Paper Citation Record · LEDGER

Scaling Laws for Precision

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2411.04330.

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

pith.paper-citation-record.v1
2411.04330 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:03:32.870353Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 98bedbf5-bc7e-48c4-a7e1-55c5c71294a9 · inbound

A Layered Architecture for Developing and Enhancing Capabilities in Large Language Model-based Software Systems cites this paper.

A Layered Architecture for Developing and Enhancing Capabilities in Large Language Model-based Software Systems Scaling Laws for Precision

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-12T17:38:41.667061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efedcb71-c729-4166-8787-d56087dc302c · inbound

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

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

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T11:54:14.243786Z

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Observation b3a8c0a0-d286-4f9f-8434-f67e104cb51a · inbound

INTELLECT-1 Technical Report cites this paper.

INTELLECT-1 Technical Report Scaling Laws for Precision

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T04:44:26.411789Z

Source-reported events for the cited work

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Observation 7ebcf684-9784-4b84-b16c-b8a1dc19ec57 · inbound

MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design cites this paper.

MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design Scaling Laws for Precision

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-23T06:57:40.270961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9e44ba9f-e0ff-4d82-8c56-cf8972fef7d1 · inbound

The Race to Efficiency: A New Perspective on AI Scaling Laws cites this paper.

The Race to Efficiency: A New Perspective on AI Scaling Laws Scaling Laws for Precision

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:55.671900Z

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Observation f6542a55-fcf3-4cce-bdf9-05369c1ece25 · inbound

Physics of Skill Learning cites this paper.

Physics of Skill Learning Scaling Laws for Precision

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T17:20:51.152418Z

Source-reported events for the cited work

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Observation 666f646f-b6b1-47c6-95dd-a7f66d8fcb67 · inbound

Scaling Inference-Efficient Language Models cites this paper.

Scaling Inference-Efficient Language Models Scaling Laws for Precision

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T00:43:28.956199Z

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Observation 08afdb74-a924-4455-b045-0f40949cdcbd · inbound

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

QuEST: Stable Training of LLMs with 1-Bit Weights and Activations Scaling Laws for Precision

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T20:44:48.443920Z

Source-reported events for the cited work

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Observation 4132cec3-9b18-4494-9813-326748b70b12 · inbound

Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient cites this paper.

Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient Scaling Laws for Precision

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:23.536558Z

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Observation 051c004b-2ccf-4e4c-af6b-4ad66df82042 · inbound

Gaussian Weight Sampling for Scalable, Efficient and Stable Pseudo-Quantization Training cites this paper.

Gaussian Weight Sampling for Scalable, Efficient and Stable Pseudo-Quantization Training Scaling Laws for Precision

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T21:03:32.870353Z

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

Scaling Law for Quantization-Aware Training cites this paper.

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 4c7422eb-915f-4c85-9266-3449b88e1a37 · inbound

Reasoning Like an Economist: Post-Training on Economic Problems Induces Strategic Generalization in LLMs cites this paper.

Reasoning Like an Economist: Post-Training on Economic Problems Induces Strategic Generalization in LLMs Scaling Laws for Precision

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T12:06:24.610518Z

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Observation be96af55-4446-4678-965c-8464ab15f5b4 · inbound

Unified Scaling Laws for Compressed Representations cites this paper.

Unified Scaling Laws for Compressed Representations Scaling Laws for Precision

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:07.103756Z

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Observation 1d234a47-80c2-4656-af6e-d0da2da7c236 · inbound

Kinetics: Rethinking Test-Time Scaling Laws cites this paper.

Kinetics: Rethinking Test-Time Scaling Laws Scaling Laws for Precision

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:34.276380Z

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Observation d7e4579b-32d9-4e9f-88f3-5b8ebf06383d · inbound

Predictable Scale: Part II, Farseer: A Refined Scaling Law in Large Language Models cites this paper.

Predictable Scale: Part II, Farseer: A Refined Scaling Law in Large Language Models Scaling Laws for Precision

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T04:21:29.346210Z

Source-reported events for the cited work

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Observation 4380e891-2ae2-4b64-a401-36da515700d0 · inbound

Characterization and Mitigation of Training Instabilities in Microscaling Formats cites this paper.

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

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T22:47:52.235193Z

Source-reported events for the cited work

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Observation 896b51bb-cf59-40a2-ac90-ec1d324084a8 · inbound

LRM-1B: Towards Large Routing Model cites this paper.

