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Paper Citation Record · LEDGER

Small Initialization Matters for Large Language Models

As of 19 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2606.17945.

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

pith.paper-citation-record.v1
2606.17945 v2

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T00:58:58.470595Z

measured 44 of 44 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

44 of 44 outbound references displayed

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External citation measurements

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Outbound references

Observation 4729e3c0-8c34-4b5b-b2b0-aafca7c2b52b · outbound

This paper cites Advances in neural information processing systems33, 1877–1901 (2020).

Small Initialization Matters for Large Language Models Advances in neural information processing systems33, 1877–1901 (2020)

Reference 1

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Observation e2d856ea-9169-490f-8048-195571b5c770 · outbound

This paper cites Scaling Laws for Neural Language Models.

Small Initialization Matters for Large Language Models Scaling Laws for Neural Language Models

Reference 2

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This paper cites In: Advances in Neural Information Processing Systems (2022).

Small Initialization Matters for Large Language Models In: Advances in Neural Information Processing Systems (2022)

Reference 3

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This paper cites International Conference on Learning Representations (2022).

Small Initialization Matters for Large Language Models International Conference on Learning Representations (2022)

Reference 4

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This paper cites In: International Conference on Learning Representations, vol.

Small Initialization Matters for Large Language Models In: International Conference on Learning Representations, vol

Reference 5

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Observation 6a00ad0a-d9f8-436b-85ae-6569ac8ee1ee · outbound

This paper cites Nature645(8081), 633–638 (2025).

Small Initialization Matters for Large Language Models Nature645(8081), 633–638 (2025)

Reference 6

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This paper cites Advances in neural information processing systems (2017).

Small Initialization Matters for Large Language Models Advances in neural information processing systems (2017)

Reference 7

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Small Initialization Matters for Large Language Models Unresolved cited work

Reference 8

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This paper cites Journal of Machine Learning Research23(120), 1–39 (2022).

Small Initialization Matters for Large Language Models Journal of Machine Learning Research23(120), 1–39 (2022)

Reference 9

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This paper cites In: First Conference on Language Modeling (2024).

Small Initialization Matters for Large Language Models In: First Conference on Language Modeling (2024)

Reference 10

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This paper cites nature521(7553), 436–444 23 (2015).

Small Initialization Matters for Large Language Models nature521(7553), 436–444 23 (2015)

Reference 11

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This paper cites In: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, pp.

Small Initialization Matters for Large Language Models In: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, pp

Reference 12

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Observation f2c16a72-8ab6-4086-adcc-200bcf86b256 · outbound

This paper cites In: Neural Networks: Tricks of the Trade, (2012).

Small Initialization Matters for Large Language Models In: Neural Networks: Tricks of the Trade, (2012)

Reference 13

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This paper cites In: Proceedings of the IEEE International Conference on Computer Vision, pp.

Small Initialization Matters for Large Language Models In: Proceedings of the IEEE International Conference on Computer Vision, pp

Reference 14

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This paper cites Advances in Neural Information Processing Systems 31(2018).

Small Initialization Matters for Large Language Models Advances in Neural Information Processing Systems 31(2018)

Reference 15

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This paper cites Advances in neural information processing systems32(2019).

Small Initialization Matters for Large Language Models Advances in neural information processing systems32(2019)

Reference 16

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Small Initialization Matters for Large Language Models In: Conference on Learning Theory, pp

Reference 17

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This paper cites Journal of Machine Learning Research22(71), 1–47 (2021).

Small Initialization Matters for Large Language Models Journal of Machine Learning Research22(71), 1–47 (2021)

Reference 18

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This paper cites In: Advances in Neural Information Processing Systems (2022).

Small Initialization Matters for Large Language Models In: Advances in Neural Information Processing Systems (2022)

Reference 19

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Observation 2b431299-8a2e-4b34-9c08-dacdbf15d5ac · outbound

This paper cites Advances in Neural Information Processing Systems37, 81157–81203 (2024).

Small Initialization Matters for Large Language Models Advances in Neural Information Processing Systems37, 81157–81203 (2024)

Reference 20

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Small Initialization Matters for Large Language Models In: The Thirty-eighth Annual Conference on Neural Information Processing Systems (2024)

Reference 21

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Small Initialization Matters for Large Language Models In: International Conference on Machine Learning, pp

Reference 22

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Small Initialization Matters for Large Language Models IEEE Transactions on Pattern Analysis and Machine Intelligence (2025)

Reference 23

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Small Initialization Matters for Large Language Models Layer Normalization

Reference 24

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Small Initialization Matters for Large Language Models In: International Conference on Learning Representations (2024)

Reference 25

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Small Initialization Matters for Large Language Models Advances in Neural Information Processing Systems38, 100092–100118 (2025)

Reference 26

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Small Initialization Matters for Large Language Models An overview of condensation phenomenon in deep learning

Reference 27

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Small Initialization Matters for Large Language Models Why do LLMs attend to the first token?

Reference 28

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Small Initialization Matters for Large Language Models In: International Conference on Learning Representations, vol

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Small Initialization Matters for Large Language Models In: Proceedings of the 41st International Conference on Machine Learning (2024)

Reference 30

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Small Initialization Matters for Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 31

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Small Initialization Matters for Large Language Models In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp

Reference 32

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Small Initialization Matters for Large Language Models Proceedings of the International Conference on Learning Representations (ICLR) (2021)

Reference 33

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Small Initialization Matters for Large Language Models Proceedings of the International Conference on Learning Representations (ICLR) (2021) 25

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Small Initialization Matters for Large Language Models In: Findings of the Association for Computational Linguistics: ACL 2023, pp

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Small Initialization Matters for Large Language Models Training Verifiers to Solve Math Word Problems

Reference 38

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Small Initialization Matters for Large Language Models Measuring Mathematical Problem Solving With the MATH Dataset

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local_arxiv, observed 2026-07-03T20:58:58.398810Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 972c3e19-ef1f-4b0b-b1ac-8e800993b774 · outbound

This paper cites In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (2026).

Small Initialization Matters for Large Language Models In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (2026)

Reference 40

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Unavailable: canonical work link unavailable.

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Observation bb632b5e-9377-4a65-859c-b47719980bfe · outbound

This paper cites DeepSeek-V3 Technical Report.

Small Initialization Matters for Large Language Models DeepSeek-V3 Technical Report

Reference 41

Resolution
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local_arxiv, observed 2026-07-03T20:58:58.403894Z

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.

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Observation 35c9599c-9d52-429b-916c-bc193e5c4696 · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

Small Initialization Matters for Large Language Models Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 42

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metadata mismatch
local_arxiv, observed 2026-07-03T20:58:58.415278Z

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.

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Observation da52a56e-760a-4695-9fbf-640c0df8d199 · outbound

This paper cites In: Interna- tional Conference on Learning Representations (2019).

Small Initialization Matters for Large Language Models In: Interna- tional Conference on Learning Representations (2019)

Reference 43

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unresolved
no resolver link, observed 2026-06-27T00:58:58.470595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3f76ff38-5d29-4894-8b95-ee030ae800ef · outbound

This paper cites Zenodo (2024) 26.

Small Initialization Matters for Large Language Models Zenodo (2024) 26

Reference 44

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unresolved
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Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.