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Słownik AI

Kompletny słownik sztucznej inteligencji

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kategorie
2 032
podkategorie
23 060
pojęcia
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pojęcia

Retriever-Reader

Two-step QA architecture where a 'retriever' first selects relevant documents, then a 'reader' extracts the precise answer from these documents to maximize efficiency and accuracy.

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Answer Span Prediction

Task of predicting the start and end positions of the exact answer in a given context, typically performed by classification layers on the text tokens.

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Knowledge-Intensive QA

QA systems requiring access to extensive external knowledge bases to answer complex questions that cannot be solved by reasoning alone on the provided context.

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Open-Domain Fact Verification

Process of validating the accuracy of a claim by searching and analyzing evidence across unrestricted sources on the web or in large document collections.

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Question Decomposition

Technique that divides a complex question into multiple simpler and individually tractable sub-questions, facilitating information retrieval and composition of complete answers.

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Answer Triggering

Binary classification mechanism that determines whether a retrieved passage actually contains an answer to the asked question, avoiding generating incorrect answers from irrelevant contexts.

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Reader Confidence Score

Metric calculated by the 'reader' model indicating the certainty level of the extracted answer, often used for reranking or filtering candidate answers in QA pipelines.

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Reranking Model

Specialized model that reevaluates and reorders an initial list of retrieved documents or passages to improve the precision of the most relevant results before the answer extraction step.

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Passage Overlap

Phenomenon where several retrieved passages contain redundant or overlapping information, requiring deduplication or merging techniques to optimize answer presentation.

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Knowledge Graph Integration

Incorporation of structured knowledge graphs into QA systems to provide verifiable factual information and complement answers based on unstructured text.

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Answer Aggregation

Process of combining multiple candidate answers from different passages or documents to form a single, coherent, and complete answer to the asked question.

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