Paper Citation Record · LEDGER

MoDS: Model-oriented Data Selection for Instruction Tuning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2311.15653.

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

pith.paper-citation-record.v1
2311.15653 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:13.031651Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:07:36.851193Z

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 976e3530-1f39-4120-b463-541ccb795faf · inbound

NVILA: Efficient Frontier Visual Language Models cites this paper.

NVILA: Efficient Frontier Visual Language Models MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-05-23T07:42:43.091735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c3bb6a7c-123a-4557-91b0-7405ff36a7e1 · 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 MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 105

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T08:02:23.945355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6a76be25-945e-4607-bc00-8c7b1c55cfd1 · inbound

A Survey of LLM $\times$ DATA cites this paper.

A Survey of LLM $\times$ DATA MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 126

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:13.031651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c75b3534-689f-4481-899d-f695a8e51882 · inbound

Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition cites this paper.

Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:12.857648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 710484db-8632-42f5-8d21-7c052288458a · inbound

From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning cites this paper.

From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:18:35.076667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a95737c2-ff48-4f42-ae82-28597335bc0e · inbound

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs cites this paper.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:43.389554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 800f6515-9b60-4c4a-8258-06dbde6f080b · inbound

Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning cites this paper.

Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T14:13:47.664410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c6005bb-6faf-4a17-99c6-11629a656cc0 · inbound

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression cites this paper.

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T12:52:01.002494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 684eab1d-0b66-41c2-a5bc-abde8a3e0001 · inbound

MADS: Model-Aware Diverse Core Set Selection for Instruction Tuning cites this paper.

MADS: Model-Aware Diverse Core Set Selection for Instruction Tuning MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-01T19:16:01.035498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2ec530ac-58d9-427c-a2a6-01bd5b4bf00c · inbound

Dynamic Proxy-Mixing: Transferring Replay Controllers from Small to Large Models for Continual Instruction Tuning cites this paper.

Dynamic Proxy-Mixing: Transferring Replay Controllers from Small to Large Models for Continual Instruction Tuning MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:02:46.609536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d87d8d73-aed0-4292-a8ce-37fc28b54d4e · inbound

Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey cites this paper.

Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 87

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:07:36.852543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.