Paper Citation Record · LEDGER

True Few-Shot Learning with Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2105.11447.

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

pith.paper-citation-record.v1
2105.11447 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:30:37.676374Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T09:51:46.814778Z

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 1484da4f-83cf-4d2b-bf5c-e99205df7aca · inbound

TruthfulQA: Measuring How Models Mimic Human Falsehoods cites this paper.

TruthfulQA: Measuring How Models Mimic Human Falsehoods True Few-Shot Learning with Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:48:54.083348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 176ea74c-d3f3-4fb8-b982-82ce5cbb0144 · inbound

Multitask Prompted Training Enables Zero-Shot Task Generalization cites this paper.

Multitask Prompted Training Enables Zero-Shot Task Generalization True Few-Shot Learning with Language Models

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T17:59:43.174482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c21ec792-3439-4a38-8490-11727e403769 · inbound

Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? cites this paper.

Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? True Few-Shot Learning with Language Models

Reference 116

Resolution: verified exact; arxiv_id, observed 2026-05-15T09:51:46.817506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b40ca333-228e-4251-a0e6-7fe7966be0fe · inbound

OPT: Open Pre-trained Transformer Language Models cites this paper.

OPT: Open Pre-trained Transformer Language Models True Few-Shot Learning with Language Models

Reference 207

Resolution: verified exact; arxiv_id, observed 2026-05-10T20:53:17.701771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c18340f9-43f3-4173-a61c-0cafce8f58cb · inbound

Improve Mathematical Reasoning in Language Models by Automated Process Supervision cites this paper.

Improve Mathematical Reasoning in Language Models by Automated Process Supervision True Few-Shot Learning with Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:53:45.957883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7cb1a54f-7ddf-4318-a0d4-af93f81011e7 · inbound

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection cites this paper.

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection True Few-Shot Learning with Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:30:37.676374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b41dbc4b-eac9-4d62-86be-23646dec4b55 · inbound

UNH at CheckThat! 2025: Fine-tuning Vs Prompting in Claim Extraction cites this paper.

UNH at CheckThat! 2025: Fine-tuning Vs Prompting in Claim Extraction True Few-Shot Learning with Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T23:01:12.801916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.