Paper Citation Record · LEDGER

Domain-Aware Scaling Laws Uncover Data Synergy

As of 22 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 1 inbound Pith citation observation for arXiv:2607.11052.

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

pith.paper-citation-record.v1
2607.11052 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T07:24:27.255815Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T03:01:55.410116Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

verified exact0
verified fuzzy0
unresolved45
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3e048f62-6b6f-4400-8b2b-d3e2ad5bbfd5 · outbound

This paper cites To Code, or Not To Code? Exploring Impact of Code in Pre-training.

Domain-Aware Scaling Laws Uncover Data Synergy To Code, or Not To Code? Exploring Impact of Code in Pre-training

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 428fe963-08f2-409f-be88-ae350776eb01 · outbound

This paper cites Program Synthesis with Large Language Models.

Domain-Aware Scaling Laws Uncover Data Synergy Program Synthesis with Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ec57828-cf92-4bd4-abe0-f3f2c6515671 · outbound

This paper cites Llemma: An Open Language Model For Mathematics.

Domain-Aware Scaling Laws Uncover Data Synergy Llemma: An Open Language Model For Mathematics

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f7f26dd-1441-478a-a4bf-c3ca51b34cf6 · outbound

This paper cites If you use this software, please cite it using these metadata.

Domain-Aware Scaling Laws Uncover Data Synergy If you use this software, please cite it using these metadata

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac82df56-db89-45b6-bb1e-0f5136fdde42 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Domain-Aware Scaling Laws Uncover Data Synergy Evaluating Large Language Models Trained on Code

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7d168f5-0b4d-45ec-af45-536721d007aa · outbound

This paper cites Aioli: A Unified Optimization Framework for Language Model Data Mixing.

Domain-Aware Scaling Laws Uncover Data Synergy Aioli: A Unified Optimization Framework for Language Model Data Mixing

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df7f5100-f438-4c5b-b4d9-1e37d02a076a · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Domain-Aware Scaling Laws Uncover Data Synergy Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72393667-e240-4e25-8e7e-ad8f20e54c82 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Domain-Aware Scaling Laws Uncover Data Synergy Training Verifiers to Solve Math Word Problems

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fb9d776-39d0-466a-a260-cb4db8ecd4cd · outbound

This paper cites Albert Ge, Tzu-Heng Huang, John Cooper, Avi Trost, Ziyi Chu, Satya Sai Srinath Namburi GNVV , Ziyang Cai, Kendall Park, Nicholas Roberts, and Frederic Sala.

Domain-Aware Scaling Laws Uncover Data Synergy Albert Ge, Tzu-Heng Huang, John Cooper, Avi Trost, Ziyi Chu, Satya Sai Srinath Namburi GNVV , Ziyang Cai, Kendall Park, Nicholas Roberts, and Frederic Sala

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69022546-8f2a-4f5a-8473-cbf110890a79 · outbound

This paper cites OLMo: Accelerating the Science of Language Models.

Domain-Aware Scaling Laws Uncover Data Synergy OLMo: Accelerating the Science of Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10773f3d-cb38-4893-a2ec-fd3f7d4faa33 · outbound

This paper cites Studying Large Language Model Generalization with Influence Functions.

Domain-Aware Scaling Laws Uncover Data Synergy Studying Large Language Model Generalization with Influence Functions

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f661269-97a9-4300-bc45-5dc84106996d · outbound

This paper cites CMR Scaling Law: Predicting Critical Mixture Ratios for Continual Pre-training of Language Models.

Domain-Aware Scaling Laws Uncover Data Synergy CMR Scaling Law: Predicting Critical Mixture Ratios for Continual Pre-training of Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b628019e-1abb-469f-b888-20a20b81e28d · outbound

This paper cites Training Compute-Optimal Large Language Models.

Domain-Aware Scaling Laws Uncover Data Synergy Training Compute-Optimal Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2455584f-c702-4866-9c58-3f581e4b710c · outbound

This paper cites Datamodels: Predicting Predictions from Training Data.

Domain-Aware Scaling Laws Uncover Data Synergy Datamodels: Predicting Predictions from Training Data

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b300a453-5410-4831-a99e-864932b4d533 · outbound

This paper cites Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning.

Domain-Aware Scaling Laws Uncover Data Synergy Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9fe6796-2f46-4d7d-bf0a-a422a40deb11 · outbound

This paper cites Autoscale: Scale-aware data mixing for pre-training llms.arXiv preprint arXiv:2407.20177,.

