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Paper Citation Record · LEDGER

LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2206.06565.

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

pith.paper-citation-record.v1
2206.06565 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T22:25:39.533017Z

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

35
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 2b1233ed-b654-4d7b-8e6d-9770a49457ff · inbound

Language Models (Mostly) Know What They Know cites this paper.

Language Models (Mostly) Know What They Know LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-10T15:42:47.552825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-10T15:42:47.274448Z digest=sha256:7d3eb2970691b5b186b05065363519c4dbdcfb402df656752a4f8d81c67c7560

Observation 593d6728-c93c-4809-a35e-c3126c9f16d6 · inbound

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold cites this paper.

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-10T14:00:29.128287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-10T13:57:36.981142Z digest=sha256:a2724114d95f0b33c4666054b7d998d19c612a87835b604645a0d62966a6ca44

Observation 9d407712-28da-4305-b6c9-7c57b2dc16be · inbound

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold cites this paper.

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-21T01:03:52.985120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-21T01:00:20.188501Z digest=sha256:3bf680b9eb6e529ab750eb7712e4e3da0e2b38b0598c79745b39612a2ce3c7ac

Observation 349b862e-0732-4771-a31a-ab3cbee2e63c · inbound

Collaborative Large and Small Language Models for Accurate and Scalable Data Repair cites this paper.

Collaborative Large and Small Language Models for Accurate and Scalable Data Repair LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-07-03T23:19:04.216486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-26T22:25:39.533017Z digest=sha256:669b6e0b0c48b7d69300154d81399abd89eb2b677db8054bd95e774ff64f636e