Long-Kai Huang
26 papers · 2013–2025 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (40) π Conference Polyglot Β· Silver π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Triple Crown
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Grand Slam
π€
Dynamic Duo
(11)
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Conference Pioneer
β‘
Prolific Year Β· Productive
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Century Club Β· Bronze
ποΈ
Keyword Collector
(105)
π₯
Unstoppable Β· Bronze
Top co-authors
Research topics
Machine Learning
(23)
Artificial Intelligence
(14)
Application Areas
(10)
Learning Paradigms Β· Artificial Intelligence
(9)
Learning Types Β· Machine Learning
(9)
Deep Learning
(7)
Optimization & Theory
(7)
Core AI
(6)
Core Methods
(6)
Learning Types Β· Deep Learning
(4)
Architectures
(3)
Learning Paradigms Β· Machine Learning
(3)
Natural Language Processing
(2)
Techniques
(2)
Mathematics & Optimization
(1)
Keywords
transfer learning
(4)
domain generalization
(4)
few-shot learning
(3)
continual learning
(3)
knowledge transfer
(2)
riemannian optimization
(2)
feature representation
(2)
task augmentation
(2)
foundation model
(2)
mutual information
(2)
drug discovery
(2)
graph neural network
(2)
optimal transport
(2)
information bottleneck
(1)
principal component analysis
(1)
adversarial learning
(1)
domain adaptation
(1)
catastrophic forgetting
(1)
time series analysis
(1)
model unlearning
(1)
Papers
Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation
ICLR 2025
IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck
ICML 2025
Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization
ICLR 2025
SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning
ICLR 2025
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model
AAAI 2025
Steering Protein Language Models
ICML 2025
Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time
ICLR 2024
Learning Where to Edit Vision Transformers
NeurIPS 2024
Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction
ICLR 2024
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization
ICML 2024
Towards Understanding Evolving Patterns in Sequential Data
NeurIPS 2024
Concept-wise Fine-tuning Matters in Preventing Negative Transfer
ICCV 2023
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery β a Focus on Affinity Prediction Problems with Noise Annotations
AAAI 2023
Retaining Beneficial Information from Detrimental Data for Neural Network Repair
NeurIPS 2023
Secure Out-of-Distribution Task Generalization with Energy-Based Models
NeurIPS 2023
Adversarial Task Up-sampling for Meta-learning
NeurIPS 2022
Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport
IJCAI 2022
Frustratingly Easy Transferability Estimation
ICML 2022
Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization
NeurIPS 2022
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery
NeurIPS 2021
Improving Generalization in Meta-learning via Task Augmentation
ICML 2021
Communication-Efficient Distributed PCA by Riemannian Optimization
ICML 2020
Accelerate Learning of Deep Hashing With Gradient Attention
ICCV 2019
Class-Wise Supervised Hashing with Label Embedding and Active Bits
IJCAI 2016
Online Hashing
IJCAI 2013
Smart Hashing Update for Fast Response
IJCAI 2013