On the importance of single directions for generalization. - Ari S. Morcos; David G. T. Barrett; Neil C. Rabinowitz; Matthew M. Botvinick (ICLR (Poster), 2018)

Measuring abstract reasoning in neural networks. - Adam Santoro; Felix Hill; David G. T. Barrett; Ari S. Morcos; Timothy P. Lillicrap (ICML, 2018)

Insights on representational similarity in neural networks with canonical correlation. - Ari S. Morcos; Maithra Raghu; Samy Bengio (NeurIPS, 2018)

Learned Deformation Stability in Convolutional Neural Networks. - Avraham Ruderman; Neil C. Rabinowitz; Ari S. Morcos; Daniel Zoran (CoRR, 2018)

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning. - Max Jaderberg; Wojciech M. Czarnecki; Iain Dunning; Luke Marris; Guy Lever; Antonio García Castañeda; Charles Beattie; Neil C. Rabinowitz; Ari S. Morcos; Avraham Ruderman; Nicolas Sonnerat; Tim Green; et al. (CoRR, 2018)

Analyzing biological and artificial neural networks: challenges with opportunities for synergy? - David G. T. Barrett; Ari S. Morcos; Jakob H. Macke (CoRR, 2018)

Learning to Make Analogies by Contrasting Abstract Relational Structure. - Felix Hill; Adam Santoro; David G. T. Barrett; Ari S. Morcos; Timothy P. Lillicrap (ICLR (Poster), 2019)

One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. - Ari S. Morcos; Haonan Yu; Michela Paganini; Yuandong Tian (NeurIPS, 2019)

Luck Matters: Understanding Training Dynamics of Deep ReLU Networks. - Yuandong Tian; Tina Jiang; Qucheng Gong; Ari S. Morcos (CoRR, 2019)

Decentralized Distributed PPO: Solving PointGoal Navigation. - Erik Wijmans; Abhishek Kadian; Ari Morcos; Stefan Lee; Irfan Essa; Devi Parikh; Manolis Savva; Dhruv Batra (CoRR, 2019)

The Early Phase of Neural Network Training. - Jonathan Frankle; David J. Schwab; Ari S. Morcos (ICLR, 2020)

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames. - Erik Wijmans; Abhishek Kadian; Ari Morcos; Stefan Lee; Irfan Essa; Devi Parikh; Manolis Savva; Dhruv Batra (ICLR, 2020)

Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP. - Haonan Yu; Sergey Edunov; Yuandong Tian; Ari S. Morcos (ICLR, 2020)

Plan2Vec: Unsupervised Representation Learning by Latent Plans. - Ge Yang 003; Amy Zhang 001; Ari S. Morcos; Joelle Pineau; Pieter Abbeel; Roberto Calandra (L4DC, 2020)

The Generalization-Stability Tradeoff In Neural Network Pruning. - Brian R. Bartoldson; Ari S. Morcos; Adrian Barbu; Gordon Erlebacher (NeurIPS, 2020)

Pruning Convolutional Neural Networks with Self-Supervision. - Mathilde Caron; Ari Morcos; Piotr Bojanowski; Julien Mairal; Armand Joulin (CoRR, 2020)

Analyzing Visual Representations in Embodied Navigation Tasks. - Erik Wijmans; Julian Straub; Dhruv Batra; Irfan Essa; Judy Hoffman; Ari Morcos (CoRR, 2020)

On the relationship between class selectivity, dimensionality, and robustness. - Matthew L. Leavitt; Ari S. Morcos (CoRR, 2020)

PareCO: Pareto-aware Channel Optimization for Slimmable Neural Networks. - Ting-Wu Chin; Ari S. Morcos; Diana Marculescu (CoRR, 2020)

Are all negatives created equal in contrastive instance discrimination? - Tiffany Tianhui Cai; Jonathan Frankle; David J. Schwab; Ari S. Morcos (CoRR, 2020)

Linking average- and worst-case perturbation robustness via class selectivity and dimensionality. - Matthew L. Leavitt; Ari S. Morcos (CoRR, 2020)

Towards falsifiable interpretability research. - Matthew L. Leavitt; Ari S. Morcos (CoRR, 2020)

Reservoir Transformer. - Sheng Shen 001; Alexei Baevski; Ari S. Morcos; Kurt Keutzer; Michael Auli; Douwe Kiela (CoRR, 2020)

Reservoir Transformers. - Sheng Shen 001; Alexei Baevski; Ari S. Morcos; Kurt Keutzer; Michael Auli; Douwe Kiela (ACL/IJCNLP (1), 2021)

Width Transfer: On the (In)variance of Width Optimization. - Ting-Wu Chin; Diana Marculescu; Ari S. Morcos (CVPR Workshops, 2021)

Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs. - Jonathan Frankle; David J. Schwab; Ari S. Morcos (ICLR, 2021)

Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs. - Matthew L. Leavitt; Ari S. Morcos (ICLR, 2021)

CURI: A Benchmark for Productive Concept Learning Under Uncertainty. - Ramakrishna Vedantam; Arthur Szlam; Maximilian Nickel; Ari Morcos; Brenden M. Lake (ICML, 2021)

ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases. - Stéphane d'Ascoli; Hugo Touvron; Matthew L. Leavitt; Ari S. Morcos; Giulio Biroli; Levent Sagun (ICML, 2021)

Grounding inductive biases in natural images: invariance stems from variations in data. - Diane Bouchacourt; Mark Ibrahim; Ari S. Morcos (NeurIPS, 2021)

Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks. - Ting-Wu Chin; Ari S. Morcos; Diana Marculescu (ECML/PKDD (3), 2021)

Representation Learning Through Latent Canonicalizations. - Or Litany; Ari Morcos; Srinath Sridhar 002; Leonidas J. Guibas; Judy Hoffman (WACV, 2021)

Leveraging background augmentations to encourage semantic focus in self-supervised contrastive learning. - Chaitanya K. Ryali; David J. Schwab; Ari S. Morcos (CoRR, 2021)

Transformed CNNs: recasting pre-trained convolutional layers with self-attention. - Stéphane d'Ascoli; Levent Sagun; Giulio Biroli; Ari Morcos (CoRR, 2021)

Trade-offs of Local SGD at Scale: An Empirical Study. - Jose Javier Gonzalez Ortiz; Jonathan Frankle; Mike Rabbat; Ari S. Morcos; Nicolas Ballas (CoRR, 2021)

Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. - Mitchell Wortsman; Gabriel Ilharco; Samir Yitzhak Gadre; Rebecca Roelofs; Raphael Gontijo Lopes; Ari S. Morcos; Hongseok Namkoong; Ali Farhadi; Yair Carmon; Simon Kornblith; Ludwig Schmidt (ICML, 2022)

COAT: Measuring Object Compositionality in Emergent Representations. - Sirui Xie; Ari S. Morcos; Song-Chun Zhu; Ramakrishna Vedantam (ICML, 2022)

Beyond neural scaling laws: beating power law scaling via data pruning. - Ben Sorscher; Robert Geirhos; Shashank Shekhar; Surya Ganguli; Ari Morcos (NeurIPS, 2022)

Robust Self-Supervised Learning with Lie Groups. - Mark Ibrahim; Diane Bouchacourt; Ari S. Morcos (CoRR, 2022)

PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. - Florian Bordes; Shashank Shekhar; Mark Ibrahim; Diane Bouchacourt; Pascal Vincent; Ari Morcos (NeurIPS, 2023)

D4: Improving LLM Pretraining via Document De-Duplication and Diversification. - Kushal Tirumala; Daniel Simig; Armen Aghajanyan; Ari Morcos (NeurIPS, 2023)

Stable and low-precision training for large-scale vision-language models. - Mitchell Wortsman; Tim Dettmers; Luke Zettlemoyer; Ari Morcos; Ali Farhadi; Ludwig Schmidt (NeurIPS, 2023)

SemDeDup: Data-efficient learning at web-scale through semantic deduplication. - Amro Abbas; Kushal Tirumala; Daniel Simig; Surya Ganguli; Ari S. Morcos (CoRR, 2023)

A Cookbook of Self-Supervised Learning. - Randall Balestriero; Mark Ibrahim; Vlad Sobal; Ari Morcos; Shashank Shekhar; Tom Goldstein; Florian Bordes; Adrien Bardes; Grégoire Mialon; Yuandong Tian; Avi Schwarzschild; Andrew Gordon Wilson; et al. (CoRR, 2023)

Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations. - Shashank Shekhar; Florian Bordes; Pascal Vincent; Ari Morcos (CoRR, 2023)

Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data. - Yu Yang; Aaditya K. Singh; Mostafa Elhoushi; Anas Mahmoud 002; Kushal Tirumala; Fabian Gloeckle; Baptiste Rozière; Carole-Jean Wu; Ari S. Morcos; Newsha Ardalani (CoRR, 2023)

The Robustness Limits of SoTA Vision Models to Natural Variation. - Mark Ibrahim; Quentin Garrido; Ari S. Morcos; Diane Bouchacourt (Trans. Mach. Learn. Res., 2023)

On the special role of class-selective neurons in early training. - Omkar Ranadive; Nikhil Thakurdesai; Ari S. Morcos; Matthew L. Leavitt; Stéphane Deny (Trans. Mach. Learn. Res., 2023)

lo-fi: distributed fine-tuning without communication. - Mitchell Wortsman; Suchin Gururangan; Shen Li; Ali Farhadi; Ludwig Schmidt; Michael G. Rabbat; Ari S. Morcos (Trans. Mach. Learn. Res., 2023)

Emergence of Maps in the Memories of Blind Navigation Agents. - Erik Wijmans; Manolis Savva; Irfan Essa; Stefan Lee; Ari S. Morcos; Dhruv Batra (AI Matters, 2023)

Sieve: Multimodal Dataset Pruning Using Image Captioning Models. - Anas Mahmoud 002; Mostafa Elhoushi; Amro Abbas; Yu Yang; Newsha Ardalani; Hugh Leather; Ari S. Morcos (CVPR, 2024)

Effective pruning of web-scale datasets based on complexity of concept clusters. - Amro Abbas; Evgenia Rusak; Kushal Tirumala; Wieland Brendel; Kamalika Chaudhuri; Ari S. Morcos (ICLR, 2024)

Brevity is the soul of wit: Pruning long files for code generation. - Aaditya K. Singh; Yu Yang; Kushal Tirumala; Mostafa Elhoushi; Ari S. Morcos (CoRR, 2024)

BeyondWeb: Lessons from Scaling Synthetic Data for Trillion-scale Pretraining. - Pratyush Maini; Vineeth Dorna; Parth Doshi; Aldo Carranza; Fan Pan; Jack Urbanek; Paul Burstein; Alex Fang; Alvin Deng; Amro Abbas; Brett W. Larsen; Cody Blakeney; et al. (CoRR, 2025)