Paper Citation Record · LEDGER

Instruction Mining: Instruction Data Selection for Tuning Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2307.06290.

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

pith.paper-citation-record.v1
2307.06290 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 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 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:09:33.588670Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:49:17.695166Z

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 42bb65dc-b14d-4987-9e6b-99e210376ade · inbound

MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets cites this paper.

MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-24T08:14:10.175046Z

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 d84fe3e4-cad7-4bb8-9fc6-41793cf5e71c · inbound

Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models cites this paper.

Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T14:21:16.542943Z

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 663ff74e-816e-4d2d-b2e6-29d3f9ee6239 · inbound

AutoSpatial: Visual-Language Reasoning for Social Robot Navigation through Efficient Spatial Reasoning Learning cites this paper.

AutoSpatial: Visual-Language Reasoning for Social Robot Navigation through Efficient Spatial Reasoning Learning Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-23T00:27:17.816053Z

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 19e4d153-5cdb-476e-96c9-1d8cd985172b · inbound

Merge to Mix: Mixing Datasets via Model Merging cites this paper.

Merge to Mix: Mixing Datasets via Model Merging Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:33.588670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11863cfa-4401-49d1-bde0-355e87d328c5 · inbound

Walk&Retrieve: Simple Yet Effective Zero-shot Retrieval-Augmented Generation via Knowledge Graph Walks cites this paper.

Walk&Retrieve: Simple Yet Effective Zero-shot Retrieval-Augmented Generation via Knowledge Graph Walks Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:58:32.633147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16e7db2c-f332-4fa9-bbe5-5e83e1d9133f · inbound

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

A Survey of LLM $\times$ DATA Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:12.899936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99126653-6042-4339-a9fe-071207acb0c2 · inbound

TAG-INSTRUCT: Controlled Instruction Complexity Enhancement through Structure-based Augmentation cites this paper.

TAG-INSTRUCT: Controlled Instruction Complexity Enhancement through Structure-based Augmentation Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T14:32:13.530356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4553c525-29a0-4827-8eaf-0364a95e7b86 · inbound

Efficient Data Selection at Scale via Influence Distillation cites this paper.

Efficient Data Selection at Scale via Influence Distillation Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T14:25:21.464252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2e9f62e-708f-4c21-84bc-ea1c79d19ced · inbound

GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation cites this paper.

GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:00:29.600015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcf1a6d7-877f-4d33-8226-a98385e3554e · inbound

Towards Efficient and Effective Alignment of Large Language Models cites this paper.

Towards Efficient and Effective Alignment of Large Language Models Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:35.093796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08b7ce6f-70e8-4e2e-a172-63c699e58f94 · inbound

ClusterUCB: Efficient Gradient-Based Data Selection for Targeted Fine-Tuning of LLMs cites this paper.

ClusterUCB: Efficient Gradient-Based Data Selection for Targeted Fine-Tuning of LLMs Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T04:37:06.226403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f4c6a3d-937d-4a27-aa13-7b627447d7d4 · inbound

Rethinking Data Curation in LLM Training: Online Reweighting Offers Better Generalization than Offline Methods cites this paper.

Rethinking Data Curation in LLM Training: Online Reweighting Offers Better Generalization than Offline Methods Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T07:11:53.337299Z

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 c5140b54-8b76-4bc2-b6de-0770784267e3 · inbound

Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training cites this paper.

Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 123

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:05:56.776981Z

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 8fb8b7cc-7eab-476a-8ced-be9e00067922 · inbound

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

HARP: Efficient Data Selection for Finetuning Large Language Models Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T16:17:09.376334Z

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 23a3e80d-cb90-470b-b2e4-916a38cdbe6e · inbound

OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework cites this paper.

OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:07:27.187260Z

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 c43ee3e2-8d64-4b29-9e90-8c920ad234a8 · inbound

Predicting Mergeability of Parameter-Efficient Fine-Tuning Updates cites this paper.

Predicting Mergeability of Parameter-Efficient Fine-Tuning Updates Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 47

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T00:49:17.697551Z

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 fbf07f84-e4e4-41be-85f1-9f0fef4c3c2c · inbound

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement cites this paper.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T13:54:03.003356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.