3 papers
cs.NE2026
Event-Driven Language Models with Sparse Neural Activity for Neuromorphic Hardware
Simon Richter, Ruhai Lin, Jason Yik +4
Inference with transformer-based large language models (LLMs) is often limited by the memory-bound KV cache and quadratic attention cost. State-space models (SSMs) mitigate this th…
cs.LG2026
Allocating Recurrent Compute in Looped Language Models
Ruhai Lin, Yiyang Guo, Rui-Jie Zhu +2
Looped language models improve reasoning and knowledge manipulation by applying shared computation repeatedly. Existing systems usually repeat an entire layer stack, although a mix…
cs.DC2024
Reducing Data Bottlenecks in Distributed, Heterogeneous Neural Networks
Ruhai Lin, Rui-Jie Zhu, Jason K. Eshraghian
The rapid advancement of embedded multicore and many-core systems has revolutionized computing, enabling the development of high-performance, energy-efficient solutions for a wide…