Paper Citation Record · LEDGER

Learning Dynamics in Continual Pre-Training for Large Language Models

As of 19 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2505.07796.

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

pith.paper-citation-record.v1
2505.07796 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:14:19.319295Z

measured 48 of 48 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:19:10.282840Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:19:11.804438Z

Reference resolution

47 of 47 outbound references displayed

verified exact0
verified fuzzy10
unresolved37
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 00532d16-4d10-4e2f-8e6b-d07cc7d4fae4 · outbound

This paper cites G., and Bakshy, E.

Learning Dynamics in Continual Pre-Training for Large Language Models G., and Bakshy, E

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.411132Z

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.

Observation 43576439-1807-48fe-b43a-972acdf4a1d6 · outbound

This paper cites An Empirical Study of Scaling Laws for Transfer.

Learning Dynamics in Continual Pre-Training for Large Language Models An Empirical Study of Scaling Laws for Transfer

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.082887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebbd0cbc-f12b-499f-a7a1-f2f1a7a5d4e1 · outbound

This paper cites and Bengio, Y.

Learning Dynamics in Continual Pre-Training for Large Language Models and Bengio, Y

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.088591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ecb05d9-559d-4b03-9bff-ee522d171bc5 · outbound

This paper cites Lifelong language pretraining with distribution-specialized experts.

Learning Dynamics in Continual Pre-Training for Large Language Models Lifelong language pretraining with distribution-specialized experts

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.383663Z

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.

Observation 008670e1-7564-4fd7-b4f8-c6d11b176cf9 · outbound

This paper cites MEDITRON-70B: Scaling Medical Pretraining for Large Language Models.

Learning Dynamics in Continual Pre-Training for Large Language Models MEDITRON-70B: Scaling Medical Pretraining for Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.098691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d739a6d0-6212-474e-926a-bcb0e6c93233 · outbound

This paper cites SaulLM-7B: A pioneering Large Language Model for Law.

Learning Dynamics in Continual Pre-Training for Large Language Models SaulLM-7B: A pioneering Large Language Model for Law

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.104299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a8ef6e3-2820-47d0-bef0-7aa2fa8edb96 · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

Learning Dynamics in Continual Pre-Training for Large Language Models DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.110481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0aa8343-9a9d-43f4-af2d-82d2479e046c · outbound

This paper cites Sailor: Open Language Models for South-East Asia.

Learning Dynamics in Continual Pre-Training for Large Language Models Sailor: Open Language Models for South-East Asia

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.115873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6215e37-1c44-43f5-812f-d573e6aceed3 · outbound

This paper cites The Llama 3 Herd of Models.

Learning Dynamics in Continual Pre-Training for Large Language Models The Llama 3 Herd of Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.121164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d02dedf-45d9-4870-a968-728aa2f832cb · outbound

This paper cites Unearthing Large Scale Domain-Specific Knowledge from Public Corpora.

Learning Dynamics in Continual Pre-Training for Large Language Models Unearthing Large Scale Domain-Specific Knowledge from Public Corpora

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.126804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81f49ded-fce9-4a5a-849c-2229406caf03 · outbound

This paper cites an unresolved cited work.

Learning Dynamics in Continual Pre-Training for Large Language Models Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.132108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98878f17-b8be-4536-999a-06ac6f02c0c1 · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Learning Dynamics in Continual Pre-Training for Large Language Models The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.137187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6f9a9fc-d37a-4aa5-aa03-fb9bb266a78d · outbound

This paper cites CMR scaling law: Predicting critical mixture ratios for continual pre-training of language models.

Learning Dynamics in Continual Pre-Training for Large Language Models CMR scaling law: Predicting critical mixture ratios for continual pre-training of language models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.142025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f197b83-e306-4a0c-9dcb-19b67cd9a90b · outbound

This paper cites Continual Pre-Training of Large Language Models: How to (re)warm your model?.

Learning Dynamics in Continual Pre-Training for Large Language Models Continual Pre-Training of Large Language Models: How to (re)warm your model?

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.146891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aea6de6c-d97c-442a-ac0e-1e1a656a6954 · outbound

This paper cites Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data?.

