Paper Citation Record · LEDGER

Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2311.08182.

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

pith.paper-citation-record.v1
2311.08182 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:57:12.021189Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:17:09.384028Z

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 f622c6a1-b7c3-4f5a-8aca-07d4679662ef · inbound

Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples cites this paper.

Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-08T11:57:12.021189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b3012be-c414-4d6c-81bb-f3c4215a930a · inbound

Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model cites this paper.

Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 102

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T08:02:23.909152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b9297f4f-b6dd-4f5f-bbbb-21083cfbbe58 · inbound

Large Language Model Agent: A Survey on Methodology, Applications and Challenges cites this paper.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:52:10.087202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f58a847f-fddd-486a-868e-8af70fe372ff · inbound

Difficulty-Based Preference Data Selection by DPO Implicit Reward Gap cites this paper.

Difficulty-Based Preference Data Selection by DPO Implicit Reward Gap Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:50:47.652495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation adc29add-8578-4dc3-8e57-32075f942b0f · inbound

SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations cites this paper.

SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:26:10.013887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7279cd2a-1805-4f0b-b9bc-3bf1ec873603 · inbound

HARP: Efficient Data Selection for Finetuning Large Language Models cites this paper.

HARP: Efficient Data Selection for Finetuning Large Language Models Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T16:17:09.385667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.