Paper Citation Record · LEDGER

Does RAG Really Perform Bad For Long-Context Processing?

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2502.11444.

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

pith.paper-citation-record.v1
2502.11444 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:47:14.618303Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T17:17:15.099136Z

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 80ab9fd9-ccb1-4f79-8347-88343e1095de · inbound

From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents cites this paper.

From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents Does RAG Really Perform Bad For Long-Context Processing?

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T18:47:14.618303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d9fd658-93e1-4e28-bab6-386601e6e3a2 · inbound

Cognitive Load-Aware Inference: A Neuro-Symbolic Framework for Optimizing the Token Economy of Large Language Models cites this paper.

Cognitive Load-Aware Inference: A Neuro-Symbolic Framework for Optimizing the Token Economy of Large Language Models Does RAG Really Perform Bad For Long-Context Processing?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T21:15:08.483177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00cd5b10-f30c-4791-bbbd-9f668479a221 · inbound

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search cites this paper.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Does RAG Really Perform Bad For Long-Context Processing?

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.726816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65ec54fd-fab7-4aad-84bf-aa1ddbc8cdb2 · inbound

EASE-TTT: Evidence-Aligned Selective Test-Time Training for Long-Context Question Answering cites this paper.

EASE-TTT: Evidence-Aligned Selective Test-Time Training for Long-Context Question Answering Does RAG Really Perform Bad For Long-Context Processing?

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-02T17:17:15.100358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.