activity
20182026
most citedJais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models

23 citations · 34 across the 18 of their papers we have counts for

collaborators

22 papers

cs.CL2026

Jais 2: A Family of Arabic-Centric Open Large Language Models

Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim +57

Jais 2 is a family of Arabic-centric large language models developed jointly by MBZUAI, Cerebras, and Inception, designed to advance Arabic-centric language modeling, with strong p…

cs.LG2026

From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning

Lingjing Kong, Xin Liu, Guangyi Chen +9

Post-training pipelines that combine supervised fine-tuning (SFT) with reinforcement learning (RL) have emerged as the key recipe for transforming large language models (LLMs) into…

cs.CV2026

Automated Quality Assessment of Blind Sweep Obstetric Ultrasound for Improved Diagnosis

Prasiddha Bhandari, Kanchan Poudel, Nishant Luitel +6

Blind Sweep Obstetric Ultrasound (BSOU) enables scalable fetal imaging in low-resource settings by allowing minimally trained operators to acquire standardized sweep videos for aut…

cs.CV2025★ 1 cited

PAN: A World Model for General, Actionable, and Long-Horizon World Simulation

PAN Team, Zihan Liu, Yi Gu +12

A world model is a cognitive simulator of the real-world environment allowing biological agents to reason about how the world evolves, whether spontaneously or in response to their…

cs.CV2025

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation

Yuheng Zha, Kun Zhou, Yujia Wu +7

Despite their success, current training pipelines for reasoning VLMs focus on a limited range of tasks, such as mathematical and logical reasoning. As a result, these models face d…

cs.CL2025

Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models

Yanbin Yin, Kun Zhou, Zhen Wang +11

The recent explosion of large language models (LLMs), each with its own general or specialized strengths, makes scalable, reliable benchmarking more urgent than ever. Standard prac…