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Paper Citation Record · LEDGER

Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2408.02085.

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

pith.paper-citation-record.v1
2408.02085 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:51:04.979136Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T12:47:45.751718Z

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 61fef1a7-5cf8-4b76-97b3-7abadd6a723c · inbound

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models cites this paper.

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models

Reference 156

Resolution
unresolved
no resolver link, observed 2026-08-11T22:57:01.927485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:57:01.927485Z digest=sha256:5ce865b73fe4ef6861b901cceb39fcd1bd73e5b0a5b749f4aa2232f762d1b8b9

Observation 9ab72358-ae4e-45c2-9fd3-d6a38806eb9b · inbound

The Rise of Small Language Models in Healthcare: A Comprehensive Survey cites this paper.

The Rise of Small Language Models in Healthcare: A Comprehensive Survey Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models

Reference 149

Resolution
unresolved
no resolver link, observed 2026-08-16T10:51:04.979136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:51:04.979136Z digest=sha256:a5889022a717ff8735e4cff115cd712a0822d4eddc053ca67da466017bb37eab

Observation 0ed18429-cc97-4c8d-8a07-a528985879f7 · inbound

Team QUST at SemEval-2025 Task 10: Evaluating Large Language Models in Multiclass Multi-label Classification of News Entity Framing cites this paper.

Team QUST at SemEval-2025 Task 10: Evaluating Large Language Models in Multiclass Multi-label Classification of News Entity Framing Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T04:31:14.360627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:31:14.360627Z digest=sha256:0ddcc211833ae82244c6d2c3f13ceaf4e9fda5c226715b5b7b3cc63eba76d02c

Observation dad7c16c-6a39-4ac4-98de-16b4ad4dece7 · inbound

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

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:47:45.791893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.314157Z digest=sha256:582c91bcd6881e6cec3cda06004d18289bee868f642df3b4304fb4c3f3f340e2

Observation 2e9fd5d5-910f-467f-a801-54427e977b73 · 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 Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-01T13:54:04.220890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T13:54:04.220890Z digest=sha256:042ae90058095aad941412ac47d9b85ee53d5d14540d816bdf54b8601040890b