Se-Young Yun
68 papers · 2014–2026 · 15 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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(11)
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Venues
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Research topics
Machine Learning
(61)
Learning Types Β· Machine Learning
(35)
Artificial Intelligence
(27)
Deep Learning
(24)
Optimization & Theory
(21)
Application Areas
(19)
Core Methods
(18)
Core AI
(17)
Mathematics & Optimization
(12)
Natural Language Processing
(12)
Learning Types Β· Deep Learning
(12)
Learning Paradigms
(10)
Optimization
(10)
Architectures
(9)
Data Science & Analytics
(7)
Keywords
regret bound
(7)
knowledge distillation
(6)
model compression
(5)
noisy label
(4)
continual learning
(4)
federated learning
(4)
multi-armed bandit
(4)
community detection
(4)
transfer learning
(4)
large language model
(3)
online learning
(3)
streaming algorithm
(3)
domain adaptation
(3)
data heterogeneity
(3)
representation learning
(3)
stochastic block model
(3)
language model
(3)
data augmentation
(2)
sample complexity
(2)
contrastive learning
(2)
Papers
MERIT Feedback Elicits Better Bargaining in LLM Negotiators
ACL 2026
Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models
ICLR 2025
C2: Scalable Auto-Feedback for LLM-based Chart Generation
NAACL 2025
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs
ICML 2025
FlickerFusion: Intra-trajectory Domain Generalizing Multi-agent Reinforcement Learning
ICLR 2025
MA$^2$E: Addressing Partial Observability in Multi-Agent Reinforcement Learning with Masked Auto-Encoder
ICLR 2025
MAVFlow: Preserving Paralinguistic Elements with Conditional Flow Matching for Zero-Shot AV2AV Multilingual Translation
ICCV 2025
MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition
ICML 2025
Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation
ICLR 2025
QuRe: Query-Relevant Retrieval through Hard Negative Sampling in Composed Image Retrieval
ICML 2025
Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model
ICML 2025
Self-Training Elicits Concise Reasoning in Large Language Models
ACL 2025
An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints
NeurIPS 2024
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
NeurIPS 2024
BAPO: Base-Anchored Preference Optimization for Overcoming Forgetting in Large Language Models Personalization
EMNLP 2024
Block Transformer: Global-to-Local Language Modeling for Fast Inference
NeurIPS 2024
Carpe diem: On the Evaluation of World Knowledge in Lifelong Language Models
NAACL 2024
Conditional Synthesis of 3D Molecules with Time Correction Sampler
NeurIPS 2024
DistiLLM: Towards Streamlined Distillation for Large Language Models
ICML 2024
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning
CVPR 2024
Fine-tuning Pre-trained Models for Robustness under Noisy Labels
IJCAI 2024
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
AISTATS 2024
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
ICLR 2024
Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning
AAAI 2024
Preference Alignment with Flow Matching
NeurIPS 2024
Stable Language Model Pre-training by Reducing Embedding Variability
EMNLP 2024
Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs
ICML 2024
Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language Models
EMNLP 2024
Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters
EMNLP 2024
A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise
AAAI 2023
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning
EMNLP 2023
Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles
AISTATS 2023
Coreset Sampling From Open-Set for Fine-Grained Self-Supervised Learning
CVPR 2023
CUDA: Curriculum of Data Augmentation for Long-tailed Recognition
ICLR 2023
Denoising after Entropy-Based Debiasing a Robust Training Method for Dataset Bias with Noisy Labels
AAAI 2023
Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint
NeurIPS 2023
Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding
EMNLP 2023
HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning
EMNLP 2023
Large Language Models Are Reasoning Teachers
ACL 2023
Mitigating Dataset Bias by Using Per-Sample Gradient
ICLR 2023
NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models
EMNLP 2023
Nearly Optimal Latent State Decoding in Block MDPs
AISTATS 2023
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification
Interspeech 2023
PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning
NeurIPS 2023
Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation
Interspeech 2023
Re-Thinking Federated Active Learning Based on Inter-Class Diversity
CVPR 2023
Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective
EACL 2023
Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network
AAAI 2023
FedBABU: Toward Enhanced Representation for Federated Image Classification
ICLR 2022
Neural Processes with Stochastic Attention: Paying more attention to the context dataset
ICLR 2022
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning
NeurIPS 2022
Robust Streaming PCA
NeurIPS 2022
Rotting Infinitely Many-Armed Bandits
ICML 2022
Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks
EMNLP 2022
Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty
NeurIPS 2022
BOIL: Towards Representation Change for Few-shot Learning
ICLR 2021
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation
IJCAI 2021
FINE Samples for Learning with Noisy Labels
NeurIPS 2021
Improved Regret Bounds of Bilinear Bandits using Action Space Analysis
ICML 2021
Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models
AISTATS 2020
Regret in Online Recommendation Systems
NeurIPS 2020
Optimal Sampling and Clustering in the Stochastic Block Model
NeurIPS 2019
Spectral Approximate Inference
ICML 2019
Collaborative Clustering: Sample Complexity and Efficient Algorithms
ALT 2017
Optimal Cluster Recovery in the Labeled Stochastic Block Model
NeurIPS 2016
Fast and Memory Optimal Low-Rank Matrix Approximation
NeurIPS 2015
Community Detection via Random and Adaptive Sampling
COLT 2014
Streaming, Memory Limited Algorithms for Community Detection
NeurIPS 2014