Scaling Latent Reasoning via Looped Language Models
Ouro introduces Looped Language Models (LoopLM) that integrate reasoning into the pre-training phase, enhancing performance without merely increasing model size, achieving results comparable to 12B SOTA LLMs across various benchmarks.
Recursive Language Models
Recursive Language Models (RLMs) enable large language models (LLMs) to process prompts significantly longer than their typical context windows by allowing them to decompose and recursively call themselves on prompt snippets, enhancing their performance.
Sirius DB
Sirius is a GPU-native SQL engine that integrates seamlessly with existing databases like DuckDB, achieving over 10× speedup in query execution without requiring major system changes.
Doubly stochastic constraints effectively stabilize Hyper-Connection instability in DeepSeek's mHC by ensuring that matrix multiplications remain bounded, preventing exponential growth in deep networks.
Anatomy of BoltzGen
BoltzGen is a Hugging Face Space that showcases innovative applications of generative models, emphasizing the intersection of machine learning and creativity.
Built a US Mortgage Underwriting OCR System With 96% Real-World Accuracy → Saved ~$2M Per Year
A US mortgage underwriting OCR system achieves ~96% accuracy in real-world applications, significantly outperforming typical services that plateau around 70–72% accuracy, leading to substantial operational improvements.
Dynamic Large Concept Models: Latent Reasoning in an Adaptive Semantic Space