Tailored queries enable identification of the embedding model used by a black-box IR system from the unordered set of retrieved documents, even when a reranker is present.
Manning, Prabhakar Raghavan, and Hinrich Schütze
6 Pith papers cite this work, alongside 10,873 external citations. Polarity classification is still indexing.
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Develops a unified framework representing performance metrics as smooth functionals of confusion-matrix probabilities to enable cluster-robust sandwich variance estimation for asymptotically valid confidence intervals and tests under clustered data.
Decontextualized, hyperlink-anchored evidence premises from fact-check articles improve retrieval and verdict prediction, released as the PrimeFacts resource.
Introduces a reproducible benchmark and hybrid sparse-dense retrieval framework for evidence-grounded access to silicon detector literature, reporting Hit@5 of 0.917 on core queries.
Cluster-based semantic chunking does not outperform fixed-size or recursive chunking for RAG on academic theses, and RAGAs faithfulness shows limited reliability in this setup.
A survey that categorizes RAG methods for LLMs into four retrieval-centric stages, reviews their evolution and evaluation, and outlines challenges and future directions.
citing papers explorer
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Embedding Inference Attack
Tailored queries enable identification of the embedding model used by a black-box IR system from the unordered set of retrieved documents, even when a reranker is present.
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Beyond Point Estimates: Reliable Evaluation of Prediction Performance Metrics under Clustered Data
Develops a unified framework representing performance metrics as smooth functionals of confusion-matrix probabilities to enable cluster-robust sandwich variance estimation for asymptotically valid confidence intervals and tests under clustered data.
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From Articles to Premises: Building PrimeFacts, an Extraction Methodology and Resource for Fact-Checking Evidence
Decontextualized, hyperlink-anchored evidence premises from fact-check articles improve retrieval and verdict prediction, released as the PrimeFacts resource.
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A Reproducible Benchmark and Evidence-Retrieval Software Framework for Silicon Detector R&D Literature
Introduces a reproducible benchmark and hybrid sparse-dense retrieval framework for evidence-grounded access to silicon detector literature, reporting Hit@5 of 0.917 on core queries.
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Evaluating Chunking Strategies for Retrieval-Augmented Generation on Academic Texts
Cluster-based semantic chunking does not outperform fixed-size or recursive chunking for RAG on academic theses, and RAGAs faithfulness shows limited reliability in this setup.
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A Survey on Retrieval-Augmented Text Generation for Large Language Models
A survey that categorizes RAG methods for LLMs into four retrieval-centric stages, reviews their evolution and evaluation, and outlines challenges and future directions.