Adam Block
20 papers · 2021–2026 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (35) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π Keyword Champion (6)
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(97)
π₯
Unstoppable Β· Bronze
β
The Questioner
(2)
β‘
Prolific Year Β· Productive
π
Renaissance Researcher
(5)
Venues
Top co-authors
Research topics
Machine Learning
(19)
Optimization & Theory Β· Machine Learning
(14)
Learning Types
(11)
Artificial Intelligence
(9)
Core AI
(8)
Mathematics & Optimization
(5)
Optimization
(4)
Deep Learning
(3)
Application Areas
(3)
Core Methods
(3)
Natural Language Processing
(2)
Mathematics
(2)
Optimization & Theory Β· Deep Learning
(2)
Resources & Methods
(2)
Reinforcement Learning
(1)
Keywords
smoothed online learning
(6)
online learning
(5)
sample complexity
(5)
behavior cloning
(3)
regret bound
(3)
imitation learning
(2)
error amplification
(2)
reward model
(2)
inference-time alignment
(2)
large language model
(2)
minimax regret
(2)
best-of-n sampling
(2)
optimization oracle
(2)
minimax optimality
(1)
adversarial learning
(1)
autoregressive generation
(1)
optimal transport
(1)
stochastic gradient descent
(1)
representation learning
(1)
interpretability
(1)
Papers
Partition Function Estimation under Bounded f-Divergence
COLT 2026
Revisiting the (Sub)Optimality of Best-of-N for Inference-Time Alignment
COLT 2026
A Theory of Learning with Autoregressive Chain of Thought
COLT 2025
Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification (extended abstract)
COLT 2025
GaussMark: A Practical Approach for Structural Watermarking of Language Models
ICML 2025
Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment
ICML 2025
Self-Improvement in Language Models: The Sharpening Mechanism
ICLR 2025
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression
ICLR 2024
Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning
NeurIPS 2024
On the Performance of Empirical Risk Minimization with Smoothed Data
COLT 2024
Oracle-Efficient Differentially Private Learning with Public Data
NeurIPS 2024
Efficient Model-Free Exploration in Low-Rank MDPs
NeurIPS 2023
Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making
COLT 2023
Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior
NeurIPS 2023
Smoothed Online Learning for Prediction in Piecewise Affine Systems
NeurIPS 2023
The Sample Complexity of Approximate Rejection Sampling With Applications to Smoothed Online Learning
COLT 2023
Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions
NeurIPS 2022
Intrinsic Dimension Estimation Using Wasserstein Distance
JMLR 2022
Smoothed Online Learning is as Easy as Statistical Learning
COLT 2022
Majorizing Measures, Sequential Complexities, and Online Learning
COLT 2021