Paper Citation Record · LEDGER

QuRating: Selecting High-Quality Data for Training Language Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2402.09739.

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

pith.paper-citation-record.v1
2402.09739 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:10:55.615594Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:18:54.736613Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 8f757b88-4eec-45e2-a1bf-77dd0261d419 · inbound

InternLM2 Technical Report cites this paper.

InternLM2 Technical Report QuRating: Selecting High-Quality Data for Training Language Models

Reference 88

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T11:44:38.290169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8d2cf921-3ca6-4c58-97ce-1c58da76e6ec · inbound

A Survey on Large Language Models for Code Generation cites this paper.

A Survey on Large Language Models for Code Generation QuRating: Selecting High-Quality Data for Training Language Models

Reference 287

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:18:06.815784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 412dddb6-e0a4-4dcc-9279-9fcf96d50a90 · inbound

DataComp-LM: In search of the next generation of training sets for language models cites this paper.

DataComp-LM: In search of the next generation of training sets for language models QuRating: Selecting High-Quality Data for Training Language Models

Reference 195

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T22:58:17.302685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a6d65f44-e795-43de-a1d8-c71c220a2dec · inbound

ProSec: Fortifying Code LLMs with Proactive Security Alignment cites this paper.

ProSec: Fortifying Code LLMs with Proactive Security Alignment QuRating: Selecting High-Quality Data for Training Language Models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T17:10:55.615594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e9b78f1-6e8f-426f-88ca-371fd5b4f85f · 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 QuRating: Selecting High-Quality Data for Training Language Models

Reference 211

Resolution: unresolved; no resolver link, observed 2026-08-11T22:57:02.085759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d999cc0-924f-401b-92b1-27c85c2d0ee2 · inbound

Weak-to-Strong Generalization Through the Data-Centric Lens cites this paper.

Weak-to-Strong Generalization Through the Data-Centric Lens QuRating: Selecting High-Quality Data for Training Language Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T22:06:28.530674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3bccff9-ea00-48d3-a331-ff3b9315da16 · inbound

Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights cites this paper.

Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights QuRating: Selecting High-Quality Data for Training Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T21:02:00.883462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44464480-61a9-4b3e-a21c-055ea8216edc · inbound

Optimizing Pretraining Data Mixtures with LLM-Estimated Utility cites this paper.

Optimizing Pretraining Data Mixtures with LLM-Estimated Utility QuRating: Selecting High-Quality Data for Training Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T18:00:05.091466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55dfd1c6-7e30-49b7-ace6-f1c89c901824 · inbound

PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts cites this paper.

PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts QuRating: Selecting High-Quality Data for Training Language Models

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-08T16:20:38.403659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f315cbc0-8d87-4f8f-81a5-ed74cc1a313f · inbound

Enhancing LLMs via High-Knowledge Data Selection cites this paper.

Enhancing LLMs via High-Knowledge Data Selection QuRating: Selecting High-Quality Data for Training Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:04.140161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1debfe81-31f3-4173-9bf5-783109667a66 · inbound

SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis cites this paper.

SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis QuRating: Selecting High-Quality Data for Training Language Models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T11:35:47.179506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 290c994f-6f21-4700-9db7-cf29e9336f1d · inbound

Time To Impeach LLM-as-a-Judge: Programs are the Future of Evaluation cites this paper.

Time To Impeach LLM-as-a-Judge: Programs are the Future of Evaluation QuRating: Selecting High-Quality Data for Training Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T04:34:09.115749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22547dd7-86c5-417b-91b3-1093554466e4 · inbound

LLM Data Selection and Utilization via Dynamic Bi-level Optimization cites this paper.

LLM Data Selection and Utilization via Dynamic Bi-level Optimization QuRating: Selecting High-Quality Data for Training Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T15:21:58.039374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f71f9222-a991-4346-b00f-6b81fd770bdf · inbound

BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining cites this paper.

BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining QuRating: Selecting High-Quality Data for Training Language Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-04T11:16:14.661866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d20d0a03-a512-4361-babe-7be14fa90ff2 · inbound

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels cites this paper.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels QuRating: Selecting High-Quality Data for Training Language Models

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T08:41:08.344219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2ba2b4b1-181a-4c67-aad5-c3fe809936dd · inbound

An Empirical Study on Influence-Based Pretraining Data Selection for Code Large Language Models cites this paper.

An Empirical Study on Influence-Based Pretraining Data Selection for Code Large Language Models QuRating: Selecting High-Quality Data for Training Language Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:16:04.558118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 02bcdd64-91a9-4893-9093-8200f7e4eb2c · inbound

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code cites this paper.

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code QuRating: Selecting High-Quality Data for Training Language Models

Reference 134

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:26:04.575591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 707067e8-c56a-445a-acae-50cf82b1f232 · inbound

Unified Data Selection for LLM Reasoning cites this paper.

Unified Data Selection for LLM Reasoning QuRating: Selecting High-Quality Data for Training Language Models

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-22T05:34:39.996586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 576fbebc-0fe0-4b8e-ab87-a90d1287d56c · inbound

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

DRIFT: Refining Instruction Data via On-Policy Data Attribution QuRating: Selecting High-Quality Data for Training Language Models

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-03T19:18:54.738254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e8c41971-b1b2-4a4d-ab55-035f0385311d · inbound

HERMES: A Multi-Granularity Labeling Substrate for Pre-training Data Mixtures cites this paper.

HERMES: A Multi-Granularity Labeling Substrate for Pre-training Data Mixtures QuRating: Selecting High-Quality Data for Training Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:48:39.419653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8a4bba88-7a4f-4b5c-b9e0-987ea6a9ec2b · inbound

DataPrep-Bench: Benchmarking LLMs as Training Data Preparators cites this paper.

DataPrep-Bench: Benchmarking LLMs as Training Data Preparators QuRating: Selecting High-Quality Data for Training Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T13:43:29.427294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b8f4a6c-9809-4b7a-b3b9-2834d9d097df · inbound

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data cites this paper.

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data QuRating: Selecting High-Quality Data for Training Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-31T07:01:44.329991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.