Nino Vieillard
15 papers · 2020–2025 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (30) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Dynamic Duo
(11)
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Grand Slam
π₯
Mega-Team Β· Squad
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Triple Crown
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Keyword Champion
(2)
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Unstoppable Β· Bronze
ποΈ
Keyword Collector
(71)
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(15)
Reinforcement Learning
(11)
Methods
(11)
Optimization & Theory
(8)
Deep Learning
(7)
Artificial Intelligence
(6)
Core AI
(6)
Learning Types Β· Machine Learning
(6)
Learning Types Β· Deep Learning
(5)
Natural Language Processing
(4)
Application Areas
(3)
Architectures
(2)
Generation
(2)
Resources & Methods
(2)
Applications
(1)
Keywords
reinforcement learning
(5)
reinforcement learning from human feedback
(3)
value iteration
(3)
deep reinforcement learning
(2)
offline reinforcement learning
(2)
temporal difference
(2)
language model
(2)
off-policy learning
(2)
large language model
(2)
policy regularization
(2)
knowledge distillation
(2)
inverse reinforcement learning
(1)
imitation learning
(1)
policy learning
(1)
minimax optimality
(1)
sequence generation
(1)
sample complexity
(1)
approximate dynamic programming
(1)
kl divergence
(1)
policy iteration
(1)
Papers
BOND: Aligning LLMs with Best-of-N Distillation
ICLR 2025
Loss Functions and Operators Generated by f-Divergences
ICML 2025
On Teacher Hacking in Language Model Distillation
ICML 2025
Imitating Language via Scalable Inverse Reinforcement Learning
NeurIPS 2024
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
ICLR 2024
WARM: On the Benefits of Weight Averaged Reward Models
ICML 2024
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
ACL 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
ICML 2023
Implicitly Regularized RL with Implicit Q-values
AISTATS 2022
Offline Reinforcement Learning as Anti-exploration
AAAI 2022
Offline Reinforcement Learning with Pseudometric Learning
ICML 2021
Deep Conservative Policy Iteration
AAAI 2020
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning
NeurIPS 2020
Momentum in Reinforcement Learning
AISTATS 2020
Munchausen Reinforcement Learning
NeurIPS 2020