{"slug": "mome-mixture-of-memory-embeddings-for-context-aware-sparse-lookup", "title": "MoME: Mixture-of-Memory Embeddings for Context-Aware Sparse Lookup", "summary": "Researchers introduced MoME, a Mixture-of-Memory Embeddings method for context-aware sparse lookup that addresses a limitation in existing memory-embedding approaches, which retrieve via a deterministic mechanism. The work targets efficient scaling of large language models by combining sparse capacity mechanisms such as Mixture-of-Experts with token-indexed embedding tables that augment the backbone through cheap parametric lookups.", "body_md": "Scaling large language models efficiently has motivated sparse capacity mechanisms such as Mixture-of-Experts and, more recently, conditional memory: token-indexed embedding tables that augment the backbone with cheap parametric lookups. Existing memory-embedding methods retrieve via a deterministic", "url": "https://wpnews.pro/news/mome-mixture-of-memory-embeddings-for-context-aware-sparse-lookup", "canonical_source": "https://aiflash.com/news/123538/", "published_at": "2026-09-21 05:30:01+00:00", "updated_at": "2026-09-21 05:54:36.982350+00:00", "lang": "en", "topics": ["large-language-models", "machine-learning", "artificial-intelligence", "ai-research"], "entities": ["MoME", "Mixture-of-Experts"], "alternates": {"html": "https://wpnews.pro/news/mome-mixture-of-memory-embeddings-for-context-aware-sparse-lookup", "markdown": "https://wpnews.pro/news/mome-mixture-of-memory-embeddings-for-context-aware-sparse-lookup.md", "text": "https://wpnews.pro/news/mome-mixture-of-memory-embeddings-for-context-aware-sparse-lookup.txt", "jsonld": "https://wpnews.pro/news/mome-mixture-of-memory-embeddings-for-context-aware-sparse-lookup.jsonld"}}