Jean-Francois Ton
20 papers · 2019–2025 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (47) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Research topics
Machine Learning
(17)
Optimization & Theory
(14)
Artificial Intelligence
(12)
Core AI
(9)
Learning Paradigms
(5)
Deep Learning
(4)
Natural Language Processing
(4)
Core Methods
(4)
Reinforcement Learning
(3)
Generation
(3)
Methods
(3)
Mathematics & Optimization
(2)
Application Areas
(2)
Learning Types
(2)
Optimization
(2)
Keywords
uncertainty quantification
(3)
large language model
(3)
causal inference
(2)
leverage score
(2)
off-policy evaluation
(2)
ridge regression
(2)
average treatment effect
(2)
contextual bandit
(2)
kernel methods
(2)
random fourier feature
(2)
bayesian inference
(2)
kernel mean embedding
(2)
reward modeling
(2)
preference learning
(1)
epistemic uncertainty
(1)
variational inference
(1)
out-of-distribution generalization
(1)
binary classification
(1)
reinforcement learning
(1)
language model alignment
(1)
Papers
ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration
ICLR 2025
Active Reward Modeling: Adaptive Preference Labeling for Large Language Model Alignment
ICML 2025
Rethinking Reward Modeling in Preference-based Large Language Model Alignment
ICLR 2025
Understanding Chain-of-Thought in LLMs through Information Theory
ICML 2025
Achievable Fairness on Your Data With Utility Guarantees
NeurIPS 2024
Fair Classifiers that Abstain without Harm
ICLR 2024
Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation
NeurIPS 2024
Invariant Learning via Probability of Sufficient and Necessary Causes
NeurIPS 2023
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits
NeurIPS 2023
Conformal Off-Policy Prediction in Contextual Bandits
NeurIPS 2022
Grassmann Stein Variational Gradient Descent
AISTATS 2022
Regularized Training of Nearest Neighbor Language Models
NAACL 2022
BayesIMP: Uncertainty Quantification for Causal Data Fusion
NeurIPS 2021
Meta Learning for Causal Direction
AAAI 2021
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings
AISTATS 2021
Robust Pruning at Initialization
ICLR 2021
Towards a Unified Analysis of Random Fourier Features
JMLR 2021
MetaFun: Meta-Learning with Iterative Functional Updates
ICML 2020
Automated Model Selection with Bayesian Quadrature
ICML 2019
Towards a Unified Analysis of Random Fourier Features
ICML 2019