Domain-Aware Scaling Laws Uncover Data Synergy Autoscale: Scale-aware data mixing for pre-training llms.arXiv preprint arXiv:2407.20177,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4e43290-447e-4dec-8ad7-d0b5bbc023a8 · outbound

This paper cites Scaling Laws for Neural Language Models.

Domain-Aware Scaling Laws Uncover Data Synergy Scaling Laws for Neural Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bda2c34-7f17-4ab6-b47e-bf2a9e9db7f2 · outbound

This paper cites Code Pretraining Improves Entity Tracking Abilities of Language Models.

Domain-Aware Scaling Laws Uncover Data Synergy Code Pretraining Improves Entity Tracking Abilities of Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebaae459-999d-4f75-b41f-1dde9c7eb7b3 · outbound

This paper cites Race: Large-scale reading comprehension dataset from examinations.

Domain-Aware Scaling Laws Uncover Data Synergy Race: Large-scale reading comprehension dataset from examinations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9600c224-e067-494a-a2a2-0fa31776251b · outbound

This paper cites Improving General Text Embedding Model: Tackling Task Conflict and Data Imbalance through Model Merging.

Domain-Aware Scaling Laws Uncover Data Synergy Improving General Text Embedding Model: Tackling Task Conflict and Data Imbalance through Model Merging

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10d740cf-1327-4572-b8a4-416925bd5f28 · outbound

This paper cites The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI.

Domain-Aware Scaling Laws Uncover Data Synergy The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 225ebb96-f56d-410e-b7d4-483a1512518b · outbound

This paper cites Atlas: Adaptive transfer scaling laws for multilingual pretraining, finetuning, and decoding the curse of multilinguality.

Domain-Aware Scaling Laws Uncover Data Synergy Atlas: Adaptive transfer scaling laws for multilingual pretraining, finetuning, and decoding the curse of multilinguality

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd68876a-91f2-42b0-9a72-6571733cb257 · outbound

This paper cites MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code.

Domain-Aware Scaling Laws Uncover Data Synergy MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40dce8b8-4584-4927-a47b-20a7226de19c · outbound

This paper cites At Which Training Stage Does Code Data Help LLMs Reasoning?.

Domain-Aware Scaling Laws Uncover Data Synergy At Which Training Stage Does Code Data Help LLMs Reasoning?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc358018-e038-4a34-b346-0d2b169b2c71 · outbound

This paper cites DataDecide: How to Predict Best Pretraining Data with Small Experiments.

Domain-Aware Scaling Laws Uncover Data Synergy DataDecide: How to Predict Best Pretraining Data with Small Experiments

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1d482d3-098e-4ce8-aa9e-726c8ce3f8aa · outbound

This paper cites Pointer Sentinel Mixture Models.

Domain-Aware Scaling Laws Uncover Data Synergy Pointer Sentinel Mixture Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75eea7b3-f3cc-4251-a6d1-1522d8fd37c7 · outbound

This paper cites The LAMBADA dataset: Word prediction requiring a broad discourse context.

Domain-Aware Scaling Laws Uncover Data Synergy The LAMBADA dataset: Word prediction requiring a broad discourse context

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87c0bd1f-c5e2-4356-a93e-abda1b9195f3 · outbound

This paper cites Pretraining scaling laws for generative evaluations of language models.arXiv preprint arXiv:2509.24012,.

Domain-Aware Scaling Laws Uncover Data Synergy Pretraining scaling laws for generative evaluations of language models.arXiv preprint arXiv:2509.24012,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0427db88-d620-4198-b9fa-623dc26e5b87 · outbound

This paper cites Scaling laws for optimal data mixtures.arXiv preprint arXiv:2507.09404,.

Domain-Aware Scaling Laws Uncover Data Synergy Scaling laws for optimal data mixtures.arXiv preprint arXiv:2507.09404,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e09b73e6-1c45-4bd7-bd1c-cac990ab38e4 · outbound

This paper cites Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.

Domain-Aware Scaling Laws Uncover Data Synergy Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27281d89-c4a0-4cac-afb3-ef7deff2bbac · outbound

This paper cites 2 OLMo 2 Furious.

