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CORE: A Training-Free Harness for Efficient Deep Research Search

CORE is a new training-free harness for deep research agents that balances long-passage retrieval with short evidence snippets. It uses a dense retriever for coarse search and a late-interaction reranker to extract only the most relevant snippets, while context management allows expanding context around retrieved sources and suppresses duplicates. In controlled comparisons, CORE achieves state-of-the-art accuracy and evidence recall across multiple agent models and benchmarks.