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Msmarco MiniLM L6 En De V1

Developed by cross-encoder
This is a cross-lingual cross-encoder model suitable for English-German bilingual paragraph re-ranking tasks, trained based on the MS Marco passage ranking task.
Downloads 2,784
Release Time : 3/2/2022

Model Overview

This model is used for paragraph re-ranking tasks in information retrieval scenarios, supporting bilingual query and document matching in English and German.

Model Features

Cross-Lingual Support
Supports bilingual query and document matching in English and German, enabling cross-lingual information retrieval.
Efficient Re-ranking
Optimizes the results of traditional retrieval methods like BM25, significantly improving retrieval quality.
High Performance
Performs excellently in benchmark tests such as TREC-DL19 and GermanDPR, surpassing baseline models.

Model Capabilities

English-German bilingual text matching
Retrieval result re-ranking
Cross-lingual information retrieval

Use Cases

Information Retrieval
Search Engine Result Optimization
Semantically re-ranks results returned by traditional search engines.
Achieved NDCG@10 of 72.94 in TREC-DL19 tests.
Cross-Lingual Document Retrieval
Retrieves English documents using German queries.
Achieved NDCG@10 of 66.07 in TREC-DL19 German-English tests.
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