Brando Miranda

34 papers A* 4Journal 27Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Quantifying the Effect of Test Set Contamination on Generative Evaluations. CoRR Rylan Schaeffer, Joshua Kazdan, Baber Abbasi, Ken Ziyu Liu, Brando Miranda, Ahmed Ahmed, Abhay Puri, Niloofar Mireshghallah, Sanmi Koyejo
2025	J	`jnl`	AlphaApollo: Orchestrating Foundation Models and Professional Tools into a Self-Evolving System for Deep Agentic Reasoning. CoRR Zhanke Zhou, Chentao Cao, Xiao Feng, Xuan Li, Zongze Li, Xiangyu Lu, Jiangchao Yao, Weikai Huang, Linrui Xu, Tian Cheng, Guanyu Jiang, Yiming Zheng, Brando Miranda, Tongliang Liu, Sanmi Koyejo, Masashi Sugiyama, Bo Han
2025	J	`jnl`	Evaluating the Robustness of Chinchilla Compute-Optimal Scaling. CoRR Rylan Schaeffer, Noam Levi, Andreas Kirsch, Theo Guenais, Brando Miranda, Elyas Obbad, Sanmi Koyejo
2025	J	`jnl`	Exploring the Efficacy of Meta-Learning: Unveiling Superior Data Diversity Utilization of MAML Over Pre-training. CoRR Kavita Selva, Satita Vittayaareekul, Brando Miranda
2025	A*	`conf`	Failures to Find Transferable Image Jailbreaks Between Vision-Language Models. ICLR Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristóbal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, Tony Tong Wang, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez
2025	J	`jnl`	Lean-ing on Quality: How High-Quality Data Beats Diverse Multilingual Data in AutoFormalization. CoRR Willy Chan, Michael Souliman, Jakob Nordhagen, Brando Miranda, Elyas Obbad, Oluwasanmi Koyejo
2025	—	`conf`	Pantograph: A Machine-to-Machine Interaction Interface for Advanced Theorem Proving, High Level Reasoning, and Data Extraction in Lean 4. TACAS (1) Leni Aniva, Chuyue Sun, Brando Miranda, Clark W. Barrett, Sanmi Koyejo
2025	J	`jnl`	Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track. CoRR Rylan Schaeffer, Joshua Kazdan, Yegor Denisov-Blanch, Brando Miranda, Matthias Gerstgrasser, Susan Zhang, Andreas Haupt, Isha Gupta, Elyas Obbad, Jesse Dodge, Jessica Zosa Forde, Koustuv Sinha, Francesco Orabona, Sanmi Koyejo, David L. Donoho
2025	J	`jnl`	Pretraining Scaling Laws for Generative Evaluations of Language Models. CoRR Rylan Schaeffer, Noam Levi, Brando Miranda, Sanmi Koyejo
2025	A*	`conf`	Putnam-AXIOM: A Functional & Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs. ICML Aryan Gulati, Brando Miranda, Eric Chen, Emily Xia, Kai Fronsdal, Bruno de Moraes Dumont, Sanmi Koyejo
2025	J	`jnl`	Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs. CoRR Aryan Gulati, Brando Miranda, Eric Chen, Emily Xia, Kai Fronsdal, Bruno de Moraes Dumont, Elyas Obbad, Sanmi Koyejo
2025	J	`jnl`	Quantifying the Importance of Data Alignment in Downstream Model Performance. CoRR Krrish Chawla, Aryan Sahai, Mario DePavia, Sudharsan Sundar, Brando Miranda
2025	A*	`conf`	Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive? ICML Rylan Schaeffer, Hailey Schoelkopf, Brando Miranda, Gabriel Mukobi, Varun Madan, Adam Ibrahim, Herbie Bradley, Stella Biderman, Sanmi Koyejo
2024	—	`conf`	A Systematic Study of the Role of Data Quality and Alignment for Fine-tuning LLMs for Enhanced Autoformalization. Tiny Papers @ ICLR Krrish Chawla, Mario DePavia, Aryan Sahai, Brando Miranda
2024	—	`conf`	An Evaluation Benchmark for Autoformalization in Lean4. Tiny Papers @ ICLR Jasdeep Sidhu, Shubhra Mishra, Aryan Gulati, Devanshu Ladsaria, Brando Miranda
