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Paper Citation Record · LEDGER

Tree Prompting: Efficient Task Adaptation without Fine-Tuning

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.14034.

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

pith.paper-citation-record.v1
2310.14034 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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:23:10.297250Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:23:11.584450Z

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 fee785b2-703e-4e63-96e4-211f0974653e · inbound

Random Rule Forest (RRF): Interpretable and Manageable Ensembles of LLM-Generated Questions for Predicting Success from Unstructured Data cites this paper.

Random Rule Forest (RRF): Interpretable and Manageable Ensembles of LLM-Generated Questions for Predicting Success from Unstructured Data Tree Prompting: Efficient Task Adaptation without Fine-Tuning

Reference 2025

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T12:23:11.622635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:23:10.297250Z digest=sha256:8d9d4e86b32912c3337b43b957ef058fde0681676215cf627176f75e1914cdc1

Observation 3fb4b496-45f2-4177-844e-f3142d249ff7 · inbound

Data-Efficient Adaptation of LLMs via Attention Head Reweighting cites this paper.

Data-Efficient Adaptation of LLMs via Attention Head Reweighting Tree Prompting: Efficient Task Adaptation without Fine-Tuning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-02T05:16:36.544435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:16:36.544435Z digest=sha256:427741313e4eb9c99912bdb2f40641766c0e54a3e36f612fb779979519f98359