JudgeMyAIRBS-Attention: How to Speed Up Long-Context LLMs 20.65x Without Training
RBS-Attention achieves 20.65x prefill speedup with training-free sparse attention, reducing mean dilution in long-context LLMs.
ZGCM-1: Open 7B Dense Model that Marries Internal Reasoning with External Tool Use for Math and Agentic Search
Executive Takeaway What happened? Researchers released ZGCM-1, a fully open 7‑billion‑parameter dense foundation model that attains competitive math‑reasoning and agentic‑search performance with a 256K context window. The model is trained from scratch using a novel interleaved gated sliding‑window + full attention architecture, a stable FP8 Muon optimizer, and a curriculum that treats interaction traces as […]