2 papers
cs.ET2026
The SpiNNaker2 chip: a many-core platform for flexible and scalable brain-inspired computing
Stefan Scholze, Johannes Partzsch, Sebastian Höppner +27
In deep learning, efficiency gets more and more important to compensate for the ongoing growth in model sizes and applications. Neuromorphic hardware has long been advocated as an…
cs.IR2026
Do We Need Bigger Models for Science? Task-Aware Retrieval with Small Language Models
Florian Kelber, Matthias Jobst, Yuni Susanti +1
Scientific knowledge discovery increasingly relies on large language models, yet many existing scholarly assistants depend on proprietary systems with tens or hundreds of billions…