Domain-Aware Scaling Laws Uncover Data Synergy 2 OLMo 2 Furious

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccf320b1-e36a-4d24-8b59-57c4a030aafe · outbound

This paper cites Mergemix: Optimizing mid-training data mixtures via learnable model merging.arXiv preprint arXiv:2601.17858,.

Domain-Aware Scaling Laws Uncover Data Synergy Mergemix: Optimizing mid-training data mixtures via learnable model merging.arXiv preprint arXiv:2601.17858,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72a3f635-59e7-4db1-9179-1a7d6df13ef4 · outbound

This paper cites Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance.

Domain-Aware Scaling Laws Uncover Data Synergy Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c910617d-f8c4-4959-8220-3b79d42a598f · outbound

This paper cites CodePMP: Scalable Preference Model Pretraining for Large Language Model Reasoning.

Domain-Aware Scaling Laws Uncover Data Synergy CodePMP: Scalable Preference Model Pretraining for Large Language Model Reasoning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eacf1bf9-76e9-4370-ae30-206522d7ba0c · outbound

This paper cites Group-Level Data Selection for Efficient Pretraining.

Domain-Aware Scaling Laws Uncover Data Synergy Group-Level Data Selection for Efficient Pretraining

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

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Observation ebc5249f-5e79-4491-beb0-3be3eadae291 · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

Domain-Aware Scaling Laws Uncover Data Synergy HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09afd6ee-be56-4718-911b-8020a59191da · outbound

This paper cites Beyond Anti-Forgetting: Multimodal Continual Instruction Tuning with Positive Forward Transfer.

Domain-Aware Scaling Laws Uncover Data Synergy Beyond Anti-Forgetting: Multimodal Continual Instruction Tuning with Positive Forward Transfer

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84d9bbad-4b30-42b1-a759-f9712ecb5536 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Domain-Aware Scaling Laws Uncover Data Synergy Instruction-Following Evaluation for Large Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

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Unavailable: canonical work link unavailable.

Observation 8e00d0b0-bbc1-46e5-b756-51130a338cec · outbound

This paper cites Here we give the per-group scales and checkpoint counts.

Domain-Aware Scaling Laws Uncover Data Synergy Here we give the per-group scales and checkpoint counts

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

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Observation 85eda1e9-b798-4ef3-84ee-c73a3402c431 · outbound

This paper cites Six domains (Books, Code, Encyclopedia, Legal, Science, Web) match DPI source domains.

Domain-Aware Scaling Laws Uncover Data Synergy Six domains (Books, Code, Encyclopedia, Legal, Science, Web) match DPI source domains

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f794378-a334-4fa0-8267-950a52638ad9 · outbound

This paper cites an unresolved cited work.

Domain-Aware Scaling Laws Uncover Data Synergy Unresolved cited work

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dcd3c89-0d75-4d1d-8e66-5397484e6485 · outbound

This paper cites All evaluations use the lm-evaluation-harness (Gao et al., 2024).

Domain-Aware Scaling Laws Uncover Data Synergy All evaluations use the lm-evaluation-harness (Gao et al., 2024)

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

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Observation 7e842dde-9294-4be7-aee2-5b61e33b2933 · outbound

This paper cites an unresolved cited work.

Domain-Aware Scaling Laws Uncover Data Synergy Unresolved cited work

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1de4917-0cd4-4105-b243-28b655743ba7 · outbound

This paper cites Appendix G.1 derives the objective used to choose the validation mixtures, and Appendix G.2 provides more details for this experiment.

Domain-Aware Scaling Laws Uncover Data Synergy Appendix G.1 derives the objective used to choose the validation mixtures, and Appendix G.2 provides more details for this experiment

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87da0339-88d5-4c34-844f-9740604a4d92 · outbound

This paper cites The 30M model uses dmodel = 256, 8 heads, and 8 layers, while the 150M model uses dmodel = 640, 10 heads, and 12 layers.

Domain-Aware Scaling Laws Uncover Data Synergy The 30M model uses dmodel = 256, 8 heads, and 8 layers, while the 150M model uses dmodel = 640, 10 heads, and 12 layers

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation a5cc47bd-3e73-41ef-a316-6d10c1a192d5 · inbound

Bridging Compute- and Data-Optimal Pretraining cites this paper.

Bridging Compute- and Data-Optimal Pretraining Domain-Aware Scaling Laws Uncover Data Synergy

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T03:01:55.410116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.