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Paper Citation Record · LEDGER

Failures Pave the Way: Enhancing Large Language Models through Tuning-free Rule Accumulation

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.15746.

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

pith.paper-citation-record.v1
2310.15746 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:18:35.830611Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T18:48:20.497474Z

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 e15215bb-2977-40be-9adc-111a73415858 · inbound

AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning cites this paper.

AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning Failures Pave the Way: Enhancing Large Language Models through Tuning-free Rule Accumulation

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-23T18:48:20.500200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-23T18:46:08.566035Z digest=sha256:fb442bb5358d98578cd048e65eb969dea63bab7043d2807c3e10bb6411c054ba

Observation 53543478-6a96-4a27-bf01-ae481adfb4ab · inbound

Error-driven Data-efficient Large Multimodal Model Tuning cites this paper.

Error-driven Data-efficient Large Multimodal Model Tuning Failures Pave the Way: Enhancing Large Language Models through Tuning-free Rule Accumulation

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-11T11:18:35.830611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:18:35.830611Z digest=sha256:a496f71560dbf18b945a2277cb0a87b8490a284aa7cfeef8519a50d4e67cac06