3 papers
cs.CL2026
Latent Reasoning with Supervised Thinking States
Ido Amos, Avi Caciularu, Mor Geva +4
Reasoning with a chain-of-thought (CoT) enables Large Language Models (LLMs) to solve complex tasks but incurs significant inference costs due to the generation of long rationales.…
q-bio.QM2024
MAMMAL -- Molecular Aligned Multi-Modal Architecture and Language
Yoel Shoshan, Moshiko Raboh, Michal Ozery-Flato +18
Large language models applied to vast biological datasets have the potential to transform biology by uncovering disease mechanisms and accelerating drug development. However, curre…
cs.LG2023
Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors
Ido Amos, Jonathan Berant, Ankit Gupta
Modeling long-range dependencies across sequences is a longstanding goal in machine learning and has led to architectures, such as state space models, that dramatically outperform…