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Paper Citation Record · LEDGER

Scaling Laws for Precision

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 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 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:44:48.443920Z

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

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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 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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T06:56:51.829741Z digest=sha256:66233676132b4b6ef393955d8ed8dee8ff569940b4d0f6e7069963677f8318df

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

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T20:44:48.443920Z digest=sha256:3b09e87383c3860ed01706b5fae736ad8bbabdbebcd0ae2ec9d9e22721701123

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

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

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source=arxiv_source observed=2026-08-08T20:06:23.536558Z digest=sha256:723924ed4fa9692fc09dfd202ca42f63a92ff976df3291fd4f95245b22648b62

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

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

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source=pdf_text observed=2026-08-07T15:41:07.082716Z digest=sha256:05c48b3de33d156109d9a9aad45cc0ce8e19fbaef054c887be8f98bb058764b8

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

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:06:24.610518Z digest=sha256:fb59e6a3e7628c13b3eeac7f3aafd1df9911b601356ef806e01af4042b1ecde0

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

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:40:07.103756Z digest=sha256:530174b8579f8d11033b5f217525e88b65646d80c47b9d7715b65626552fe640

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

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source=pdf_text observed=2026-08-07T10:30:34.276380Z digest=sha256:d0e3d7a33d90f8bfd61bfe364081b9cc7fa61c594e33350494008e3f3ebeaf31

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

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

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source=pdf_text observed=2026-08-07T04:21:29.346210Z digest=sha256:24ad7afc2b9c4edf56471f5e991d3c6753152e951a9b0691978b742afe168987

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

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:47:52.235193Z digest=sha256:d2177136ba04c62ced1066c3a7dd54a3652be92765e11a41819336121498c816

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

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

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source=pdf_text observed=2026-08-06T20:20:44.174979Z digest=sha256:08ac965c940b08413af072ac99ddd1b5e86a530b30c2de6b7cdf7ae4e96283f0

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

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

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source=arxiv_source observed=2026-08-06T19:16:25.036428Z digest=sha256:811c59d22bd402060388b7397913749ecb8ddb3b660344079c0b9bd4aae304ba

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

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source=pdf_text observed=2026-08-06T11:15:33.959039Z digest=sha256:e81fe5ef78ab53551a8b84404d46ab82d861c06db68551cba2eefaa9e0b4e4d6

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T05:30:11.389756Z digest=sha256:b8ee6520939ad0bf51e5f3497a8bc04aac4fa30916e20fd89841f612d7676b94

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

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

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source=pdf_text observed=2026-08-04T08:50:46.192841Z digest=sha256:72b6afba2e1e1d66c2aacd6067ee19a8501c53bb32d6ceb61ea1f7ed6d55f4b2

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T21:31:05.116491Z digest=sha256:85e9d6d63ec13f8e9eb54b13959927306bbefb20af1c8bbaa09c918e94799a2d

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

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arxiv_id, observed 2026-05-10T11:25:18.548606Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T11:23:46.371799Z digest=sha256:5a8ac29565eec27989b0dd2da64b086ba5d41b9e912481b17dd0d19bdcd34e61

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

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arxiv_id, observed 2026-05-10T00:24:47.008477Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T00:21:30.101748Z digest=sha256:0296fa9047dd60a997e9a82f8cfa61acca73d71386e0c4553daefdb870166a69

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

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arxiv_id, observed 2026-06-30T21:05:03.951165Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-30T21:03:05.361805Z digest=sha256:8fe5c4f3aa82c0433d341caa9372e80a8a4b1c8aea2f8d5662971999fbdeac60

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

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arxiv_id, observed 2026-05-25T03:20:16.932922Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-25T03:16:34.488732Z digest=sha256:234ae011ade4806441f70fbdcd209527496cc9ff1808aeb5e97dd9e999c7d231

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

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arxiv_id, observed 2026-05-25T04:35:21.781093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T04:30:35.962947Z digest=sha256:a7a5070559cab4a10d01f1104f181500c1084d26d3a96d0b4268129cd1374763

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

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arxiv_id, observed 2026-06-30T15:04:46.177292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T15:03:31.289211Z digest=sha256:757c3c027d0a8fe12d2cd54cb171918f816d2edd6441aed543f02743f698cae7

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

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arxiv_id, observed 2026-07-02T11:26:54.600469Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T03:47:27.000639Z digest=sha256:bd316451ee0ed57485fc1c1d8c97f833830a2e75d51dbfd2486c3992219bdffe

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

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source=pdf_text observed=2026-07-14T15:32:26.691504Z digest=sha256:5f9ab318da0f92fa31b9589e2739a08c6183d50790b643187a37ef3d77360777

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

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source=arxiv_source observed=2026-07-14T08:45:52.855783Z digest=sha256:ee008eeef5a7e66ced158508dda5298e81dba920551be82aa3e6c91dae0db443