Cyril Zhang - RankMe

64 papers A* 23A 1B 1Journal 34Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes. CoRR Adam Block, Cyril Zhang
2025	—	`conf`	EyeO: Autocalibrating Gaze Output with Gaze Input for Gaze Typing. CHI Extended Abstracts Akanksha Saran, Jacob Alber, Cyril Zhang, Ann Paradiso, Danielle Bragg, John Langford
2025	A*	`conf`	On the Query Complexity of Verifier-Assisted Language Generation. ICML Edoardo Botta, Yuchen Li, Aashay Mehta, Jordan T. Ash, Cyril Zhang, Andrej Risteski
2025	J	`jnl`	On the Query Complexity of Verifier-Assisted Language Generation. CoRR Edoardo Botta, Yuchen Li, Aashay Mehta, Jordan T. Ash, Cyril Zhang, Andrej Risteski
2025	A*	`conf`	Self-Improvement in Language Models: The Sharpening Mechanism. ICLR Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy
2024	A*	`conf`	ASL STEM Wiki: Dataset and Benchmark for Interpreting STEM Articles. EMNLP Kayo Yin, Chinmay Singh, Fyodor Minakov, Vanessa Milan, Hal Daumé III, Cyril Zhang, Alex Lu, Danielle Bragg
2024	J	`jnl`	ASL STEM Wiki: Dataset and Benchmark for Interpreting STEM Articles. CoRR Kayo Yin, Chinmay Singh, Fyodor O. Minakov, Vanessa Milan, Hal Daumé III, Cyril Zhang, Alex X. Lu, Danielle Bragg
2024	A*	`conf`	Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression. ICLR Adam Block, Dylan J. Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang
2024	A*	`conf`	Can large language models explore in-context? NeurIPS Akshay Krishnamurthy, Keegan Harris, Dylan J. Foster, Cyril Zhang, Aleksandrs Slivkins
2024	J	`jnl`	Can large language models explore in-context? CoRR Akshay Krishnamurthy, Keegan Harris, Dylan J. Foster, Cyril Zhang, Aleksandrs Slivkins
2024	J	`jnl`	Phi-4 Technical Report. CoRR Marah I Abdin, Jyoti Aneja, Harkirat S. Behl, Sébastien Bubeck, Ronen Eldan, Suriya Gunasekar, Michael Harrison, Russell J. Hewett, Mojan Javaheripi, Piero Kauffmann, James R. Lee, Yin Tat Lee, Yuanzhi Li, Weishung Liu, Caio C. T. Mendes, Anh Nguyen, Eric Price, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Xin Wang, Rachel Ward, Yue Wu, Dingli Yu, Cyril Zhang, Yi Zhang
2024	J	`jnl`	Self-Improvement in Language Models: The Sharpening Mechanism. CoRR Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy
2023	J	`jnl`	Autocalibrating Gaze Tracking: A Demonstration through Gaze Typing. CoRR Akanksha Saran, Jacob Alber, Danielle Bragg, Cyril Zhang, John Langford
2023	J	`jnl`	Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression. CoRR Adam Block, Dylan J. Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang
2023	A*	`conf`	Exposing Attention Glitches with Flip-Flop Language Modeling. NeurIPS Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
2023	J	`jnl`	Exposing Attention Glitches with Flip-Flop Language Modeling. CoRR Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
2023	A*	`conf`	Learning Hidden Markov Models Using Conditional Samples. COLT Gaurav Mahajan, Sham M. Kakade, Akshay Krishnamurthy, Cyril Zhang
2023	J	`jnl`	Learning Hidden Markov Models Using Conditional Samples. CoRR Sham M. Kakade, Akshay Krishnamurthy, Gaurav Mahajan, Cyril Zhang
2023	A*	`conf`	Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck. NeurIPS Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
2023	J	`jnl`	Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck. CoRR Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
2023	A*	`conf`	Transformers Learn Shortcuts to Automata. ICLR Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
2023	A	`conf`	Understanding and Improving Neural Active Learning on Heteroskedastic Distributions. ECAI Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb
2022	A*	`conf`	Anti-Concentrated Confidence Bonuses For Scalable Exploration. ICLR Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
2022	A*	`conf`	Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit. NeurIPS Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
2022	J	`jnl`	Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit. CoRR Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang
2022	A*	`conf`	Inductive Biases and Variable Creation in Self-Attention Mechanisms. ICML Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Cyril Zhang
2022	J	`jnl`	Neural Active Learning on Heteroskedastic Distributions. CoRR Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb
2022	A*	`conf`	Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. NeurIPS Surbhi Goel, Sham M. Kakade, Adam Kalai, Cyril Zhang
2022	J	`jnl`	Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. CoRR Surbhi Goel, Sham M. Kakade, Adam Tauman Kalai, Cyril Zhang
