Paper Citation Record · LEDGER

Scaling Law for Quantization-Aware Training

As of 23 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 6 inbound Pith citation observations for arXiv:2505.14302.

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

pith.paper-citation-record.v1
2505.14302 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:41:09.461235Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T23:28:12.790404Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T23:47:28.471233Z

Reference resolution

46 of 46 outbound references displayed

verified exact0
verified fuzzy3
unresolved43
parse uncertain0
malformed identifier0
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External citation measurements

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Outbound references

Observation 7e1950c4-6e56-4fc6-a841-ab796ff1fa07 · outbound

This paper cites GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints.

Scaling Law for Quantization-Aware Training GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:05.316172Z

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Observation 18f7cfff-5082-4f97-b094-e30305d06dd1 · outbound

This paper cites Systematic Outliers in Large Language Models.

Scaling Law for Quantization-Aware Training Systematic Outliers in Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:05.394285Z

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Observation 881d5d36-540e-4658-92b1-aeda91d6ac48 · outbound

This paper cites QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs.

Scaling Law for Quantization-Aware Training QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:05.503504Z

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Observation d709f4f0-08ff-4cec-bf56-6dc742c4a4b7 · outbound

This paper cites A survey on mixture of experts in large language models.IEEE Transactions on Knowledge and Data Engineering, 2025.

Scaling Law for Quantization-Aware Training A survey on mixture of experts in large language models.IEEE Transactions on Knowledge and Data Engineering, 2025

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:05.573300Z

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Observation 963a8901-6437-4f05-8cc8-66e3186bf5b2 · outbound

This paper cites PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization.

Scaling Law for Quantization-Aware Training PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:05.692619Z

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Observation 3731e759-c438-4353-b6eb-394b5715d224 · outbound

This paper cites EfficientQAT: Efficient Quantization-Aware Training for Large Language Models.

Scaling Law for Quantization-Aware Training EfficientQAT: Efficient Quantization-Aware Training for Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:05.756352Z

Source-reported events for the cited work

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Observation c2df047c-ca82-42bc-9a03-359a59f1484c · outbound

This paper cites On the meaning and use of kurtosis.Psychological methods, 2(3):292, 1997.

Scaling Law for Quantization-Aware Training On the meaning and use of kurtosis.Psychological methods, 2(3):292, 1997

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:10.537711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 368234f2-7e28-48e2-b42d-b737098b5645 · outbound

This paper cites The case for 4-bit precision: k-bit inference scaling laws.

Scaling Law for Quantization-Aware Training The case for 4-bit precision: k-bit inference scaling laws

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:10.370026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 39e43c9c-7f1a-448c-8ae6-bde3be19a16c · outbound

This paper cites Learned Step Size Quantization.

Scaling Law for Quantization-Aware Training Learned Step Size Quantization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:06.036806Z

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Observation 4cac8f33-ef05-41ca-aeeb-e6fc175a5a72 · outbound

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

Scaling Law for Quantization-Aware Training Scaling FP8 training to trillion-token LLMs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:06.104682Z

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Observation d4b70f21-f8bb-472c-8def-f3c80f445e1f · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

Scaling Law for Quantization-Aware Training GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:06.190490Z

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Observation 45f5a1e3-d7c1-4f98-8df0-fc66c4eb61f1 · outbound

This paper cites Compression Scaling Laws:Unifying Sparsity and Quantization.

Scaling Law for Quantization-Aware Training Compression Scaling Laws:Unifying Sparsity and Quantization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:06.287977Z

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Observation 1c50a440-80ff-4b2a-84ea-1d8a8f40ed31 · outbound

This paper cites Language models scale reliably with over-training and on downstream tasks.

Scaling Law for Quantization-Aware Training Language models scale reliably with over-training and on downstream tasks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:06.383153Z

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Observation fa166223-cc23-4f58-83c8-9c18fe01deed · outbound

This paper cites Mathematics of computation.American Mathematical Society, 24:23, 1970.

Scaling Law for Quantization-Aware Training Mathematics of computation.American Mathematical Society, 24:23, 1970

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:10.204235Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 10662844-c3c7-4753-b1fa-8e93c71f7092 · outbound

This paper cites The Llama 3 Herd of Models.

Scaling Law for Quantization-Aware Training The Llama 3 Herd of Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:06.585810Z

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Observation 70952f4d-def8-436c-b2de-26463ab88f20 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Scaling Law for Quantization-Aware Training Training Compute-Optimal Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:06.678870Z

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Observation df94132b-c2da-409c-98d2-6c8d43edafac · outbound

This paper cites an unresolved cited work.

Scaling Law for Quantization-Aware Training Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:06.818295Z

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Observation 60625648-4231-490d-aba4-ad236aaf48fa · outbound

This paper cites A Study of BFLOAT16 for Deep Learning Training.

