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Paper Citation Record · LEDGER

Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 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 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:51:30.545051Z

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 ffa12b22-71a1-4c10-9fa3-88efaa20d286 · inbound

Mastering Collaborative Multi-modal Data Selection: A Focus on Informativeness, Uniqueness, and Representativeness cites this paper.

Mastering Collaborative Multi-modal Data Selection: A Focus on Informativeness, Uniqueness, and Representativeness Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-11T19:54:52.051309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:54:52.051309Z digest=sha256:5ccd15b4724b62c9c15fda26e5eb17fa8f4853dc9a02b3ac45eef10b8b545093

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.

source=arxiv_source observed=2026-08-08T11:57:12.021189Z digest=sha256:416ac55648917ef5101bd9234d6cf00301fae3a635f29c23f9e061a487fb40ad

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-19T08:02:23.002090Z digest=sha256:ab821b29e514b7c906444c183c30a797e4293f79265edbdf44e2e911567f0139

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:22cb28354e55348f271121fe13cf2ccf3d4f646e8e4d02f3bed91dd6fabfc79f

Observation ed84f166-8d59-4bd5-a3e6-1159accd51c1 · inbound

Vendi Information Gain: An Alternative To Mutual Information For Science And Machine Learning cites this paper.

Vendi Information Gain: An Alternative To Mutual Information For Science And Machine Learning Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-15T21:51:30.545051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:51:30.545051Z digest=sha256:1ec9ea048ca3165d2ca94e084d893e5a3caa956bb51a225d85895b1c64a9a6e8

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-21T23:46:24.208438Z digest=sha256:98a14f1e4ce9aecd9f94045173e1e41d0fd699d1ea780dd480951fb1e7678d1d

Observation 14e13088-dd88-4c53-930c-065cc08b1a20 · inbound

ReSURE: Regularizing Supervision Unreliability for Multi-turn Dialogue Fine-tuning cites this paper.

ReSURE: Regularizing Supervision Unreliability for Multi-turn Dialogue Fine-tuning Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-15T16:53:23.892270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:53:23.892270Z digest=sha256:f537ee08fe303f8a5c015e6bfba1e74e08cd035dbc378a1516d4c1d1a56fb255

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-22T06:25:06.024542Z digest=sha256:86e3110995c6c6ae4995f20cb36e34687cf88f8ae3f32598f455ac20f1bc1db8

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-27T22:49:48.330530Z digest=sha256:68dffb666cf54a7a923ee5bc4120621bab0b8b727e75592c6499acccf6b074a0