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Paper Citation Record · LEDGER

ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.06683.

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

pith.paper-citation-record.v1
2405.06683 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:07:57.460567Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T02:15:55.436472Z

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 b3715c46-8f15-4306-b3c4-1060f22bfdc7 · 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 ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization

Reference 127

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:15:55.438792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-24T02:15:05.379583Z digest=sha256:b9a7a65e83dbbeed6b1beacc6c30c34b35e9745bf977919c26ba3975594602a1

Observation 67bf0ed9-fac6-4de0-b919-a9ca21621bd4 · inbound

SRSA: A Cost-Efficient Strategy-Router Search Agent for Real-world Human-Machine Interactions cites this paper.

SRSA: A Cost-Efficient Strategy-Router Search Agent for Real-world Human-Machine Interactions ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T15:12:03.281383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:12:03.281383Z digest=sha256:ac27e60f9c10db147a63f8da195671a72346ac69eafab1a2e06bc654f24a43e1

Observation bf24110f-a3b3-49ac-a790-f33c68a93423 · inbound

A Survey on Foundation Models for Personalized Federated Intelligence cites this paper.

A Survey on Foundation Models for Personalized Federated Intelligence ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization

Reference 134

Resolution
verified exact
arxiv_id, observed 2026-05-22T15:34:57.626858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-22T15:32:15.293888Z digest=sha256:b449c8b31a5078d40b58e9f09b0aab56a58dd0e6a9d250578d754153de069d3a

Observation 9b6695cf-93a2-4d3f-8ba2-51104e92d298 · inbound

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection cites this paper.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-15T18:07:57.460567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:07:57.460567Z digest=sha256:b099486155da0d4441edf97429cf81082551bcbc8dd3ca6e2bf4d37466977511

Observation 97fa33d6-7766-4798-9de7-ee1a62162705 · inbound

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models cites this paper.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-04T22:32:17.716695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:32:17.716695Z digest=sha256:20ebd4a7afdf2f4822e722794a600147642d445fec29a228128d0942f0197d44