2025 Taxonomy of Comprehensive Safety for Clinical Agents EMNLP 2025 Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation ICLR 2025 TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation ICML 2025 Token-Supervised Value Models for Enhancing Mathematical Problem-Solving Capabilities of Large Language Models ICLR 2025 Towards Precise Prediction Uncertainty in GNNs: Refining GNNs with Topology-grouping Strategy AAAI 2025 Unveiling the Response of Large Vision-Language Models to Visually Absent Tokens EMNLP 2025 A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective NeurIPS 2024 CloudFixer: Test-Time Adaptation for 3D Point Clouds via Diffusion-Guided Geometric Transformation ECCV 2024 Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images CVPR 2024 Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication ICLR 2024 PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning EMNLP 2024 PruNeRF: Segment-Centric Dataset Pruning via 3D Spatial Consistency ICML 2024 TEDDY: Trimming Edges with Degree-based Discrimination Strategy ICLR 2024 TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias ECCV 2024 BiasAdv: Bias-Adversarial Augmentation for Model Debiasing CVPR 2023 Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding CVPR 2023 Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation ICML 2023 GEX: A flexible method for approximating influence via Geometric Ensemble NeurIPS 2023 Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance ICLR 2023 PC-Adapter: Topology-Aware Adapter for Efficient Domain Adaption on Point Clouds with Rectified Pseudo-label ICCV 2023 RGE: A Repulsive Graph Rectification for Node Classification via Influence ICML 2023 Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds NeurIPS 2023 Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel ICLR 2023 SGEM: Test-Time Adaptation for Automatic Speech Recognition via Sequential-Level Generalized Entropy Minimization Interspeech 2023 ZET-Speech: Zero-shot adaptive Emotion-controllable Text-to-Speech Synthesis with Diffusion and Style-based Models Interspeech 2023 AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning AISTATS 2022 Does it Really Generalize Well on Unseen Data? Systematic Evaluation of Relational Triple Extraction Methods NAACL 2022 GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification ICLR 2022 Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation AAAI 2022 Model-augmented Prioritized Experience Replay ICLR 2022 Online Coreset Selection for Rehearsal-based Continual Learning ICLR 2022 Online Hyperparameter Meta-Learning with Hypergradient Distillation ICLR 2022 Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing AAAI 2022 Set Based Stochastic Subsampling ICML 2022 TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification ICML 2022 Adaptive Proximal Gradient Methods for Structured Neural Networks NeurIPS 2021 Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning AAAI 2021 Cluster-Promoting Quantization With Bit-Drop for Minimizing Network Quantization Loss ICCV 2021 Distilling Linguistic Context for Language Model Compression EMNLP 2021 Federated Continual Learning with Weighted Inter-client Transfer ICML 2021 Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning ICLR 2021 FedMix: Approximation of Mixup under Mean Augmented Federated Learning ICLR 2021 GTA: Graph Truncated Attention for Retrosynthesis AAAI 2021 Learning to Sample with Local and Global Contexts in Experience Replay Buffer ICLR 2021 Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation ICML 2021 Multi-Domain Knowledge Distillation via Uncertainty-Matching for End-to-End ASR Models Interspeech 2021 RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning IJCAI 2021 Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning NeurIPS 2021 Attribution Preservation in Network Compression for Reliable Network Interpretation NeurIPS 2020 Bootstrapping neural processes NeurIPS 2020 Cost-Effective Interactive Attention Learning with Neural Attention Processes ICML 2020 Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare AAAI 2020 Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning NeurIPS 2020 Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning NeurIPS 2020 Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks ICLR 2020 Meta Dropout: Learning to Perturb Latent Features for Generalization ICLR 2020 Neural Complexity Measures NeurIPS 2020 Scalable and Order-robust Continual Learning with Additive Parameter Decomposition ICLR 2020 Time-Reversal Symmetric ODE Network NeurIPS 2020 Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks ICLR 2020 LEARNING TO PROPAGATE LABELS: TRANSDUCTIVE PROPAGATION NETWORK FOR FEW-SHOT LEARNING ICLR 2019 Spectral Approximate Inference ICML 2019 Trimming the ℓ_1 Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning ICML 2019 Deep Asymmetric Multi-task Feature Learning ICML 2018 DropMax: Adaptive Variational Softmax NeurIPS 2018 Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding NeurIPS 2018 Lifelong Learning with Dynamically Expandable Networks ICLR 2018 Uncertainty-Aware Attention for Reliable Interpretation and Prediction NeurIPS 2018 Ordinal Graphical Models: A Tale of Two Approaches ICML 2017 Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity ICML 2017 Asymmetric Multi-task Learning Based on Task Relatedness and Loss ICML 2016 Closed-form Estimators for High-dimensional Generalized Linear Models NeurIPS 2015 Graphical Models via Univariate Exponential Family Distributions JMLR 2015 Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso NeurIPS 2015 Elementary Estimators for Graphical Models NeurIPS 2014 Elementary Estimators for High-Dimensional Linear Regression ICML 2014 Elementary Estimators for Sparse Covariance Matrices and other Structured Moments ICML 2014 Mixed Graphical Models via Exponential Families AISTATS 2014 Conditional Random Fields via Univariate Exponential Families NeurIPS 2013 Dirty Statistical Models NeurIPS 2013 On Poisson Graphical Models NeurIPS 2013 On Robust Estimation of High Dimensional Generalized Linear Models IJCAI 2013 Graphical Models via Generalized Linear Models NeurIPS 2012 Perturbation based Large Margin Approach for Ranking AISTATS 2012 On NDCG Consistency of Listwise Ranking Methods AISTATS 2011