LRM-1B: Towards Large Routing Model Scaling Laws for Precision

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T20:20:44.174979Z

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Observation 4926aa8e-9bf8-4ca7-8267-7d332fcbfd78 · inbound

QS4D: Quantization-aware training for efficient hardware deployment of structured state-space sequential models cites this paper.

QS4D: Quantization-aware training for efficient hardware deployment of structured state-space sequential models Scaling Laws for Precision

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T19:16:25.036428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e91b256-0d82-4bcd-ad0d-353c4c24d757 · inbound

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration cites this paper.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Scaling Laws for Precision

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:33.959039Z

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Unavailable: canonical work link unavailable.

Observation 77a1a9f5-b51f-4a18-b02d-d7fb973e58e6 · inbound

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

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs Scaling Laws for Precision

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T05:30:55.061410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 55f10632-c74f-4610-a32d-ddbc3da57613 · inbound

CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training cites this paper.

CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training Scaling Laws for Precision

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T08:50:46.192841Z

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Observation 7737ce5a-5f63-4d95-a054-21c4bf0edb50 · inbound

Continued AI Scaling Requires Repeated Efficiency Doublings cites this paper.

Continued AI Scaling Requires Repeated Efficiency Doublings Scaling Laws for Precision

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:32:58.868260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 91c0a9ba-9230-4ba0-a128-f219dd32f689 · inbound

Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models cites this paper.

Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models Scaling Laws for Precision

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T11:25:18.548606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d48861ed-1443-4717-97ae-9a85b91220e1 · inbound

On the Quantization Robustness of Diffusion Language Models in Coding Benchmarks cites this paper.

On the Quantization Robustness of Diffusion Language Models in Coding Benchmarks Scaling Laws for Precision

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T00:24:47.008477Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c4223ed8-f9e8-4f6a-8761-3b3611edde8c · inbound

A Hardware-Aware, Per-Layer Methodology for Post-Training Quantization of Large Language Models cites this paper.

A Hardware-Aware, Per-Layer Methodology for Post-Training Quantization of Large Language Models Scaling Laws for Precision

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:05:03.951165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 508a95a2-2afe-4c7e-94d1-46f23da5fa1a · inbound

Asymmetric Scaling Laws from Sparse Features cites this paper.

Asymmetric Scaling Laws from Sparse Features Scaling Laws for Precision

Reference 23

Resolution: metadata mismatch; arxiv_id, observed 2026-05-25T03:20:16.932922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 23864b76-d090-4a95-b643-dd81ceecb4cb · inbound

LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws cites this paper.

LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws Scaling Laws for Precision

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:35:21.781093Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d56d4330-afff-4cf2-b55b-6864e4d2789b · inbound

When NPUs Are Not Always Faster: A Stage-Level Analysis of Mobile LLM Inference cites this paper.

When NPUs Are Not Always Faster: A Stage-Level Analysis of Mobile LLM Inference Scaling Laws for Precision

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T15:04:46.177292Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0f74a084-582a-4c67-a1d0-66f1e3bcb47c · inbound

GoldenFloat: A Phi-Derived Static-Split Floating-Point Family from GF4 to GF1024 with a Lucas-Exact Integer Identity cites this paper.

GoldenFloat: A Phi-Derived Static-Split Floating-Point Family from GF4 to GF1024 with a Lucas-Exact Integer Identity Scaling Laws for Precision

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:26:54.600469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3207bbad-cee5-467a-a870-de7e887ed7f3 · inbound

Reference Traces for Auditing Invisible Weight Updates and Guiding Exact-Budget Protection cites this paper.

Reference Traces for Auditing Invisible Weight Updates and Guiding Exact-Budget Protection Scaling Laws for Precision

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-14T15:32:26.691504Z

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Observation 72ce8324-0291-4f38-b0b6-71069e02c81b · inbound

Reliability Scaling Laws for Quantized Large Language Models cites this paper.

Reliability Scaling Laws for Quantized Large Language Models Scaling Laws for Precision

Reference 136

Resolution: unresolved; no resolver link, observed 2026-07-14T08:45:52.855783Z

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Observation 51b41c23-dda1-41a4-a7a2-c676ac100917 · inbound

Which Decisions Low-Bit Quantization Breaks, and How to Predict Them cites this paper.

Which Decisions Low-Bit Quantization Breaks, and How to Predict Them Scaling Laws for Precision

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T04:22:45.215431Z

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Observation c7775ab7-0c66-4fd6-b83d-96012f15f7b7 · inbound

Which Decisions Low-Bit Quantization Breaks, and How to Predict Them cites this paper.

Which Decisions Low-Bit Quantization Breaks, and How to Predict Them Scaling Laws for Precision

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T04:17:46.220805Z

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