20 citations · 50 across the 5 of their papers we have counts for
5 papers
Jamba-1.5: Hybrid Transformer-Mamba Models at Scale
Jamba Team, Barak Lenz, Alan Arazi +58
We present Jamba-1.5, new instruction-tuned large language models based on our Jamba architecture. Jamba is a hybrid Transformer-Mamba mixture of experts architecture, providing hi…
Human or Not? A Gamified Approach to the Turing Test
Daniel Jannai, Amos Meron, Barak Lenz +2
We present "Human or Not?", an online game inspired by the Turing test, that measures the capability of AI chatbots to mimic humans in dialog, and of humans to tell bots from other…
Standing on the Shoulders of Giant Frozen Language Models
Yoav Levine, Itay Dalmedigos, Ori Ram +10
Huge pretrained language models (LMs) have demonstrated surprisingly good zero-shot capabilities on a wide variety of tasks. This gives rise to the appealing vision of a single, ve…
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design
Yoav Levine, Noam Wies, Daniel Jannai +3
Pretraining Neural Language Models (NLMs) over a large corpus involves chunking the text into training examples, which are contiguous text segments of sizes processable by the neur…
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention
Noam Wies, Yoav Levine, Daniel Jannai +1
After their successful debut in natural language processing, Transformer architectures are now becoming the de-facto standard in many domains. An obstacle for their deployment over…