12 citations · 20 across the 8 of their papers we have counts for
4 papers · 1 filter
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations
Rylan Schaeffer, Victor Lecomte, Dhruv Bhandarkar Pai +10
Maximum Manifold Capacity Representations (MMCR) is a recent multi-view self-supervised learning (MVSSL) method that matches or surpasses other leading MVSSL methods. MMCR is intri…
Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data
Matthias Gerstgrasser, Rylan Schaeffer, Apratim Dey +11
The proliferation of generative models, combined with pretraining on web-scale data, raises a timely question: what happens when these models are trained on their own generated out…
The Unreasonable Ineffectiveness of the Deeper Layers
Andrey Gromov, Kushal Tirumala, Hassan Shapourian +2
How is knowledge stored in an LLM's weights? We study this via layer pruning: if removing a certain layer does not affect model performance in common question-answering benchmarks,…
Bridging Associative Memory and Probabilistic Modeling
Rylan Schaeffer, Nika Zahedi, Mikail Khona +9
Associative memory and probabilistic modeling are two fundamental topics in artificial intelligence. The first studies recurrent neural networks designed to denoise, complete and r…