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Paper Citation Record · LEDGER

Searching for Best Practices in Retrieval-Augmented Generation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2407.01219.

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

pith.paper-citation-record.v1
2407.01219 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:05:42.210375Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

6
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 512deba6-ee64-4ac3-aee7-a55fd181391d · inbound

A Survey on Retrieval-Augmented Text Generation for Large Language Models cites this paper.

A Survey on Retrieval-Augmented Text Generation for Large Language Models Searching for Best Practices in Retrieval-Augmented Generation

Reference 144

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:15:55.492720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T02:15:05.379583Z digest=sha256:cd5980e7dce29db0f820cd9883f96b569bcfecd1a25d0e910f650276cc506a6a

Observation f14cfd23-de2d-4d20-91d4-f43b9229c5dd · inbound

Climate Finance Bench cites this paper.

Climate Finance Bench Searching for Best Practices in Retrieval-Augmented Generation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T13:05:42.210375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:05:42.210375Z digest=sha256:ff5e45cb479ad2ac7e2d0dd2ffe69e3f9d11606a2dc2a75246bb1f7bb2c1e8b7

Observation b9d484cb-273d-408c-8ba9-c94000835865 · inbound

RAGOps: Operating and Managing Retrieval-Augmented Generation Pipelines cites this paper.

RAGOps: Operating and Managing Retrieval-Augmented Generation Pipelines Searching for Best Practices in Retrieval-Augmented Generation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T11:07:10.550863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:07:10.550863Z digest=sha256:1ff98ebacaf856a61b2ae6c7e9bea3b18de79050cb983afcdf3f4a04823cd317

Observation fd6652c5-5c9d-4bb3-9842-a4c75f95a24c · inbound

MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks cites this paper.

MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks Searching for Best Practices in Retrieval-Augmented Generation

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:53.443996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:49:53.443996Z digest=sha256:e3f15e4d15572dea03077cbf313211a25c515842c1ebc6440a922a30d842b966

Observation 0d0cec41-34fa-4827-bfb2-0050c65f8c5f · inbound

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward cites this paper.

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward Searching for Best Practices in Retrieval-Augmented Generation

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-05T19:21:52.811377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:21:52.811377Z digest=sha256:d84f57d40f320216de0e8a2fec4924f4ffd0a50730c23ee8d5601f37b24f5ea9

Observation 161e8940-08fd-462c-ac78-ed716c86097d · inbound

An Agile Method for Implementing Retrieval Augmented Generation Tools in Industrial SMEs cites this paper.

An Agile Method for Implementing Retrieval Augmented Generation Tools in Industrial SMEs Searching for Best Practices in Retrieval-Augmented Generation

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-05T14:39:44.055327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:39:44.055327Z digest=sha256:f48754ec833da70f79264a9c460ef58b80210ebfc4a98a52ec4d8c72e04ee172

Observation bc3e986d-920c-48a3-8b26-9e9c5981e50e · inbound

MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems cites this paper.

MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems Searching for Best Practices in Retrieval-Augmented Generation

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T14:28:38.966921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:38.966921Z digest=sha256:6abacc813b3bd8eda53eae3eed80588953c1314818c3026f6f6df8738e4e1009

Observation ec19a4ef-ba19-4b7e-bb86-2c1bbae2e195 · inbound

GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Framework cites this paper.

GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Framework Searching for Best Practices in Retrieval-Augmented Generation

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-05T13:36:43.508738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:36:43.508738Z digest=sha256:9bcfe622d99918b86dc5c735934fc74536e8fd7845c40ce99d2ef9626f1e6b63

Observation 21ce2727-451a-4376-9509-4825ce63c651 · inbound

ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text Reranking cites this paper.

ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text Reranking Searching for Best Practices in Retrieval-Augmented Generation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T13:36:39.517828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:36:39.517828Z digest=sha256:fee8fd4ec871c8558bb76d3398922966e152f16633a0e3e6d2432797cce6efee

Observation b042da31-450c-4486-ae65-011ae2f67aec · inbound

RAG-DIVE: A Dynamic Approach for Multi-Turn Dialogue Evaluation in Retrieval-Augmented Generation cites this paper.

RAG-DIVE: A Dynamic Approach for Multi-Turn Dialogue Evaluation in Retrieval-Augmented Generation Searching for Best Practices in Retrieval-Augmented Generation

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-16T09:17:40.321700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T09:13:55.204404Z digest=sha256:5a0f9e530be1458616fb6364f62b79f298c9d0d22d65d16e6fbf9a54c5014e0e

Observation 58083f60-24a0-41e2-8128-db51cb4495a7 · inbound

Not All RAGs Are Created Equal: A Component-Wise Empirical Study for Software Engineering Tasks cites this paper.

Not All RAGs Are Created Equal: A Component-Wise Empirical Study for Software Engineering Tasks Searching for Best Practices in Retrieval-Augmented Generation

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:53:28.524252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T01:52:53.116772Z digest=sha256:f40d2b38a96e9d1a533fe71d9fa2269afd6f608be18af62f000a47d4814c373e

Observation 8b49e204-05ca-455a-9ba4-f60130388cd2 · inbound

Is Grep All You Need? How Agent Harnesses Reshape Agentic Search cites this paper.

Is Grep All You Need? How Agent Harnesses Reshape Agentic Search Searching for Best Practices in Retrieval-Augmented Generation

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-15T03:08:58.257805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T03:07:26.498202Z digest=sha256:b1674422c241b0c4fed1155ffac7a9e4b9703df9e197cdf54e87aba492ad2e2a

Observation 0139c653-0c14-4241-aa80-cc18dad6e8f4 · inbound

Inference Cost Attacks for Retrieval-Augmented Large Language Models cites this paper.

Inference Cost Attacks for Retrieval-Augmented Large Language Models Searching for Best Practices in Retrieval-Augmented Generation

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-06-28T17:02:24.521367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T16:55:50.702951Z digest=sha256:e1845ace14829e8c2477ce80f527fa03d35c08d44933b7c6b1cfcba82162074e

Observation f81e1d55-a4fc-4597-be1e-ef8e3a1eacfb · inbound

Qiskit Code Migration with LLMs cites this paper.

Qiskit Code Migration with LLMs Searching for Best Practices in Retrieval-Augmented Generation

Reference 101

Resolution
verified exact
arxiv_id, observed 2026-06-26T16:29:35.727427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-26T16:24:25.357338Z digest=sha256:760301bd539c7d4bf7b3933a67c85f0699a86de10a50059cdcf096088b6e55a2

Observation be0c49d7-bc3a-4562-a797-c9e367cbe447 · inbound

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling cites this paper.

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling Searching for Best Practices in Retrieval-Augmented Generation

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-29T19:03:51.881183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-29T04:59:00.304723Z digest=sha256:5393c5f118e53f6187d6a9da62d06f69d24264d320c8488c89e5d7848b446636