6 citations · 9 across the 7 of their papers we have counts for
3 papers · 1 filter
Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance
Jingwei Zuo, Maksim Velikanov, Ilyas Chahed +24
In this report, we introduce Falcon-H1, a new series of large language models (LLMs) featuring hybrid architecture designs optimized for both high performance and efficiency across…
3LM: Bridging Arabic, STEM, and Code through Benchmarking
Basma El Amel Boussaha, Leen AlQadi, Mugariya Farooq +5
Arabic is one of the most widely spoken languages in the world, yet efforts to develop and evaluate Large Language Models (LLMs) for Arabic remain relatively limited. Most existing…
NeurIPS 2025 E2LM Competition : Early Training Evaluation of Language Models
Mouadh Yagoubi, Yasser Dahou, Billel Mokeddem +12
Existing benchmarks have proven effective for assessing the performance of fully trained large language models. However, we find striking differences in the early training stages o…