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Paper Citation Record · LEDGER

D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2503.11441.

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

pith.paper-citation-record.v1
2503.11441 v2

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 2026-08-19T06:32:44.657259+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:39:31.334337Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:18:54.714750Z

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 00e351dc-dc67-4171-9ccd-3b5fa1d12ec5 · inbound

DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training cites this paper.

DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-16T10:39:31.334337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:39:31.334337Z digest=sha256:a1556c8c66da7578ff3f3080f37d00990d38e621d2d5afcd70f8f1fd0ff5dd51

Observation 52d023e3-a318-4e59-a67a-7dd08e6b49f0 · inbound

Text2Cypher: Data Pruning using Hard Example Selection cites this paper.

Text2Cypher: Data Pruning using Hard Example Selection D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T23:16:58.171151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:16:58.171151Z digest=sha256:06f3ce9e18d62d12f707749a3d1764ef21eb78413b74de24ba79a5bdc16dfb2d

Observation 903b6c40-3d1b-44e8-b7aa-b55195d09203 · inbound

Rethinking Expert Trajectory Utilization in LLM Post-training for Mathematical Reasoning cites this paper.

Rethinking Expert Trajectory Utilization in LLM Post-training for Mathematical Reasoning D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-16T22:43:37.862856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-16T22:43:01.937642Z digest=sha256:aebe7ab41d15b10895e00249ad867ae402a81a07860c66fb4c2f417860946428

Observation 661475a5-5cc7-46b9-8551-59154d25d68a · inbound

Learning to Adapt SFT Data for Better Reasoning Generalization cites this paper.

Learning to Adapt SFT Data for Better Reasoning Generalization D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T18:23:51.103620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-29T18:14:22.896656Z digest=sha256:eac2810d00ca11d6f77d9899f6e4e548dc6311ed97815edddd43eca6ada82278

Observation 892db32d-4303-4e73-8c36-e20d23251fed · inbound

DRIFT: Refining Instruction Data via On-Policy Data Attribution cites this paper.

DRIFT: Refining Instruction Data via On-Policy Data Attribution D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-03T19:18:54.716387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T01:57:05.784589Z digest=sha256:d7b0a34216812fc0aa2644c79755f9d1a4667322bd14babc21c2b40405fa2dc0