Renzhe Xu
20 papers · 2021–2026 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (44) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Gold π Grand Slam
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Deep Specialist
(11)
π€
Dynamic Duo
(18)
ποΈ
Keyword Collector
(86)
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
π
Renaissance Researcher
(6)
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Trend Setter
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(18)
Application Areas
(14)
Learning Types Β· Machine Learning
(9)
Optimization & Theory
(9)
Artificial Intelligence
(7)
Core AI
(6)
Core Methods
(4)
Deep Learning
(3)
Mathematics & Optimization
(3)
Learning Types Β· Deep Learning
(3)
Optimization
(3)
Computer Vision
(2)
Natural Language Processing
(2)
Analysis
(2)
Learning Paradigms
(2)
Keywords
out-of-distribution generalization
(7)
domain generalization
(6)
distribution shift
(4)
stable learning
(3)
multi-armed bandit
(2)
domain adaptation
(2)
covariate-shift generalization
(2)
generalization bound
(2)
sample reweighting
(2)
in-context learning
(2)
covariate shift
(2)
causal inference
(2)
regret bound
(2)
sharpness-aware minimization
(1)
visual grounding
(1)
transformer
(1)
model pretraining
(1)
representation learning
(1)
empirical risk minimization
(1)
object detection
(1)
Papers
Error Slice Discovery via Manifold Compactness
AAAI 2026
Partial Fairness Awareness: Belief-Guided Strategic Mechanism for Strategic Agents
AAAI 2026
COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts
CVPR 2025
Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources
ICML 2025
On the Out-Of-Distribution Generalization of Large Multimodal Models
CVPR 2025
Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study
ICLR 2025
Rethinking the Evaluation Protocol of Domain Generalization
CVPR 2024
Competing for Shareable Arms in Multi-Player Multi-Armed Bandits
ICML 2023
Covariate-Shift Generalization via Random Sample Weighting
AAAI 2023
Factual Observation Based Heterogeneity Learning for Counterfactual Prediction
CLeaR 2023
Flatness-Aware Minimization for Domain Generalization
ICCV 2023
Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization
CVPR 2023
Measure the Predictive Heterogeneity
ICLR 2023
NICO++: Towards Better Benchmarking for Domain Generalization
CVPR 2023
Stable Learning via Sparse Variable Independence
AAAI 2023
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization
ICML 2022
Model Agnostic Sample Reweighting for Out-of-Distribution Learning
ICML 2022
Product Ranking for Revenue Maximization with Multiple Purchases
NeurIPS 2022
Towards Unsupervised Domain Generalization
CVPR 2022
Deep Stable Learning for Out-of-Distribution Generalization
CVPR 2021