Learning Dynamics in Continual Pre-Training for Large Language Models Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data?

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.151913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efb64f27-ea03-4570-afd7-15484ead5ddb · outbound

This paper cites Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset.

Learning Dynamics in Continual Pre-Training for Large Language Models Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.156722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c955415a-2ab1-4134-822e-bea0556c528a · outbound

This paper cites Scaling Laws for Transfer.

Learning Dynamics in Continual Pre-Training for Large Language Models Scaling Laws for Transfer

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.166601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 924fd2e6-07e5-452f-9712-8f8363a75d86 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Learning Dynamics in Continual Pre-Training for Large Language Models Training Compute-Optimal Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.171347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d121661f-28b3-4877-aeae-050ecf8bd875 · outbound

This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

Learning Dynamics in Continual Pre-Training for Large Language Models MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.176388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34833b2e-1659-4506-8777-22dbf7c8949e · outbound

This paper cites an unresolved cited work.

Learning Dynamics in Continual Pre-Training for Large Language Models Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.181367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fe99d26-80ac-4698-9dac-b1857eb3ffc0 · outbound

This paper cites Qwen2.5-Coder Technical Report.

Learning Dynamics in Continual Pre-Training for Large Language Models Qwen2.5-Coder Technical Report

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.185976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e60ba88-dd35-4f19-aa2c-6ce5fc1e1df3 · outbound

This paper cites L., Anthony, Q.

Learning Dynamics in Continual Pre-Training for Large Language Models L., Anthony, Q

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.355983Z

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.

Observation 459ae38a-4482-428d-9128-83b4ab155c1d · outbound

This paper cites Scaling Laws for Neural Language Models.

Learning Dynamics in Continual Pre-Training for Large Language Models Scaling Laws for Neural Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.195460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68069132-8bea-4109-b031-5cbd052be450 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Learning Dynamics in Continual Pre-Training for Large Language Models Adam: A Method for Stochastic Optimization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.200692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8a86594-ef36-4e22-a423-6908413e4ed9 · outbound

This paper cites D., van de Ven, G.

Learning Dynamics in Continual Pre-Training for Large Language Models D., van de Ven, G

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.339444Z

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.

Observation 9b3c9d46-f34f-41a5-9d27-fa350dd6b9bd · outbound

This paper cites Crafting papers on machine learning.

Learning Dynamics in Continual Pre-Training for Large Language Models Crafting papers on machine learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.210233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d3ac477-eb42-470d-989a-cd4faea88925 · outbound

This paper cites and Hutter, F.

Learning Dynamics in Continual Pre-Training for Large Language Models and Hutter, F

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.309928Z

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.

Observation 2e51e396-b711-4e09-9e85-55a0c2fbbb37 · outbound

This paper cites Decoupled Weight Decay Regularization.

Learning Dynamics in Continual Pre-Training for Large Language Models Decoupled Weight Decay Regularization

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.219560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bd6e633-6962-47b5-b386-475c95976855 · outbound

This paper cites A multi-power law for loss curve prediction across learning rate schedules.

Learning Dynamics in Continual Pre-Training for Large Language Models A multi-power law for loss curve prediction across learning rate schedules

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.290973Z

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.

Observation 989c7cc4-f2b7-4702-b280-e8eb39b9ad2c · outbound

This paper cites Updating quasi newton matrices with limited storage.

Learning Dynamics in Continual Pre-Training for Large Language Models Updating quasi newton matrices with limited storage

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.229110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdee20b3-088e-4cd9-a63a-432b79da5f9e · outbound

This paper cites GPT-4 Technical Report.

Learning Dynamics in Continual Pre-Training for Large Language Models GPT-4 Technical Report

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.233882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9f86186-71aa-4f82-882d-d1a69542bfc8 · outbound

This paper cites Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models.

Learning Dynamics in Continual Pre-Training for Large Language Models Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.238721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 861df785-cb40-41e5-bb8b-024345a2a11c · outbound

This paper cites D., Azerbayev, Z., and Ba, J.

Learning Dynamics in Continual Pre-Training for Large Language Models D., Azerbayev, Z., and Ba, J

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.273507Z

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.

