4 papers · 1 filter
Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
Connor Schenck, Isaac Reid, Mithun George Jacob +19
We introduce STRING: Separable Translationally Invariant Position Encodings. STRING extends Rotary Position Encodings, a recently proposed and widely used algorithm in large langua…
Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning
Arijit Sehanobish, Avinava Dubey, Krzysztof Choromanski +4
Recent efforts to scale Transformer models have demonstrated rapid progress across a wide range of tasks (Wei et al., 2022). However, fine-tuning these models for downstream tasks…
Linear Transformer Topological Masking with Graph Random Features
Isaac Reid, Kumar Avinava Dubey, Deepali Jain +12
When training transformers on graph-structured data, incorporating information about the underlying topology is crucial for good performance. Topological masking, a type of relativ…
Modeling the Real World with High-Density Visual Particle Dynamics
William F. Whitney, Jacob Varley, Deepali Jain +3
We present High-Density Visual Particle Dynamics (HD-VPD), a learned world model that can emulate the physical dynamics of real scenes by processing massive latent point clouds con…