The Concept of Automation in Conventional Systems Creation Applied to the Preliminary Aircraft Design. - Nikolay Borgest; Maksim Korovin; Andrey Gromov; Aleksey Gromov (ACS, 2014)

Critical initialization of wide and deep neural networks through partial Jacobians: general theory and applications to LayerNorm. - Darshil Doshi; Tianyu He; Andrey Gromov (CoRR, 2021)

AutoInit: Automatic Initialization via Jacobian Tuning. - Tianyu He; Darshil Doshi; Andrey Gromov (CoRR, 2022)

Critical Initialization of Wide and Deep Neural Networks using Partial Jacobians: General Theory and Applications. - Darshil Doshi; Tianyu He; Andrey Gromov (NeurIPS, 2023)

Grokking modular arithmetic. - Andrey Gromov (CoRR, 2023)

Deconstructing the generalization gap. - Andrey Gromov (Nat. Mac. Intell., 2023)

To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets. - Darshil Doshi; Aritra Das; Tianyu He; Andrey Gromov (ICLR, 2024)

Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks. - Tianyu He; Darshil Doshi; Aritra Das; Andrey Gromov (NeurIPS, 2024)

Bridging Associative Memory and Probabilistic Modeling. - Rylan Schaeffer; Nika Zahedi; Mikail Khona; Dhruv Pai; Sang T. Truong; Yilun Du; Mitchell Ostrow; Sarthak Chandra; Andres Carranza; Ila Rani Fiete; Andrey Gromov; Sanmi Koyejo (CoRR, 2024)

Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data. - Matthias Gerstgrasser; Rylan Schaeffer; Apratim Dey; Rafael Rafailov; Henry Sleight; John Hughes; Tomasz Korbak; Rajashree Agrawal; Dhruv Pai; Andrey Gromov; Daniel A. Roberts; Diyi Yang; et al. (CoRR, 2024)

Grokking Modular Polynomials. - Darshil Doshi; Tianyu He; Aritra Das; Andrey Gromov (CoRR, 2024)

Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations. - Rylan Schaeffer; Victor Lecomte; Dhruv Bhandarkar Pai; Andres Carranza; Berivan Isik; Alyssa Unell; Mikail Khona; Thomas E. Yerxa; Yann LeCun; SueYeon Chung; Andrey Gromov; Ravid Shwartz-Ziv; et al. (CoRR, 2024)

The Unreasonable Ineffectiveness of the Deeper Layers. - Andrey Gromov; Kushal Tirumala; Hassan Shapourian; Paolo Glorioso; Daniel A. Roberts (ICLR, 2025)

Spectral Journey: How Transformers Predict the Shortest Path. - Andrew Cohen; Andrey Gromov; Kaiyu Yang; Yuandong Tian (CoRR, 2025)

PARQ: Piecewise-Affine Regularized Quantization. - Lisa Jin; Jianhao Ma; Zechun Liu; Andrey Gromov; Aaron Defazio; Lin Xiao (CoRR, 2025)

Towards Distributed Neural Architectures. - Aditya Cowsik; Tianyu He; Andrey Gromov (CoRR, 2025)