Cyril Zhang
26 papers · 2017–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (8) π Conference Polyglot (6) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (7)
π
Cross-Pollinator
(7)
π
Renaissance Researcher
(6)
πΊοΈ
Taxonomy Completionist
(50)
π
Keyword Champion
(2)
π
Triple Crown
β‘
Prolific Year
(6)
π
Conference Pioneer
ποΈ
Keyword Collector
(100)
π
Century Club
(26)
β
The Questioner
π
Trend Setter
π₯
Unstoppable
(9)
Conferences
ICML (8)
NIPS (8)
ICLR (6)
COLT (2)
ALT (1)
EMNLP (1)
Top co-authors
Research topics
Keywords
linear dynamical system
(4)
inductive bia
(3)
online learning
(2)
regret bound
(2)
sample complexity
(2)
convex optimization
(2)
stochastic gradient descent
(2)
spectral filtering
(2)
autoregressive filter
(2)
large language model
(2)
computational complexity
(2)
reinforcement learning
(1)
non-convex optimization
(1)
decision making
(1)
contrastive learning
(1)
representation learning
(1)
neural network training
(1)
parallel corpus
(1)
feature learning
(1)
lottery ticket hypothesis
(1)
Papers
On the Query Complexity of Verifier-Assisted Language Generation
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
Can large language models explore in-context?
NIPS 2024
ASL STEM Wiki: Dataset and Benchmark for Interpreting STEM Articles
EMNLP 2024
Exposing Attention Glitches with Flip-Flop Language Modeling
NIPS 2023
Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck
NIPS 2023
Learning Hidden Markov Models Using Conditional Samples
COLT 2023
Transformers Learn Shortcuts to Automata
ICLR 2023
Understanding Contrastive Learning Requires Incorporating Inductive Biases
ICML 2022
Inductive Biases and Variable Creation in Self-Attention Mechanisms
ICML 2022
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit
NIPS 2022
Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms
NIPS 2022
Sparsity in Partially Controllable Linear Systems
ICML 2022
Anti-Concentrated Confidence Bonuses For Scalable Exploration
ICLR 2022
Acceleration via Fractal Learning Rate Schedules
ICML 2021
Extreme Tensoring for Low-Memory Preconditioning
ICLR 2020
Stochastic Optimization with Laggard Data Pipelines
NIPS 2020
Robust guarantees for learning an autoregressive filter
ALT 2020
No-Regret Prediction in Marginally Stable Systems
COLT 2020
Calibration, Entropy Rates, and Memory in Language Models
ICML 2020
Efficient Full-Matrix Adaptive Regularization
ICML 2019
Not-So-Random Features
ICLR 2018
Spectral Filtering for General Linear Dynamical Systems
NIPS 2018
Efficient Regret Minimization in Non-Convex Games
ICML 2017
Learning Linear Dynamical Systems via Spectral Filtering
NIPS 2017