Paper Citation Record · LEDGER

When is Warmstarting Effective for Scaling Language Models?

As of 14 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2605.13405.

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

pith.paper-citation-record.v1
2605.13405 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-14T20:00:47.126736Z

measured 38 of 38 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

verified exact23
verified fuzzy9
unresolved4
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 166c4dd5-d84a-4117-a34d-b56503e7dd2b · outbound

This paper cites Bergsma, B.

When is Warmstarting Effective for Scaling Language Models? Bergsma, B

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:52.971842Z

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Observation 857ed5f3-c96a-4d6e-a765-002b2ca79b6a · outbound

This paper cites Brown, B.

When is Warmstarting Effective for Scaling Language Models? Brown, B

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T20:02:54.620589Z

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Observation 5c79c660-0134-4341-b9b7-864abec704b7 · outbound

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

When is Warmstarting Effective for Scaling Language Models? Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-14T20:02:52.977944Z

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Observation a519cee7-e1af-46a2-9c49-eb9f0864fed0 · outbound

This paper cites an unresolved cited work.

When is Warmstarting Effective for Scaling Language Models? Unresolved cited work

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:53.028001Z

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Observation 4e00b95c-2dd8-471f-a8a2-3921f7e2c625 · outbound

This paper cites Don’t be lazy: Completep enables compute-efficient deep transformers.

When is Warmstarting Effective for Scaling Language Models? Don’t be lazy: Completep enables compute-efficient deep transformers

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:53.004359Z

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Observation 8bd0698d-2c4c-4b19-98bd-00c2ebca09a7 · outbound

This paper cites Maintaining Plasticity in Deep Continual Learning.

When is Warmstarting Effective for Scaling Language Models? Maintaining Plasticity in Deep Continual Learning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:53.011616Z

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Observation c018810f-77f1-493e-b2f7-79b864874de0 · outbound

This paper cites Practical Efficiency of Muon for Pretraining.

When is Warmstarting Effective for Scaling Language Models? Practical Efficiency of Muon for Pretraining

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:53.040706Z

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Observation 039146de-b5d7-4940-b374-f3a16c2b65b2 · outbound

This paper cites Tune As You Scale: Hyperparameter Optimization For Compute Efficient Training.

When is Warmstarting Effective for Scaling Language Models? Tune As You Scale: Hyperparameter Optimization For Compute Efficient Training

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:53.060870Z

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Observation f92ea071-a9f2-409a-9722-4847d80c5611 · outbound

This paper cites Filatov, J.

When is Warmstarting Effective for Scaling Language Models? Filatov, J

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:52.996815Z

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Observation 9bfea212-151a-414c-bba6-af48498c7aa9 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

When is Warmstarting Effective for Scaling Language Models? Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-14T20:02:53.080173Z

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Observation 5c55f784-bd38-4abc-9629-78247574edcd · outbound

This paper cites Scaling Laws for Neural Language Models.

When is Warmstarting Effective for Scaling Language Models? Scaling Laws for Neural Language Models

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-14T20:02:53.018294Z

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Observation ff14f264-26cb-40b5-9440-8c52167e737d · outbound

This paper cites Landscape-Aware Growing: The Power of a Little LAG.

When is Warmstarting Effective for Scaling Language Models? Landscape-Aware Growing: The Power of a Little LAG

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:53.086528Z

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Observation ae6ef9ec-3d43-4dfc-9e67-911427ac3152 · outbound

This paper cites arXiv preprint arXiv:2510.06548 , year=.

When is Warmstarting Effective for Scaling Language Models? arXiv preprint arXiv:2510.06548 , year=

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:53.034301Z

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Observation d10de383-9733-4bf1-a916-3e68e1d5bdd6 · outbound

This paper cites $\mu$pscaling small models: Principled warm starts and hyperparameter transfer.

When is Warmstarting Effective for Scaling Language Models? $\mu$pscaling small models: Principled warm starts and hyperparameter transfer

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-03T02:16:49.045063Z

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Observation 77694bcf-1c11-4ed6-b205-f317191741e4 · outbound

This paper cites Mihaylov, P.

When is Warmstarting Effective for Scaling Language Models? Mihaylov, P

Reference 15

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Observation 2e4b1609-7317-42c5-ac8d-00c81c037857 · outbound

This paper cites GPT-4 Technical Report.

When is Warmstarting Effective for Scaling Language Models? GPT-4 Technical Report

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-14T20:02:53.098552Z

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Observation f372e8cf-2faa-46e5-9a6c-cae219386f7f · outbound

This paper cites Porian, M.

When is Warmstarting Effective for Scaling Language Models? Porian, M

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T20:02:54.591746Z

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Observation 748e86c1-48ae-40d3-8071-563a27a0fb3a · outbound

This paper cites Knowledge Inheritance for Pre-trained Language Models.

When is Warmstarting Effective for Scaling Language Models? Knowledge Inheritance for Pre-trained Language Models

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:53.073632Z

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Observation 95e7bbe6-0968-421c-86f1-41900fd61071 · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

When is Warmstarting Effective for Scaling Language Models? Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-14T20:02:53.054105Z

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Observation 7e33514b-bed9-43ce-b9dc-93a0ccf1b66e · outbound

This paper cites Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization.

When is Warmstarting Effective for Scaling Language Models? Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:52.958845Z

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Observation 41e1fed8-4fb3-4ef0-b270-046fc059d2d4 · outbound

This paper cites an unresolved cited work.

