3 papers
cs.AI2026
Falcon-H1R: Pushing the Reasoning Frontiers with a Hybrid Model for Efficient Test-Time Scaling
Falcon LLM Team, Iheb Chaabane, Puneesh Khanna +8
This work introduces Falcon-H1R, a 7B-parameter reasoning-optimized model that establishes the feasibility of achieving competitive reasoning performance with small language models…
cs.CL2025
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…
cs.CV2025
RBench-V: A Primary Assessment for Visual Reasoning Models with Multi-modal Outputs
Meng-Hao Guo, Xuanyu Chu, Qianrui Yang +12
The rapid advancement of native multi-modal models and omni-models, exemplified by GPT-4o, Gemini, and o3, with their capability to process and generate content across modalities s…