Codesota · Tasks · RetrievalHome/Tasks/General/Retrieval

Retrieval.

Retrieval is the process of fetching relevant information from a vast knowledge base or database to answer a user's query or enhance a model's response, most notably seen in Retrieval-Augmented Generation (RAG) systems. RAG combines traditional search capabilities with large language models (LLMs) to ensure accuracy, provide up-to-date information, and ground AI responses in factual, external data rather than relying solely on a model's internal, potentially outdated knowledge.

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Datasets
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Canonical metric
§ 02 · Canonical benchmark

The reference dataset.

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§ 03 · Top 10

Leading models.

Leading models across all datasets in this task.

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§ 04 · All datasets

Tracked datasets.

7 datasets tracked for this task.

AmsterTime
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BEIR
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CodeSearchNet (CSN)
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INRIA Copydays (strong subset)
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MLDR (English subset)
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Revisited Paris (R_Par) — Medium split
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StackOverflow-QA (StackQA)
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§ 05 · Related tasks

Other tasks in General.

Coding AgentsComputer Use AgentsEmbedding modelsGeneralOmni modelsReasoningReinforcement LearningVideo-Language Models
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