5 papers
Sparse Attention as Compact Kernel Regression
Saul Santos, Nuno Gonçalves, Daniel C. McNamee +2
Recent work has revealed a link between self-attention mechanisms in transformers and test-time kernel regression via the Nadaraya-Watson estimator, with standard softmax attention…
Hopfield-Fenchel-Young Networks: A Unified Framework for Associative Memory Retrieval
Saul Santos, Vlad Niculae, Daniel McNamee +1
Associative memory models, such as Hopfield networks and their modern variants, have garnered renewed interest due to advancements in memory capacity and connections with self-atte…
World Models as Reference Trajectories for Rapid Motor Adaptation
Carlos Stein Brito, Daniel McNamee
Deploying learned control policies in real-world environments poses a fundamental challenge. When system dynamics change unexpectedly, performance degrades until models are retrain…
-Video: A Training-Free Approach to Long Video Understanding via Continuous-Time Memory Consolidation
Saul Santos, António Farinhas, Daniel C. McNamee +1
Current video-language models struggle with long-video understanding due to limited context lengths and reliance on sparse frame subsampling, often leading to information loss. Thi…
Modern Hopfield Networks with Continuous-Time Memories
Saul Santos, António Farinhas, Daniel C. McNamee +1
Recent research has established a connection between modern Hopfield networks (HNs) and transformer attention heads, with guarantees of exponential storage capacity. However, these…