GEM Model: Reasoning Before Retrieval Improves Information Recall
kalyan_kpl · x · 2026-08-15
The paper introduces GEM (Generative Embedding Model), a generative embedding model that reasons before retrieval. While conventional retrievers rely on surface-level matching between queries and documents, GEM unifies generation and embedding within a single model. It first reasons over the query, then appends an embedding token to encode the enriched context for retrieval. Experiments show that GEM's reasoning-augmented retrieval is effective, outperforming non-reasoning variants and matching baselines that use substantially larger models.
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