2022	A*	`conf`	Sparsity in Partially Controllable Linear Systems. ICML Yonathan Efroni, Sham M. Kakade, Akshay Krishnamurthy, Cyril Zhang
2022	J	`jnl`	Transformers Learn Shortcuts to Automata. CoRR Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
2022	A*	`conf`	Understanding Contrastive Learning Requires Incorporating Inductive Biases. ICML Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy
2022	J	`jnl`	Understanding Contrastive Learning Requires Incorporating Inductive Biases. CoRR Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy
2021	A*	`conf`	Acceleration via Fractal Learning Rate Schedules. ICML Naman Agarwal, Surbhi Goel, Cyril Zhang
2021	J	`jnl`	Acceleration via Fractal Learning Rate Schedules. CoRR Naman Agarwal, Surbhi Goel, Cyril Zhang
2021	J	`jnl`	Anti-Concentrated Confidence Bonuses for Scalable Exploration. CoRR Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
2021	J	`jnl`	Deluca - A Differentiable Control Library: Environments, Methods, and Benchmarking. CoRR Paula Gradu, John Hallman, Daniel Suo, Alex Yu, Naman Agarwal, Udaya Ghai, Karan Singh, Cyril Zhang, Anirudha Majumdar, Elad Hazan
2021	J	`jnl`	Inductive Biases and Variable Creation in Self-Attention Mechanisms. CoRR Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Cyril Zhang
2021	J	`jnl`	Machine Learning for Mechanical Ventilation Control (Extended Abstract). CoRR Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel J. Cohen, Elad Hazan
2021	J	`jnl`	Machine Learning for Mechanical Ventilation Control. CoRR Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel J. Cohen, Elad Hazan
2021	J	`jnl`	Sparsity in Partially Controllable Linear Systems. CoRR Yonathan Efroni, Sham M. Kakade, Akshay Krishnamurthy, Cyril Zhang
2020	A*	`conf`	Calibration, Entropy Rates, and Memory in Language Models. ICML Mark Braverman, Xinyi Chen, Sham M. Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang
2020	J	`jnl`	Disentangling Adaptive Gradient Methods from Learning Rates. CoRR Naman Agarwal, Rohan Anil, Elad Hazan, Tomer Koren, Cyril Zhang
2020	A*	`conf`	Extreme Tensoring for Low-Memory Preconditioning. ICLR Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang
2020	A*	`conf`	No-Regret Prediction in Marginally Stable Systems. COLT Udaya Ghai, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang
2020	J	`jnl`	No-Regret Prediction in Marginally Stable Systems. CoRR Udaya Ghai, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang
2020	—	`—`	Regret-Minimizing Algorithms Beyond Classical Optimization and Control Cyril Zhang
2020	B	`conf`	Robust guarantees for learning an autoregressive filter. ALT Holden Lee, Cyril Zhang
2020	A*	`conf`	Stochastic Optimization with Laggard Data Pipelines. NeurIPS Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang
2020	J	`jnl`	Stochastic Optimization with Laggard Data Pipelines. CoRR Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang
2019	J	`jnl`	Calibration, Entropy Rates, and Memory in Language Models. CoRR Mark Braverman, Xinyi Chen, Sham M. Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang
2019	A*	`conf`	Efficient Full-Matrix Adaptive Regularization. ICML Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang
2019	J	`jnl`	Extreme Tensoring for Low-Memory Preconditioning. CoRR Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang
2019	J	`jnl`	Robust guarantees for learning an autoregressive filter. CoRR Holden Lee, Cyril Zhang
2018	—	`conf`	Not-So-Random Features. ICLR (Poster) Brian Bullins, Cyril Zhang, Yi Zhang
2018	A*	`conf`	Spectral Filtering for General Linear Dynamical Systems. NeurIPS Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang
2018	J	`jnl`	Spectral Filtering for General Linear Dynamical Systems. CoRR Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang
2018	J	`jnl`	The Case for Full-Matrix Adaptive Regularization. CoRR Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang
2018	—	`conf`	Towards Provable Control for Unknown Linear Dynamical Systems. ICLR (Workshop) Sanjeev Arora, Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang
2017	A*	`conf`	Efficient Regret Minimization in Non-Convex Games. ICML Elad Hazan, Karan Singh, Cyril Zhang
2017	J	`jnl`	Efficient Regret Minimization in Non-Convex Games. CoRR Elad Hazan, Karan Singh, Cyril Zhang
2017	—	`conf`	Learning Linear Dynamical Systems via Spectral Filtering. NIPS Elad Hazan, Karan Singh, Cyril Zhang
2017	J	`jnl`	Learning Linear Dynamical Systems via Spectral Filtering. CoRR Elad Hazan, Karan Singh, Cyril Zhang
2017	J	`jnl`	Not-So-Random Features. CoRR Brian Bullins, Cyril Zhang, Yi Zhang