Nathalie Baracaldo
8 papers · 2021–2025 · 6 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (20) 🐣 Hot Topic Early Bird 🏆 Grand Slam
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The Questioner
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Research topics
Machine Learning
(8)
Artificial Intelligence
(6)
Core AI
(5)
Deep Learning
(3)
Application Areas
(3)
Optimization & Theory
(3)
Natural Language Processing
(2)
Core Methods
(2)
Learning Paradigms · Machine Learning
(2)
Learning Types · Machine Learning
(2)
Models
(2)
Resources & Methods
(2)
Applications
(1)
Learning Paradigms · Artificial Intelligence
(1)
Learning Types · Deep Learning
(1)
Keywords
large language model
(2)
federated learning
(2)
machine unlearning
(2)
adversarial robustness
(1)
hyperparameter optimization
(1)
gradient-based optimization
(1)
feature selection
(1)
in-context learning
(1)
preference optimization
(1)
backdoor attack
(1)
model editing
(1)
gradient boosting
(1)
invariance
(1)
communication efficiency
(1)
probability calibration
(1)
knowledge editing
(1)
primal-dual method
(1)
data heterogeneity
(1)
parameter-efficient fine-tuning
(1)
convex optimization
(1)
Papers
Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning
ICML 2025
MAP: Multi-Human-Value Alignment Palette
ICLR 2025
Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills
EMNLP 2025
Enhancing In-context Learning via Linear Probe Calibration
AISTATS 2024
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
NeurIPS 2024
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning
ICML 2023
Single-shot General Hyper-parameter Optimization for Federated Learning
ICLR 2023
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning
AAAI 2021