Paper Citation Record · LEDGER

In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning

As of 18 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 4 inbound Pith citation observations for arXiv:2412.13243.

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

pith.paper-citation-record.v1
2412.13243 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:25:28.925998Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:13:38.924089Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T14:43:22.160745Z

Reference resolution

7 of 7 outbound references displayed

verified exact0
verified fuzzy0
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation abb1632b-fdbe-46f2-bd10-bea6910df7eb · outbound

This paper cites write newline.

In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T13:25:28.893991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59b66219-cfc1-482b-aa8b-274afd36ba25 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning LoRA: Low-Rank Adaptation of Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T13:25:28.901477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79c49ed9-bd6e-4914-a495-3adea0ec4ed1 · outbound

This paper cites Full Parameter Fine-tuning for Large Language Models with Limited Resources.

In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning Full Parameter Fine-tuning for Large Language Models with Limited Resources

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T13:25:28.906352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08a1a6bc-7e13-4c78-895b-40919d41efff · outbound

This paper cites Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation.

In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T13:25:28.911080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea039472-5f86-438a-b025-4c12b6a6c08a · outbound

This paper cites Learning by Distilling Context.

In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning Learning by Distilling Context

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T13:25:28.916202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4539b37-cb7c-4e1c-bcab-81204fb12999 · outbound

This paper cites A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference.

In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T13:25:28.920836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fcf8c6d-e68c-42d4-8c97-35f31d579b4a · outbound

This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.

In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T13:25:28.925998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 830b141c-608c-4e24-b460-41728c4a8649 · inbound

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes cites this paper.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:38.924089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 605531b5-d9b5-4a88-a6ce-73c1cc402a66 · inbound

Chain-based Distillation for Effective Initialization of Variable-Sized Small Language Models cites this paper.

Chain-based Distillation for Effective Initialization of Variable-Sized Small Language Models In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning

Reference 78

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:40:54.030810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation da853add-376c-4c13-8f01-36b6f3571c98 · inbound

Self-Supervised On-Policy Distillation for Reasoning Language Models cites this paper.

Self-Supervised On-Policy Distillation for Reasoning Language Models In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning

Reference 111

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:43:22.163699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d25eefd2-f16f-4acc-8369-6452d37912ab · inbound

Sample-Efficient Learning from Agent Experience cites this paper.

Sample-Efficient Learning from Agent Experience In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-01T08:43:20.905414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.