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Paper Citation Record · LEDGER

DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2505.07233.

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

pith.paper-citation-record.v1
2505.07233 v2

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 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T10:20:20.991380Z

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

0
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 5f25fbd1-4f95-44fc-8cd2-0267dda19230 · inbound

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation cites this paper.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-04T10:20:20.991380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:20:20.991380Z digest=sha256:1df0b8927de9ae6f9a1f963746bd9984708fc956cb962f64d84c9d563875b6a5

Observation c5c6cba6-58a2-4529-a767-ee34a853a36c · inbound

Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning cites this paper.

Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-13T13:59:01.287449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T13:59:01.287449Z digest=sha256:3b1b5c30460cf8aab8d5d241c741ed265db063480fd121ac0a31b2f7bb891bb0

Observation 63a72e2d-e962-4c9c-ab36-e4f399c4fd73 · inbound

Active Learners as Efficient PRP Rerankers cites this paper.

Active Learners as Efficient PRP Rerankers DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:43:27.227839Z

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=arxiv_source observed=2026-05-15T01:43:10.436537Z digest=sha256:773eb00911307d077d4863a5997ea6177f9c52fe8e8a8f6b73a60afe12e8f5df

Observation afe64bb5-0998-41c4-b816-5a7138231377 · inbound

Active Learners as Efficient PRP Rerankers cites this paper.

Active Learners as Efficient PRP Rerankers DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:09:02.442786Z

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=arxiv_source observed=2026-05-20T21:07:32.652880Z digest=sha256:4fa0936dd4722fa4d4adbbbd1783ca7e784942926931fcb2365f53fec5f79beb