Scaling Law for Quantization-Aware Training A Study of BFLOAT16 for Deep Learning Training

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:06.921374Z

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Observation 215202ff-a5b5-475c-b11c-34e1cd8d044e · outbound

This paper cites Scaling Laws for Neural Language Models.

Scaling Law for Quantization-Aware Training Scaling Laws for Neural Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.010048Z

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Observation 5ce689b7-426f-4e5f-8f35-fb0f2daa6f2d · outbound

This paper cites Scaling Laws for Precision.

Scaling Law for Quantization-Aware Training Scaling Laws for Precision

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.082716Z

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Observation 4104ab95-42d0-4deb-8b00-966762ab9d89 · outbound

This paper cites Predictable Scale: Part I, Step Law -- Optimal Hyperparameter Scaling Law in Large Language Model Pretraining.

Scaling Law for Quantization-Aware Training Predictable Scale: Part I, Step Law -- Optimal Hyperparameter Scaling Law in Large Language Model Pretraining

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.209817Z

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Observation ea88425f-0a16-4ce2-9567-f92c3927c428 · outbound

This paper cites Svdqunat: Absorbing outliers by low-rank components for 4-bit diffusion models.arXiv preprint arXiv:2411.05007, 2024.

Scaling Law for Quantization-Aware Training Svdqunat: Absorbing outliers by low-rank components for 4-bit diffusion models.arXiv preprint arXiv:2411.05007, 2024

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.305818Z

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Observation e2efac40-1122-46b6-b68b-d5ce2766f56e · outbound

This paper cites AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration.

Scaling Law for Quantization-Aware Training AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.407101Z

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Observation 9a386d66-5d85-417b-933a-32d68b6a6fe4 · outbound

This paper cites DeepSeek-V3 Technical Report.

Scaling Law for Quantization-Aware Training DeepSeek-V3 Technical Report

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.468951Z

Source-reported events for the cited work

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Observation 08e57eb2-f5df-47b9-9eec-83e88e6ee691 · outbound

This paper cites Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models.

Scaling Law for Quantization-Aware Training Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.584041Z

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Observation 01c85478-12b4-4632-a43f-bdb6171e44e0 · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

Scaling Law for Quantization-Aware Training SpinQuant: LLM quantization with learned rotations

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.657920Z

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Observation 6cb3d514-02c5-4468-9439-ed8b7220c167 · outbound

This paper cites Paretoq: Scaling laws in extremely low-bit llm quantization.arXiv preprint arXiv:2502.02631, 2025.

Scaling Law for Quantization-Aware Training Paretoq: Scaling laws in extremely low-bit llm quantization.arXiv preprint arXiv:2502.02631, 2025

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.715662Z

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Observation 6af10574-3c48-4c09-ba65-7a7e18cf931d · outbound

This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

Scaling Law for Quantization-Aware Training The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.779945Z

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Observation 1eabd452-370b-430c-924e-e12ba898c7e7 · outbound

This paper cites Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization.

Scaling Law for Quantization-Aware Training Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.875870Z

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Observation d00b3f19-8afd-4a88-a38c-851596f59091 · outbound

This paper cites 2 OLMo 2 Furious.

Scaling Law for Quantization-Aware Training 2 OLMo 2 Furious

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:07.983240Z

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Observation 6c252e7d-47d1-4d0f-9ca1-9490a2a02c51 · outbound

This paper cites Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens.

Scaling Law for Quantization-Aware Training Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.080609Z

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Observation 0d03675b-b4af-43a8-9b9a-58862f3451e3 · outbound

This paper cites QuEST: Stable Training of LLMs with 1-Bit Weights and Activations.

Scaling Law for Quantization-Aware Training QuEST: Stable Training of LLMs with 1-Bit Weights and Activations

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.146988Z

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Observation 8fce1a7a-1080-4413-84fb-cb17fd1a81d6 · outbound

This paper cites FP8-LM: Training FP8 Large Language Models.

Scaling Law for Quantization-Aware Training FP8-LM: Training FP8 Large Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.205307Z

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Observation e0aade8b-4176-40b5-9bad-2d26c00f6f3f · outbound

This paper cites Microscaling Data Formats for Deep Learning.

Scaling Law for Quantization-Aware Training Microscaling Data Formats for Deep Learning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.331673Z

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Observation 1f0aa7f4-0c2a-418b-96ad-ecdc53f7bc62 · outbound

This paper cites Seed1.5-thinking: Advancing superb reasoning models with reinforcement learning.arXiv preprint arXiv:2504.13914, 2025.

