布萊嗯研究所

透過開源重建，揭開大模型「隱藏推理」與遞歸深度架構的神秘面紗。 Unveiling the mystery of "hidden reasoning" and recurrent-depth architectures in LLMs through open-source reconstruction. 🔎 工具速覽 / AT A GLANCE Category AI Architecture / Research Pricing Free (Open Source) BestFor AI Researchers, LLM Architects, Deep Learning Enthusiasts GitHub Stars ⭐ 1274 🚀 引言 / Introduction 在當前大語言模型（LLM）的競賽中，人們對 Claude 等頂尖模型如何實現強大的邏輯推理能力充滿好奇。傳統的 Transformer 依賴於堆疊數百層參數，但這是否是唯一路徑？OpenMythos 提出了一個大膽的理論假設：模型可能採用了「遞歸深度變壓器」（Recurrent-Depth Transformer），讓權重在內部循環運算，實現「沉默的思考」。 In the current LLM race, there is immense curiosity about how top-tier models like Claude achieve powerful logical reasoning. Traditional Transformers rely on stacking hundreds of unique layers, but is this the only path? OpenMythos proposes a bold theoretical hypothesis: models may employ a "Recurrent-...