Mengdi Huai
26 papers · 2018–2026 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (57) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
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Keyword Champion
(3)
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Renaissance Researcher
(8)
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Conference Pioneer
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Century Club Β· Bronze
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Keyword Collector
(118)
Top co-authors
Research topics
Machine Learning
(21)
Artificial Intelligence
(16)
Core AI
(16)
Application Areas
(10)
Learning Types Β· Machine Learning
(10)
Deep Learning
(7)
Optimization & Theory
(6)
Core Methods
(5)
Security & Privacy
(4)
Learning Types Β· Deep Learning
(4)
Architectures
(3)
Computer Vision
(2)
Differential Privacy
(2)
Models
(2)
Privacy
(2)
Keywords
conformal prediction
(4)
machine unlearning
(4)
uncertainty quantification
(4)
differential privacy
(3)
adversarial attack
(3)
adversarial robustness
(3)
neural network interpretability
(3)
pairwise learning
(3)
large language model
(2)
selective forgetting
(2)
shapley value
(2)
deep neural network
(2)
online learning
(1)
metric learning
(1)
false discovery rate
(1)
concept-based explanation
(1)
privacy attack
(1)
natural language processing
(1)
certified robustness
(1)
representation learning
(1)
Papers
Quantifying and Understanding Uncertainty in Large Reasoning Models
ACL 2026
Towards Benchmarking Privacy Vulnerabilities in Selective Forgetting with Large Language Models
AAAI 2026
Membership Inference Attacks with False Discovery Rate Control
ICCV 2025
Neuron Explanations for Conformal Prediction (Student Abstract)
AAAI 2025
Quantifying Uncertainty in Natural Language Explanations of Large Language Models for Question Answering
EMNLP 2025
AdvST: Revisiting Data Augmentations for Single Domain Generalization
AAAI 2024
Automated Natural Language Explanation of Deep Visual Neurons with Large Models (Student Abstract)
AAAI 2024
Backdoor Attacks via Machine Unlearning
AAAI 2024
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning
ICML 2024
Data Poisoning Attacks against Conformal Prediction
ICML 2024
Fostering Trustworthiness in Machine Learning Algorithms
AAAI 2024
Improving Interpretation Faithfulness for Vision Transformers
ICML 2024
Modeling and Understanding Uncertainty in Medical Image Classification
MICCAI 2024
Rethinking Adversarial Robustness in the Context of the Right to be Forgotten
ICML 2024
Towards Modeling Uncertainties of Self-Explaining Neural Networks via Conformal Prediction
AAAI 2024
SEAT: Stable and Explainable Attention
AAAI 2023
Static and Sequential Malicious Attacks in the Context of Selective Forgetting
NeurIPS 2023
Understanding and Enhancing Robustness of Concept-Based Models
AAAI 2023
Towards Automating Model Explanations with Certified Robustness Guarantees
AAAI 2022
Differentially Private Pairwise Learning Revisited
IJCAI 2021
EC-GAN: Inferring Brain Effective Connectivity via Generative Adversarial Networks
AAAI 2020
Pairwise Learning with Differential Privacy Guarantees
AAAI 2020
Towards Interpretation of Pairwise Learning
AAAI 2020
Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm
IJCAI 2019
Privacy-aware Synthesizing for Crowdsourced Data
IJCAI 2019
Representation Learning for Treatment Effect Estimation from Observational Data
NeurIPS 2018