打開語言模型“黑箱”！Google DeepMind 發佈一套可視化工具Gemma Scope
Google DeepMind的最新研究Gemma Scope揭開了語言模型黑箱的祕密，通過稀疏自編碼器(SAEs)分解和重構語言模型的激活，旨在揭示背後有意義的特徵。Gemma Scope採用JumpReLU SAEs，通過控制激活，優化重建損失並正則化活躍的潛在特徵數量，以揭示語言模型的內部機制。研究發現，殘差流SAEs的性能通常較低，序列長度對SAE性能有顯著影響，不同數據集子集的表現各異，DeepMind mathematics上表現最佳。Gemma Scope的發佈不僅有助於理解SAEs，還能改進實際任務性能，對SAEs進行紅隊測試，提高AI的可解釋性和安全性。
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