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Paper Citation Record · LEDGER

Long Context RAG Performance of Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2411.03538.

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

pith.paper-citation-record.v1
2411.03538 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:45:12.477922Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T12:34:38.858375Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation fd5ee21f-c993-4e70-8c09-0c560372048b · inbound

LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework cites this paper.

LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework Long Context RAG Performance of Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T19:45:12.477922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:45:12.477922Z digest=sha256:25d42d3db3f227b1e42dd3f0ae2768e07c0390c798fa60b1bc29f541f0343965

Observation 8d24e04b-5c05-4f81-8347-4c434e4ca36f · inbound

Agent Identity Evals: Measuring Agentic Identity cites this paper.

Agent Identity Evals: Measuring Agentic Identity Long Context RAG Performance of Large Language Models

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-06T14:57:06.923301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:57:06.923301Z digest=sha256:0c71d38ed533d0493a280559bf88c84cf6840848cf29b9b134e5dd819ae4844a

Observation 2ceedd2a-2e2e-4eaf-99a3-7e0fb54901c7 · inbound

Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs cites this paper.

Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs Long Context RAG Performance of Large Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-03T12:42:32.334383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T12:42:32.334383Z digest=sha256:78cc37b819cdde03d682fbab06fe5a48a236f31c4580e9f92cafcf2ad5632ce1

Observation fa81a8e2-2d32-4862-bfdc-04712d4ec644 · inbound

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure cites this paper.

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure Long Context RAG Performance of Large Language Models

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:26:00.602284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T14:59:05.826933Z digest=sha256:650ed71ff49c2ceb9bd726f599917eb4cc92652afd2e7a71080a8f12e2f92abd

Observation 121d55d7-b8a7-4e99-8db6-cee6d8bde2e2 · inbound

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure cites this paper.

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure Long Context RAG Performance of Large Language Models

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-25T06:26:41.317769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-25T06:26:27.908346Z digest=sha256:8bab173c54b26029e9cffc014ad3c69f8e28b7d1445810dd922459c7bffa6302

Observation a3f82fb7-3b90-41bd-9718-984649734de1 · inbound

MuMuTestUp: Mutation-based Multi-Agent Test Case Update cites this paper.

MuMuTestUp: Mutation-based Multi-Agent Test Case Update Long Context RAG Performance of Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-20T05:08:05.314324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T05:03:20.704001Z digest=sha256:7ea453ea5c1cb8539ffae037142f3bbb5de5890afaa8e739433bfcea68c35538

Observation 3bafd783-5e13-4487-9a76-4810533ee20b · inbound

MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration cites this paper.

MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration Long Context RAG Performance of Large Language Models

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-30T12:34:38.859890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T12:27:46.629948Z digest=sha256:0edcf95604c56043d1a8e6c01e7c02e1cd4e74f38509ee7824482f819abc9c26

Observation a334f36e-3a8c-4f1b-ae75-439b1f71b487 · inbound

Replicating Belief, Not Bits: Epistemic State Replication for Agentic Systems cites this paper.

Replicating Belief, Not Bits: Epistemic State Replication for Agentic Systems Long Context RAG Performance of Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-07-14T16:32:10.501693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T16:32:10.501693Z digest=sha256:f1cc28d8786f7723b4a8a5f063dc5dea29856c7e7e079f9bc126c16b189373a5

Observation 280d7c0e-8be9-40d6-ab6b-e1dd23b86994 · inbound

Evidence Interfaces Shape How Retrieval-Augmented Readers Use Support cites this paper.

Evidence Interfaces Shape How Retrieval-Augmented Readers Use Support Long Context RAG Performance of Large Language Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-01T19:03:37.218389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T19:03:37.218389Z digest=sha256:997ee671e66a6d775491c23b33048df787f417499ff51e5f3485d8748584ec93