Understanding how transformer components operate in LLMs is important, as it is at the core of recent technological advances in artificial intelligence. In this work, we revisit the challenges associated with interpretability of feed-forward modules (FFNs) and propose MemoryLLM, which aims to decouple FFNs from self-attention and enables us to...
🛡️ VERIFIED CYBER INTELLIGENCE ID: #3613702
🔧 MemoryLLM: Plug-n-Play Interpretable Feed-Forward Memory for Transformers
⏱️ vor 27d 14h (02.07.2026 um 02:00 Uhr) 📂 🔧 AI Nachrichten 📡 Feed 🔗 Quelle: machinelearning.apple.com