Paper Citation Record · LEDGER

MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2406.06046.

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

pith.paper-citation-record.v1
2406.06046 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:21:56.521904Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:48:39.405954Z

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 f3e0ccfe-6668-4d09-b5f5-7a27ce0e6b6c · inbound

RefineX: Learning to Refine Pre-training Data at Scale from Expert-Guided Programs cites this paper.

RefineX: Learning to Refine Pre-training Data at Scale from Expert-Guided Programs MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T20:21:56.521904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c91ef90a-3734-44ab-832d-846d511e3051 · inbound

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

LLM Data Selection and Utilization via Dynamic Bi-level Optimization MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T15:21:58.101569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ac98bfb-6693-4547-848f-59cec9b21172 · 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 MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-04T11:16:15.281996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 668e404a-e66a-4f73-8486-a25ecaa60f98 · inbound

GradAlign: Gradient-Aligned Data Selection for LLM Reinforcement Learning cites this paper.

GradAlign: Gradient-Aligned Data Selection for LLM Reinforcement Learning MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T21:05:26.804742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05bae7ed-8f67-43e1-87cf-22af4b88def0 · inbound

Efficient Dataset Selection for Continual Adaptation of Generative Recommenders cites this paper.

Efficient Dataset Selection for Continual Adaptation of Generative Recommenders MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:16:03.771646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d6b18352-4ab4-49ea-87fd-1b67c952ec14 · 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 MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:16:04.521623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c1e8c891-7e22-489a-89ba-d09753bbf189 · inbound

GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization cites this paper.

GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 80

Resolution: malformed identifier; arxiv_id, observed 2026-05-11T05:30:57.980667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 030ce241-3d36-4241-873b-1a6b7690c8b4 · inbound

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation cites this paper.

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 57

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T08:48:00.969572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1205b449-a336-4516-8c77-888553e55417 · inbound

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation cites this paper.

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-02T16:12:13.358123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3ced776-83bb-45e9-a0c6-bb99289f2fde · 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 MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:48:39.407393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.