29 citations · 94 across the 25 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
cs.CL2026
Titan-Llama: Retrofitting Pre-trained LLMs with External Neural Memory Modules
Sarah Pan, Ali Behrouz
Transformers are efficient to pre-train at scale because attention permits parallel computation across sequence positions, but long-context inference requires increasingly large KV…
cs.CL2026
Self-Preservation in Language Models
Dongkyu Cho, Rumi Chunara, Ali Behrouz
Continual learning (CL) seeks to adapt pretrained models while preserving prior capabilities. Yet the tasks supplied for preservation cover only part of what a model knows, while f…
cs.CL2025
ATLAS: Learning to Optimally Memorize the Context at Test Time
Ali Behrouz, Zeman Li, Praneeth Kacham +5
Transformers have been established as the most popular backbones in sequence modeling, mainly due to their effectiveness in in-context retrieval tasks and the ability to learn at s…