Paper Citation Record · LEDGER

Constructing and Evaluating Declarative RAG Pipelines in PyTerrier

As of 19 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2506.10802.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.10802 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

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measured 56 of 56 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

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External citation measurements

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Outbound references

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier Unresolved cited work

Reference 1

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This paper cites PyTerrier-GenRank: The PyTerrier Plugin for Reranking with Large Language Models.

Constructing and Evaluating Declarative RAG Pipelines in PyTerrier PyTerrier-GenRank: The PyTerrier Plugin for Reranking with Large Language Models

Reference 5

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier Retrieval-Augmented Generation for Large Language Models: A Survey

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier Weld, and Luke Zettlemoyer

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, and Christopher Potts

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob De- vlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier Pseudo Relevance Feedback with Deep Language Models and Dense Retrievers: Successes and Pitfalls

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier 2021.Pretrained Trans- formers for Text Ranking: BERT and Beyond

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier On Precomputation and Caching in Information Retrieval Experiments with Pipeline Architectures

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier Smith, and Mike Lewis

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier In8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020

Reference 2020

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Constructing and Evaluating Declarative RAG Pipelines in PyTerrier InThe Twelfth International Conference on Learning Representa- tions, ICLR 2024, Vienna, Austria, May 7-11, 2024

Reference 2024

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Pith citing papers

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