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MARS enables multilingual search without learned retrievers

Researchers propose MARS, a multilingual search agent that retrieves evidence directly from raw corpora using shell commands, eliminating the need for learned retrievers and their associated cross-lingual errors.

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Researchers at the paper's institution have introduced MARS, a multilingual search agent designed to retrieve evidence directly from raw corpora without relying on learned retrievers or similarity-based ranking systems. The approach uses executable shell commands to interact with raw text collection...

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Method & sources
Source type
Primary publication (lab/vendor blog) — our analysis + implication
Source link
r/arxiv-compression
Published
UTC
Byline
By the gotcontext.ai team (editorial standards)
Correction?
corrections@gotcontext.ai

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