MoME: Mixture-of-Memory Embeddings for Context-Aware Sparse Lookup
MoME introduces context-aware memory embeddings with gated multi-slot lookup, improving LLM efficiency across Llama-3 and Qwen3 backbones.
Mixture of Memory Embeddings (MoME) replaces each token's single memory row with a mixture of M slots selected by a learned gate over the hidden state, resolving sense-collision in deterministic lookups. In controlled pretraining on nanochat, Llama-3/MobileLLM, and Qwen3 backbones, MoME beats Value Embedding, Bigram, and STEM baselines in iso-parameter and iso-FLOP settings. Routing analyses show semantic interpretability, dispatching polysemous tokens to distinct slots by context.
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