Eunho Yang
97 papers · 2011–2026 · 16 conferences · across top CS/AI conferences
Achievements
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Conferences
ICLR (22)
NIPS (21)
ICML (17)
AAAI (6)
CVPR (5)
EMNLP (5)
AISTATS (4)
ICCV (3)
INTERSPEECH (3)
EACL (2)
ECCV (2)
IJCAI (2)
NAACL (2)
ACL (1)
JMLR (1)
WACV (1)
Top co-authors
Keywords
graph neural network
(6)
graphical model
(6)
multi-task learning
(5)
neural network
(5)
uncertainty quantification
(4)
exponential family
(4)
contrastive learning
(4)
negative transfer
(3)
knowledge distillation
(3)
statistical guarantee
(3)
convex optimization
(3)
model compression
(3)
data augmentation
(3)
influence function
(3)
diffusion model
(3)
representation learning
(3)
non-convex optimization
(3)
high-dimensional statistics
(3)
attention mechanism
(3)
exponential families
(3)
Papers
LLM Plug-ins Are Not a Free Lunch for Clinical Time-Series Prediction
EACL 2026
Evaluating the Pre-Consultation Ability of LLMs using Diagnostic Guidelines
EACL 2026
Bringing Real-World Relations into Video Generation with Graph-Structured Knowledge
ACL 2026
Towards Reliable Test-Time Adaptation: Style Invariance as a Correctness Likelihood
WACV 2026
REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring
ICLR 2025
Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
ICLR 2025
Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning
ICLR 2025
Token-Supervised Value Models for Enhancing Mathematical Problem-Solving Capabilities of Large Language Models
ICLR 2025
LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding
ICLR 2025
Towards Precise Prediction Uncertainty in GNNs: Refining GNNs with Topology-grouping Strategy
AAAI 2025
Preserve or Modify? Context-Aware Evaluation for Balancing Preservation and Modification in Text-Guided Image Editing
CVPR 2025
LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices
NAACL 2025
TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation
ICML 2025
Early Timestep Zero-Shot Candidate Selection for Instruction-Guided Image Editing
ICCV 2025
Taxonomy of Comprehensive Safety for Clinical Agents
EMNLP 2025
Format Inertia: A Failure Mechanism of LLMs in Medical Pre-Consultation
EMNLP 2025
Unveiling the Response of Large Vision-Language Models to Visually Absent Tokens
EMNLP 2025
Playing the Fool: Jailbreaking LLMs and Multimodal LLMs with Out-of-Distribution Strategy
CVPR 2025
PruNeRF: Segment-Centric Dataset Pruning via 3D Spatial Consistency
ICML 2024
Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images
CVPR 2024
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective
NIPS 2024
TEDDY: Trimming Edges with Degree-based Discrimination Strategy
ICLR 2024
Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication
ICLR 2024
CloudFixer: Test-Time Adaptation for 3D Point Clouds via Diffusion-Guided Geometric Transformation
ECCV 2024
PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning
EMNLP 2024
TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
ECCV 2024
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
ICLR 2023
GEX: A flexible method for approximating influence via Geometric Ensemble
NIPS 2023
Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds
NIPS 2023
Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding
CVPR 2023
BiasAdv: Bias-Adversarial Augmentation for Model Debiasing
CVPR 2023
PC-Adapter: Topology-Aware Adapter for Efficient Domain Adaption on Point Clouds with Rectified Pseudo-label
ICCV 2023
Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance
ICLR 2023
Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation
ICML 2023
RGE: A Repulsive Graph Rectification for Node Classification via Influence
ICML 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
Set Based Stochastic Subsampling
ICML 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
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
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation
AAAI 2022
AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning
AISTATS 2022
TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification
ICML 2022
Distilling Linguistic Context for Language Model Compression
EMNLP 2021
Learning to Sample with Local and Global Contexts in Experience Replay Buffer
ICLR 2021
FedMix: Approximation of Mixup under Mean Augmented Federated Learning
ICLR 2021
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning
ICLR 2021
GTA: Graph Truncated Attention for Retrosynthesis
AAAI 2021
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning
AAAI 2021
RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning
IJCAI 2021
Multi-Domain Knowledge Distillation via Uncertainty-Matching for End-to-End ASR Models
INTERSPEECH 2021
Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
ICML 2021
Federated Continual Learning with Weighted Inter-client Transfer
ICML 2021
Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning
NIPS 2021
Adaptive Proximal Gradient Methods for Structured Neural Networks
NIPS 2021
Cluster-Promoting Quantization With Bit-Drop for Minimizing Network Quantization Loss
ICCV 2021
Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks
ICLR 2020
Meta Dropout: Learning to Perturb Latent Features for Generalization
ICLR 2020
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks
ICLR 2020
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
ICLR 2020
Neural Complexity Measures
NIPS 2020
Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning
NIPS 2020
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning
NIPS 2020
Bootstrapping neural processes
NIPS 2020
Attribution Preservation in Network Compression for Reliable Network Interpretation
NIPS 2020
Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare
AAAI 2020
Time-Reversal Symmetric ODE Network
NIPS 2020
Cost-Effective Interactive Attention Learning with Neural Attention Processes
ICML 2020
Spectral Approximate Inference
ICML 2019
LEARNING TO PROPAGATE LABELS: TRANSDUCTIVE PROPAGATION NETWORK FOR FEW-SHOT LEARNING
ICLR 2019
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning
ICML 2019
DropMax: Adaptive Variational Softmax
NIPS 2018
Lifelong Learning with Dynamically Expandable Networks
ICLR 2018
Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding
NIPS 2018
Deep Asymmetric Multi-task Feature Learning
ICML 2018
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
NIPS 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
NIPS 2015
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso
NIPS 2015
Graphical Models via Univariate Exponential Family Distributions
JMLR 2015
Elementary Estimators for Graphical Models
NIPS 2014
Elementary Estimators for Sparse Covariance Matrices and other Structured Moments
ICML 2014
Mixed Graphical Models via Exponential Families
AISTATS 2014
Elementary Estimators for High-Dimensional Linear Regression
ICML 2014
On Poisson Graphical Models
NIPS 2013
Conditional Random Fields via Univariate Exponential Families
NIPS 2013
On Robust Estimation of High Dimensional Generalized Linear Models
IJCAI 2013
Dirty Statistical Models
NIPS 2013
Perturbation based Large Margin Approach for Ranking
AISTATS 2012
Graphical Models via Generalized Linear Models
NIPS 2012
On NDCG Consistency of Listwise Ranking Methods
AISTATS 2011