Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance Paper • 2507.22448 • Published 15 days ago • 62
Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding Paper • 2507.19427 • Published 19 days ago • 18
SWE-Perf: Can Language Models Optimize Code Performance on Real-World Repositories? Paper • 2507.12415 • Published 28 days ago • 41
Vision Foundation Models as Effective Visual Tokenizers for Autoregressive Image Generation Paper • 2507.08441 • Published Jul 11 • 61
Open Vision Reasoner: Transferring Linguistic Cognitive Behavior for Visual Reasoning Paper • 2507.05255 • Published Jul 7 • 70
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? Paper • 2504.13837 • Published Apr 18 • 134
Step1X-Edit: A Practical Framework for General Image Editing Paper • 2504.17761 • Published Apr 24 • 93
Expanding RL with Verifiable Rewards Across Diverse Domains Paper • 2503.23829 • Published Mar 31 • 24
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models Paper • 2503.24235 • Published Mar 31 • 55
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model Paper • 2503.24290 • Published Mar 31 • 63
view article Article NVIDIA's GTC 2025 Announcement for Physical AI Developers: New Open Models and Datasets By mingyuliutw and 4 others • Mar 18 • 41
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding Paper • 2411.04282 • Published Nov 6, 2024 • 38
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore Paper • 2407.12854 • Published Jul 9, 2024 • 32
Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies Paper • 2407.13623 • Published Jul 18, 2024 • 57