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Paper Citation Record · LEDGER

CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.04302.

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

pith.paper-citation-record.v1
2404.04302 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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:35:30.074525Z

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

4
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 5c6842e3-29d3-4bae-9feb-36e7a3f8c845 · inbound

Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoning cites this paper.

Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoning CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-08T11:35:30.074525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T11:35:30.074525Z digest=sha256:5118b92ee8bb062bba444a82336525dbf71f72d19803a0f234528e9a703bbe33

Observation 0660c8e3-54a6-4a97-a154-661a34964098 · inbound

Learning When Not to Decide: A Framework for Overcoming Factual Presumptuousness in AI Adjudication cites this paper.

Learning When Not to Decide: A Framework for Overcoming Factual Presumptuousness in AI Adjudication CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-10T02:11:57.313750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T02:08:24.770003Z digest=sha256:b0850c5a67ae5a0854a6595bcbdff21abe480c0331afb0162f6c14d5c2eef6b4

Observation aba422c5-62a7-498d-ae17-f694a45f251d · inbound

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters cites this paper.

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:07:16.991251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T05:04:05.567756Z digest=sha256:fc6b73e64187e391a00598d9067682306f14ef10868bcb0b8080525a666c0dd4

Observation af5ee3f3-bff6-42ee-aef7-642067a52ce0 · inbound

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters cites this paper.

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:03:47.042217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T22:01:57.997948Z digest=sha256:aca740cb8fc62fa2fed00347305df428c5822405979ef574f3611a42046fc419

Observation af9a5c4e-620f-4e10-9670-226eac5a1315 · inbound

Towards Persistent Case-Based Memory for Autonomous Data Science: A CBR-Augmented R&D-Agent with a Locally Deployable Small Language Model cites this paper.

Towards Persistent Case-Based Memory for Autonomous Data Science: A CBR-Augmented R&D-Agent with a Locally Deployable Small Language Model CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T10:06:51.704792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T05:19:14.975753Z digest=sha256:df28569a25f6e85ec66238bbe993cb90b2728bd6615f469847d2f40d0af6538c