When is Warmstarting Effective for Scaling Language Models? Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-05-14T20:02:54.600050Z

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Observation 2c524322-9ff8-46e3-8489-a20837f450fa · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

When is Warmstarting Effective for Scaling Language Models? RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-14T20:02:52.964832Z

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Observation 3b246ad4-492b-48aa-8619-060e739f08a6 · outbound

This paper cites Thérien, C.

When is Warmstarting Effective for Scaling Language Models? Thérien, C

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:52.984062Z

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Observation 7c3faa21-eb96-44fc-916c-1c97034859f2 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

When is Warmstarting Effective for Scaling Language Models? LLaMA: Open and Efficient Foundation Language Models

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-14T20:02:53.092487Z

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Observation debbe55d-f196-454e-a243-ee78a484e021 · outbound

This paper cites Preservation Is Not Enough for Width Growth: Regime-Sensitive Selection of Dense LM Warm Starts.

When is Warmstarting Effective for Scaling Language Models? Preservation Is Not Enough for Width Growth: Regime-Sensitive Selection of Dense LM Warm Starts

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-05-14T20:02:53.066891Z

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Observation 51e8d4f7-ff39-4b93-a88a-86c1aafbf229 · outbound

This paper cites Efficient Large Language Models: A Survey.

When is Warmstarting Effective for Scaling Language Models? Efficient Large Language Models: A Survey

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:02:53.104922Z

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Observation 9d8fb988-dd5a-4056-b221-c6d9a04fc9e8 · outbound

This paper cites SPARKLING: Balancing Signal Preservation and Symmetry Breaking for Width-Progressive Learning.

When is Warmstarting Effective for Scaling Language Models? SPARKLING: Balancing Signal Preservation and Symmetry Breaking for Width-Progressive Learning

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-06-30T03:18:06.134504Z

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Observation c16acb1a-c7f0-45c2-af20-8b04ffe883ca · outbound

This paper cites This family of parameteriza- tions describes scaling factors for the weights, the learning rate, and the standard deviation of the initialization.

When is Warmstarting Effective for Scaling Language Models? This family of parameteriza- tions describes scaling factors for the weights, the learning rate, and the standard deviation of the initialization

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T20:02:54.580817Z

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Observation d32acd80-7f12-41c7-a133-35a9ee3289aa · outbound

This paper cites B Synthetic Regression Benchmark We use the synthetic regression benchmark in which the target function is constructed to have a power-law Fourier spectrum [Qiu et al., 2025].

When is Warmstarting Effective for Scaling Language Models? B Synthetic Regression Benchmark We use the synthetic regression benchmark in which the target function is constructed to have a power-law Fourier spectrum [Qiu et al., 2025]

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T20:02:54.575901Z

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Observation b90c003f-7ebc-49ca-a25c-8ed92a5cc03f · outbound

This paper cites Grid Sizes.The base grid contains 8·3·5·3·2 = 720 configurations.

When is Warmstarting Effective for Scaling Language Models? Grid Sizes.The base grid contains 8·3·5·3·2 = 720 configurations

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T20:02:54.587430Z

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Observation 3a46482d-97e8-4afe-838e-9c3fe9523c53 · outbound

This paper cites an unresolved cited work.

When is Warmstarting Effective for Scaling Language Models? Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-05-14T20:02:54.604152Z

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Observation ab4b6cea-df64-4369-a6d9-d6306c6a0549 · outbound

This paper cites To study its sensitivity, we sweep the perturbation scale σperturb on a 32M→286M transfer, keeping the remaining SZP settings fixed.

When is Warmstarting Effective for Scaling Language Models? To study its sensitivity, we sweep the perturbation scale σperturb on a 32M→286M transfer, keeping the remaining SZP settings fixed

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T20:02:54.608501Z

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Observation 6e87f098-361a-4a95-9f03-faf382187222 · outbound

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When is Warmstarting Effective for Scaling Language Models? Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-05-14T20:02:54.612694Z

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Observation cf4664b6-c31a-47d5-aa2b-e648f41b8a4a · outbound

This paper cites Weight Decay.All experiments usezeroweight decay.

When is Warmstarting Effective for Scaling Language Models? Weight Decay.All experiments usezeroweight decay

Reference 34

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Observation 7ac909cf-3983-4ab1-904b-967620676fc5 · outbound

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When is Warmstarting Effective for Scaling Language Models? Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-05-14T20:02:54.562630Z

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Observation bb041131-db90-4501-884a-c8d60784a859 · outbound

This paper cites For the reported language-model experiments, we report GPU-hour ranges based on the number of completed runs, hardware allocation, and typical wall-clock time per target scale.

When is Warmstarting Effective for Scaling Language Models? For the reported language-model experiments, we report GPU-hour ranges based on the number of completed runs, hardware allocation, and typical wall-clock time per target scale

Reference 36

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Observation 73987363-78ce-4c61-887f-1248229eae0b · outbound

This paper cites copy-and-rescale.

When is Warmstarting Effective for Scaling Language Models? copy-and-rescale

Reference 37

Resolution: malformed identifier; raw_fallback, observed 2026-05-14T20:02:54.571721Z

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Observation a0a6ed75-0ff1-49d8-bca1-ce9ae6f7050c · outbound

This paper cites Following Approach 3 of Hoffmann et al.

When is Warmstarting Effective for Scaling Language Models? Following Approach 3 of Hoffmann et al

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T20:02:54.559030Z

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Pith citing papers

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