3 citations · 5 across the 23 of their papers we have counts for
7 papers · 1 filter
Are Arabic Benchmarks Reliable? QIMMA's Quality-First Approach to LLM Evaluation
Leen AlQadi, Ahmed Alzubaidi, Mohammed Alyafeai +6
We present QIMMA, a quality-assured Arabic LLM leaderboard that places systematic benchmark validation at its core. Rather than aggregating existing resources as-is, QIMMA applies…
Evaluating Arabic Large Language Models: A Survey of Benchmarks, Methods, and Gaps
Ahmed Alzubaidi, Shaikha Alsuwaidi, Basma El Amel Boussaha +5
This survey provides the first systematic review of Arabic LLM benchmarks, analyzing 40+ evaluation benchmarks across NLP tasks, knowledge domains, cultural understanding, and spec…
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…
Falcon Mamba: The First Competitive Attention-free 7B Language Model
Jingwei Zuo, Maksim Velikanov, Dhia Eddine Rhaiem +4
In this technical report, we present Falcon Mamba 7B, a new base large language model based on the novel Mamba architecture. Falcon Mamba 7B is trained on 5.8 trillion tokens with…
Falcon2-11B Technical Report
Quentin Malartic, Nilabhra Roy Chowdhury, Ruxandra Cojocaru +14
We introduce Falcon2-11B, a foundation model trained on over five trillion tokens, and its multimodal counterpart, Falcon2-11B-vlm, which is a vision-to-text model. We report our f…
ViSpeR: Multilingual Audio-Visual Speech Recognition
Sanath Narayan, Yasser Abdelaziz Dahou Djilali, Ankit Singh +2
This work presents an extensive and detailed study on Audio-Visual Speech Recognition (AVSR) for five widely spoken languages: Chinese, Spanish, English, Arabic, and French. We hav…