Paper Citation Record · LEDGER

Characterization and Mitigation of Training Instabilities in Microscaling Formats

As of 19 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2506.20752.

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

pith.paper-citation-record.v1
2506.20752 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:47:52.291301Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:45:23.162011Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T07:03:23.229274Z

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation 4d5e57a5-33d2-4c06-adea-adcbf60450da · outbound

This paper cites an unresolved cited work.

Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

Reference 1

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Claude 4 system card

Reference 2

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

Reference 3

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This paper cites Loss-to-Loss Prediction: Scaling Laws for All Datasets.

Characterization and Mitigation of Training Instabilities in Microscaling Formats Loss-to-Loss Prediction: Scaling Laws for All Datasets

Reference 4

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Z., and Talwalkar, A

Reference 7

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Characterization and Mitigation of Training Instabilities in Microscaling Formats A., Cao, C., Cao, K., Castagné, R., Cendrero, J., Currie, L

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

Reference 12

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This paper cites F., Mahendran, A., Yu, F., Oliver, A., Huot, F., Bastings, J., Collier, M.

Characterization and Mitigation of Training Instabilities in Microscaling Formats F., Mahendran, A., Yu, F., Oliver, A., Huot, F., Bastings, J., Collier, M

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Characterization and Mitigation of Training Instabilities in Microscaling Formats and Zettlemoyer, L

Reference 14

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This paper cites Scaling FP8 training to trillion-token LLMs.

Characterization and Mitigation of Training Instabilities in Microscaling Formats Scaling FP8 training to trillion-token LLMs

Reference 15

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This paper cites The Llama 3 Herd of Models.

Characterization and Mitigation of Training Instabilities in Microscaling Formats The Llama 3 Herd of Models

Reference 16

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

Characterization and Mitigation of Training Instabilities in Microscaling Formats OLMo: Accelerating the Science of Language Models

Reference 17

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Query-Key Normalization for Transformers

Reference 18

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Training Compute-Optimal Large Language Models

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Characterization and Mitigation of Training Instabilities in Microscaling Formats L., Anthony, Q

Reference 20

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Scaling Laws for Neural Language Models

Reference 23

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Scaling Laws for Precision

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Characterization and Mitigation of Training Instabilities in Microscaling Formats J., and Lee, D

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Characterization and Mitigation of Training Instabilities in Microscaling Formats DeepSeek-V3 Technical Report

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats FP8 Formats for Deep Learning

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Mx pytorch emulation library

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Characterization and Mitigation of Training Instabilities in Microscaling Formats S., Narang, S., Poulton, A., Silva, R., Tang, B., Liskovich, D., Xu, P., Zhang, Y., Kambadur, M., Roller, S., and Zhang, S

Reference 33

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Nvidia blackwell architecture

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Gpt-4.5 system card

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens

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Characterization and Mitigation of Training Instabilities in Microscaling Formats B., Lozhkov, A., Mitchell, M., Raffel, C., Werra, L

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Microscaling Data Formats for Deep Learning

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Massive Activations in Large Language Models

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Characterization and Mitigation of Training Instabilities in Microscaling Formats Unresolved cited work

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Characterization and Mitigation of Training Instabilities in Microscaling Formats J., Xiao, L., Everett, K

Reference 44

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Characterization and Mitigation of Training Instabilities in Microscaling Formats V., Mihaylov, T., Ott, M., Shleifer, S., Shuster, K., Simig, D., Koura, P

Reference 46

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Pith citing papers

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Preventing Learning Stagnation in PPO by Scaling to 1 Million Parallel Environments cites this paper.

Preventing Learning Stagnation in PPO by Scaling to 1 Million Parallel Environments Characterization and Mitigation of Training Instabilities in Microscaling Formats

Reference 56

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The Thermodynamic Costs of Simple Linear Regression cites this paper.

The Thermodynamic Costs of Simple Linear Regression Characterization and Mitigation of Training Instabilities in Microscaling Formats

Reference 48

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