Observation 1f09191e-1298-4fc4-aa62-52aa61bb9fad · outbound

This paper cites B., Lozhkov, A., Mitchell, M., Raffel, C., Werra, L.

Learning Dynamics in Continual Pre-Training for Large Language Models B., Lozhkov, A., Mitchell, M., Raffel, C., Werra, L

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.249541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2ef0944-f9cd-415d-b159-fe312a74b41a · outbound

This paper cites D- CPT law: Domain-specific continual pre-training scaling law for large language models.

Learning Dynamics in Continual Pre-Training for Large Language Models D- CPT law: Domain-specific continual pre-training scaling law for large language models

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.243990Z

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.

Observation 85f9ac97-6833-42f3-987d-cddf4ef01bcf · outbound

This paper cites Continual Learning of Large Language Models: A Comprehensive Survey.

Learning Dynamics in Continual Pre-Training for Large Language Models Continual Learning of Large Language Models: A Comprehensive Survey

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.259110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a839d7a2-7450-47b5-9c0b-1a24bd2dda44 · outbound

This paper cites an unresolved cited work.

Learning Dynamics in Continual Pre-Training for Large Language Models Unresolved cited work

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.264207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 321a79f9-b434-444b-8146-0f2629a50b16 · outbound

This paper cites R., Hestness, J., and Dey, N.

Learning Dynamics in Continual Pre-Training for Large Language Models R., Hestness, J., and Dey, N

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.269275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cbb1862-92dd-443b-af9b-41f1447b764f · outbound

This paper cites Scaling Law with Learning Rate Annealing.

Learning Dynamics in Continual Pre-Training for Large Language Models Scaling Law with Learning Rate Annealing

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.273955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f722a6d-d6be-452a-a960-a2ed3c795b4c · outbound

This paper cites Learning to prompt for continual learning.

Learning Dynamics in Continual Pre-Training for Large Language Models Learning to prompt for continual learning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.279303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58551376-09c2-48f3-af18-a0df838298b2 · outbound

This paper cites A learning rate path switching training paradigm for version updates of large language models.

Learning Dynamics in Continual Pre-Training for Large Language Models A learning rate path switching training paradigm for version updates of large language models

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.202006Z

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.

Observation 6676a362-fa8a-4ecc-a150-6af55c89abbf · outbound

This paper cites an unresolved cited work.

Learning Dynamics in Continual Pre-Training for Large Language Models Unresolved cited work

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.289495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f304d238-6658-47b8-a1da-c9b68b70feff · outbound

This paper cites Optimization Hyper-parameter Laws for Large Language Models.

Learning Dynamics in Continual Pre-Training for Large Language Models Optimization Hyper-parameter Laws for Large Language Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.295472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5971afbb-59ef-4cc7-8894-97b5c7ac19fd · outbound

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

Learning Dynamics in Continual Pre-Training for Large Language Models Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.300672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d9b136e-0af0-43a8-8371-126b20a2042f · outbound

This paper cites Domain2vec: Vectorizing datasets to find the optimal data mixture without training, 2025.

Learning Dynamics in Continual Pre-Training for Large Language Models Domain2vec: Vectorizing datasets to find the optimal data mixture without training, 2025

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:14:20.172977Z

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.

Observation 6563d047-ff19-4651-b5fc-a2132e7fe312 · outbound

This paper cites Investigating Continual Pretraining in Large Language Models: Insights and Implications.

Learning Dynamics in Continual Pre-Training for Large Language Models Investigating Continual Pretraining in Large Language Models: Insights and Implications

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.313213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 396d8970-4cd2-4e07-8d1d-91227aeadf41 · outbound

This paper cites write newline.

Learning Dynamics in Continual Pre-Training for Large Language Models write newline

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T22:14:19.319295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation f881e0e2-8d5b-4e42-93fc-65d87c471d6c · inbound

Domain2Vec: Vectorizing Datasets to Find the Optimal Data Mixture without Training cites this paper.

Domain2Vec: Vectorizing Datasets to Find the Optimal Data Mixture without Training Learning Dynamics in Continual Pre-Training for Large Language Models

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:19:11.911632Z

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.