Scaling Law for Quantization-Aware Training Seed1.5-thinking: Advancing superb reasoning models with reinforcement learning.arXiv preprint arXiv:2504.13914, 2025

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.446023Z

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Observation 1f080767-53a3-48c0-b9f6-15ad216f506c · outbound

This paper cites OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models.

Scaling Law for Quantization-Aware Training OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.567630Z

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Observation 55bb6485-ba0e-4735-a6de-d2c9bcd8dbeb · outbound

This paper cites GLU Variants Improve Transformer.

Scaling Law for Quantization-Aware Training GLU Variants Improve Transformer

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.690152Z

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Observation b5cf86ae-758d-424a-b787-5db412bc7dc7 · outbound

This paper cites Scaling Laws for Floating Point Quantization Training.

Scaling Law for Quantization-Aware Training Scaling Laws for Floating Point Quantization Training

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.770397Z

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Observation 9c62804d-be7c-4241-939c-aaa8d16d30ba · outbound

This paper cites Training LLMs with MXFP4.

Scaling Law for Quantization-Aware Training Training LLMs with MXFP4

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.862934Z

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Observation ec36895e-8ba7-47f7-be3d-19cb69ded4cc · outbound

This paper cites BitNet a4.8: 4-bit Activations for 1-bit LLMs.

Scaling Law for Quantization-Aware Training BitNet a4.8: 4-bit Activations for 1-bit LLMs

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:08.943376Z

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Observation 5d6fe3e8-7784-418c-a16d-6a97d0c84444 · outbound

This paper cites Optimizing Large Language Model Training Using FP4 Quantization.

Scaling Law for Quantization-Aware Training Optimizing Large Language Model Training Using FP4 Quantization

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:09.035320Z

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Observation 09df09a8-3320-49cc-bb25-02aaa7d0d225 · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models.

Scaling Law for Quantization-Aware Training Smoothquant: Accurate and efficient post-training quantization for large language models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:09.118089Z

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Observation ecca2898-dbd4-46c9-b25a-38c76e1393d0 · outbound

This paper cites LLM Inference Unveiled: Survey and Roofline Model Insights.

Scaling Law for Quantization-Aware Training LLM Inference Unveiled: Survey and Roofline Model Insights

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:09.214394Z

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Observation 90f8cfd0-4918-4aef-831d-3931fb1084c7 · outbound

This paper cites Accurate INT8 Training Through Dynamic Block-Level Fallback.

Scaling Law for Quantization-Aware Training Accurate INT8 Training Through Dynamic Block-Level Fallback

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:09.309660Z

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Observation c09ac455-b575-4ebb-99dd-4052e946f812 · outbound

This paper cites An Empirical Study of Qwen3 Quantization.

Scaling Law for Quantization-Aware Training An Empirical Study of Qwen3 Quantization

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:09.367262Z

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Observation 83d0fa69-6442-4f7b-8d99-a54054ed5bb1 · outbound

This paper cites A Survey on Efficient Inference for Large Language Models.

Scaling Law for Quantization-Aware Training A Survey on Efficient Inference for Large Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:09.461235Z

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Pith citing papers

Observation 29230e97-6ab5-4f76-b4cd-0ae41a7c2b4f · inbound

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs cites this paper.

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs Scaling Law for Quantization-Aware Training

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-18T05:30:55.053160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 075e0595-15e1-411a-8f9d-235a7ed50c94 · inbound

NVIDIA Nemotron 3: Efficient and Open Intelligence cites this paper.

NVIDIA Nemotron 3: Efficient and Open Intelligence Scaling Law for Quantization-Aware Training

Reference 197

Resolution: verified exact; arxiv_id, observed 2026-05-18T01:40:42.766329Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0c792bf6-3b7a-4016-bc8e-bcddde0b31a7 · inbound

Efficient Reasoning on the Edge cites this paper.

Efficient Reasoning on the Edge Scaling Law for Quantization-Aware Training

Reference 110

Resolution: unresolved; no resolver link, observed 2026-07-13T23:28:12.790404Z

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Observation 7729d0c6-9271-450c-ae88-41f708d5c269 · inbound

When Flat Minima Fail: Characterizing INT4 Quantization Collapse After FP32 Convergence cites this paper.

When Flat Minima Fail: Characterizing INT4 Quantization Collapse After FP32 Convergence Scaling Law for Quantization-Aware Training

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:20.811947Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 325ad9e5-98d7-48e3-8ae5-9ac037940e5b · inbound

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing cites this paper.

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing Scaling Law for Quantization-Aware Training

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:47:28.472823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8ee2f68a-0091-4da2-ac86-835dc4603600 · inbound

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing cites this paper.

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing Scaling Law for Quantization-Aware Training

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-30T11:24:38.674059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.