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Paper Citation Record · LEDGER

Divide-or-Conquer? Which Part Should You Distill Your LLM?

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.15000.

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

pith.paper-citation-record.v1
2402.15000 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:16:23.964233Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T10:46:27.432549Z

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 6778df7f-d04e-4ec2-8bbc-c928b9f71c7d · inbound

LLMQuoter: Enhancing RAG Capabilities Through Efficient Quote Extraction From Large Contexts cites this paper.

LLMQuoter: Enhancing RAG Capabilities Through Efficient Quote Extraction From Large Contexts Divide-or-Conquer? Which Part Should You Distill Your LLM?

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T21:16:23.964233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:16:23.964233Z digest=sha256:3dc021181f276279b4e507d37163723ac94448211e645cec3e292ea659b2451f

Observation 3d564ee0-bfba-4f05-8291-494fa1280fcc · inbound

DeepRAG: Thinking to Retrieve Step by Step for Large Language Models cites this paper.

DeepRAG: Thinking to Retrieve Step by Step for Large Language Models Divide-or-Conquer? Which Part Should You Distill Your LLM?

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-09T16:31:17.719672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:31:17.719672Z digest=sha256:8079b8892d38be8f5a0e6e81fc3c3eccaee53f3a1f353c98ba7997a2287b25e3

Observation 44d6470d-98c6-4352-885e-fceb1a78b845 · inbound

SQLens: An End-to-End Framework for Error Detection and Correction in Text-to-SQL cites this paper.

SQLens: An End-to-End Framework for Error Detection and Correction in Text-to-SQL Divide-or-Conquer? Which Part Should You Distill Your LLM?

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:46:27.437933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T10:46:27.185579Z digest=sha256:c29cc2a40037fed5753380f23b5800248243eb3e527dd490d88ead231c333434