2 citations · 2 across the 4 of their papers we have counts for
5 papers
How Local Mixing Encodes Relative Position in Global NoPE Attention
Cutter Dawes, Nick Alonso, Tom Figliolia +1
The attention operation is naively position invariant. However, positional information is fundamental to natural language, and therefore a variety of explicit position encodings ha…
Online Vector Quantized Attention
Nick Alonso, Tomas Figliolia, Beren Millidge
Standard sequence mixing layers used in language models struggle to balance efficiency and performance. Self-attention performs well on long context tasks but has expensive quadrat…
Compressed Convolutional Attention: Efficient Attention in a Compressed Latent Space
Tomas Figliolia, Nicholas Alonso, Rishi Iyer +2
Multi-headed Attention's (MHA) quadratic compute and linearly growing KV-cache make long-context transformers expensive to train and serve. Prior works such as Grouped Query Attent…
Mixture-of-PageRanks: Replacing Long-Context with Real-Time, Sparse GraphRAG
Nicholas Alonso, Beren Millidge
Recent advances have extended the context window of frontier LLMs dramatically, from a few thousand tokens up to millions, enabling entire books and codebases to fit into context.…
Toward Conversational Agents with Context and Time Sensitive Long-term Memory
Nick Alonso, Tomás Figliolia, Anthony Ndirango +1
There has recently been growing interest in conversational agents with long-term memory which has led to the rapid development of language models that use retrieval-augmented gener…