45 citations · 90 across the 5 of their papers we have counts for
6 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…
Generating Benchmarks for Factuality Evaluation of Language Models
Dor Muhlgay, Ori Ram, Inbal Magar +7
Before deploying a language model (LM) within a given domain, it is important to measure its tendency to generate factually incorrect information in that domain. Existing methods f…
In-Context Retrieval-Augmented Language Models
Ori Ram, Yoav Levine, Itay Dalmedigos +4
Retrieval-Augmented Language Modeling (RALM) methods, which condition a language model (LM) on relevant documents from a grounding corpus during generation, were shown to significa…
MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning
Ehud Karpas, Omri Abend, Yonatan Belinkov +14
Huge language models (LMs) have ushered in a new era for AI, serving as a gateway to natural-language-based knowledge tasks. Although an essential element of modern AI, LMs are als…
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…
Value-based Search in Execution Space for Mapping Instructions to Programs
Dor Muhlgay, Jonathan Herzig, Jonathan Berant
Training models to map natural language instructions to programs given target world supervision only requires searching for good programs at training time. Search is commonly done…