2024	J	`jnl`	An Evaluation Benchmark for Autoformalization in Lean4. CoRR Aryan Gulati, Devanshu Ladsaria, Shubhra Mishra, Jasdeep Sidhu, Brando Miranda
2024	J	`jnl`	Pantograph: A Machine-to-Machine Interaction Interface for Advanced Theorem Proving, High Level Reasoning, and Data Extraction in Lean 4. CoRR Leni Aniva, Chuyue Sun, Brando Miranda, Clark W. Barrett, Sanmi Koyejo
2024	J	`jnl`	When Do Universal Image Jailbreaks Transfer Between Vision-Language Models? CoRR Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristóbal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez
2024	J	`jnl`	Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive? CoRR Rylan Schaeffer, Hailey Schoelkopf, Brando Miranda, Gabriel Mukobi, Varun Madan, Adam Ibrahim, Herbie Bradley, Stella Biderman, Sanmi Koyejo
2024	J	`jnl`	ZIP-FIT: Embedding-Free Data Selection via Compression-Based Alignment. CoRR Elyas Obbad, Iddah Mlauzi, Brando Miranda, Rylan Schaeffer, Kamal Obbad, Suhana Bedi, Sanmi Koyejo
2023	A*	`conf`	Are Emergent Abilities of Large Language Models a Mirage? NeurIPS Rylan Schaeffer, Brando Miranda, Sanmi Koyejo
2023	J	`jnl`	Are Emergent Abilities of Large Language Models a Mirage? CoRR Rylan Schaeffer, Brando Miranda, Sanmi Koyejo
2023	J	`jnl`	Beyond Scale: the Diversity Coefficient as a Data Quality Metric Demonstrates LLMs are Pre-trained on Formally Diverse Data. CoRR Alycia Lee, Brando Miranda, Sanmi Koyejo
2023	J	`jnl`	Is Pre-training Truly Better Than Meta-Learning? CoRR Brando Miranda, Patrick Yu, Saumya Goyal, Yu-Xiong Wang, Sanmi Koyejo
2023	J	`jnl`	Transformer Models for Type Inference in the Simply Typed Lambda Calculus: A Case Study in Deep Learning for Code. CoRR Brando Miranda, Avi Shinnar, Vasily Pestun, Barry M. Trager
2022	J	`jnl`	The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence. CoRR Brando Miranda, Patrick Yu, Yu-Xiong Wang, Sanmi Koyejo
2021	J	`jnl`	Does MAML Only Work via Feature Re-use? A Data Centric Perspective. CoRR Brando Miranda, Yu-Xiong Wang, Sanmi Koyejo
2019	J	`jnl`	Theory III: Dynamics and Generalization in Deep Networks. CoRR Andrzej Banburski, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Bob Liang, Jack Hidary, Tomaso A. Poggio
2018	J	`jnl`	A Surprising Linear Relationship Predicts Test Performance in Deep Networks. CoRR Qianli Liao, Brando Miranda, Andrzej Banburski, Jack Hidary, Tomaso A. Poggio
2018	J	`jnl`	Theory IIIb: Generalization in Deep Networks. CoRR Tomaso A. Poggio, Qianli Liao, Brando Miranda, Andrzej Banburski, Xavier Boix, Jack Hidary
2018	J	`jnl`	Theory of Deep Learning III: explaining the non-overfitting puzzle. CoRR Tomaso A. Poggio, Kenji Kawaguchi, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Xavier Boix, Jack Hidary, Hrushikesh N. Mhaskar
2018	J	`jnl`	Theory of Deep Learning IIb: Optimization Properties of SGD. CoRR Chiyuan Zhang, Qianli Liao, Alexander Rakhlin, Brando Miranda, Noah Golowich, Tomaso A. Poggio
2017	J	`jnl`	Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review. Int. J. Autom. Comput. Tomaso A. Poggio, Hrushikesh N. Mhaskar, Lorenzo Rosasco, Brando Miranda, Qianli Liao
2016	J	`jnl`	Why and When Can Deep - but Not Shallow - Networks Avoid the Curse of Dimensionality: a Review. CoRR Tomaso A. Poggio, Hrushikesh N. Mhaskar, Lorenzo Rosasco, Brando Miranda, Qianli Liao