Paper Citation Record · LEDGER

Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2004.09602.

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

pith.paper-citation-record.v1
2004.09602 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 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 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:48:57.416043Z

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
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

218
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 1b7ac546-f2c6-47a8-94d8-29d51490788e · inbound

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale cites this paper.

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 170

Resolution: verified exact; arxiv_id, observed 2026-05-13T13:35:36.181856Z

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.

Observation 7f7950c7-18ea-4467-ab28-d3572da8b7d6 · inbound

FP8 Formats for Deep Learning cites this paper.

FP8 Formats for Deep Learning Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-15T09:47:03.823240Z

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.

Observation 2c44be9d-2733-408d-9782-b296bbd94d07 · inbound

Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity cites this paper.

Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-09T15:48:57.416043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fe6532d-b2bf-4128-b300-c6d16d6d1885 · inbound

Exploring Model Invariance with Discrete Search for Ultra-Low-Bit Quantization cites this paper.

Exploring Model Invariance with Discrete Search for Ultra-Low-Bit Quantization Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-08T22:37:02.580336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6987a822-5131-46eb-8a78-4b2cbcec28c5 · inbound

Adaptive Semantic Token Communication for Transformer-based Edge Inference cites this paper.

Adaptive Semantic Token Communication for Transformer-based Edge Inference Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:49:37.533756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba2b57fa-d859-4d6e-8514-009769030acd · inbound

Power-of-Two (PoT) Weights in Large Language Models (LLMs) cites this paper.

Power-of-Two (PoT) Weights in Large Language Models (LLMs) Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T12:12:12.442972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97168a3a-9f63-4c09-88df-0f4a53ed8a5d · inbound

Assigning Distinct Roles to Quantized and Low-Rank Matrices Toward Optimal Weight Decomposition cites this paper.

Assigning Distinct Roles to Quantized and Low-Rank Matrices Toward Optimal Weight Decomposition Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T11:48:04.806412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3259b1b-281b-46b4-8d6f-76daf87549d5 · inbound

Enhancing Automatic PT Tagging for MEDLINE Citations Using Transformer-Based Models cites this paper.

Enhancing Automatic PT Tagging for MEDLINE Citations Using Transformer-Based Models Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T11:09:11.698213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3b3f99f-06db-4ab7-a298-b7d592d8ec7a · inbound

Compress Any Segment Anything Model (SAM) cites this paper.

Compress Any Segment Anything Model (SAM) Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T18:20:01.054268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdc6778d-2a6f-4b35-86d9-374984c81022 · inbound

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization cites this paper.

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-06T16:42:12.199052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45840cbb-72ee-4c4f-8e37-e9f5d9e50cfb · inbound

FlashSVD: Memory-Efficient Inference with Streaming for Low-Rank Models cites this paper.

FlashSVD: Memory-Efficient Inference with Streaming for Low-Rank Models Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T05:40:49.038808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70b0a9f2-3e07-4c69-b13c-7988d25889fd · inbound

Real-Time Analysis of Unstructured Data with Machine Learning on Heterogeneous Architectures cites this paper.

Real-Time Analysis of Unstructured Data with Machine Learning on Heterogeneous Architectures Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 171

Resolution: unresolved; no resolver link, observed 2026-08-05T22:14:25.968694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a4bf14f-38f9-4456-be4f-c72fc3b6e620 · inbound

Float8@2bits: Entropy Coding Enables Data-Free Model Compression cites this paper.

Float8@2bits: Entropy Coding Enables Data-Free Model Compression Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-03T06:31:25.776256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfcbfe30-b875-445e-85a6-b7bf9690cc15 · inbound

DharmaOCR: Specialized Small Language Models for Structured OCR that outperform Open-Source and Commercial Baselines cites this paper.

DharmaOCR: Specialized Small Language Models for Structured OCR that outperform Open-Source and Commercial Baselines Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:20:25.559806Z

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.

Observation ef43d0be-b3b7-4f94-a423-64dbf4425ecb · inbound

Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy cites this paper.

Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:41:09.361664Z

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.

Observation b11c958c-c8e7-41db-be04-b9420632ae17 · inbound

Quantamination: Dynamic Quantization Leaks Your Data Across the Batch cites this paper.

Quantamination: Dynamic Quantization Leaks Your Data Across the Batch Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:26:26.126828Z

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.

Observation 298aa269-ad3f-4f13-b0ef-4502da03ce3b · inbound

Edge AI for Automotive Vulnerable Road User Safety: Deployable Detection via Knowledge Distillation cites this paper.

Edge AI for Automotive Vulnerable Road User Safety: Deployable Detection via Knowledge Distillation Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:36:25.997306Z

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.

Observation d5c3725f-3028-447b-afa4-a2894fe57f4f · inbound

QuIDE: Mastering the Quantized Intelligence Trade-off via Active Optimization cites this paper.

QuIDE: Mastering the Quantized Intelligence Trade-off via Active Optimization Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:52:31.102099Z

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.

Observation 92293adb-0d91-4667-9e23-3c8a73a98f9e · inbound

QuantSR+: Pushing the Limit of Quantized Image Super-Resolution Networks cites this paper.

QuantSR+: Pushing the Limit of Quantized Image Super-Resolution Networks Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:36:10.290668Z

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.

Observation 75f74f80-d2c1-4287-a2da-7561e066b15b · inbound

Transformers Provably Learn to Internalize Chain-of-Thought cites this paper.

Transformers Provably Learn to Internalize Chain-of-Thought Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:33:30.544786Z

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.

Observation e7c9e099-038b-4cdc-81b4-76f93b3a840d · inbound

Learning through Internalization cites this paper.

Learning through Internalization Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T03:39:31.028930Z

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.

Observation 15487451-e522-402f-8682-57d9ced1c672 · inbound

Jack of All Scales: A Versatile FPGA Tensor Block for MXFP Precisions cites this paper.

Jack of All Scales: A Versatile FPGA Tensor Block for MXFP Precisions Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T03:25:29.313595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c3cbe49-3751-4064-9ac4-7c526d9d93fa · inbound

Efficient EEG Seizure Detection Using INT8 Quantization, Channel Pruning, and Spiking Neural Networks cites this paper.

Efficient EEG Seizure Detection Using INT8 Quantization, Channel Pruning, and Spiking Neural Networks Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-02T06:57:39.362250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31666098-4755-48b3-9dea-d1477f05a35e · inbound

INT8 Quantization Makes ARM Edge Inference Dispatch-Invariant cites this paper.

INT8 Quantization Makes ARM Edge Inference Dispatch-Invariant Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T00:06:42.126247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fb0fd25-fcb7-4af6-8c2b-9bf7f723f62f · inbound

Approximate reservoir computing with a semiconductor laser for reducing energy consumption cites this paper.

Approximate reservoir computing with a semiconductor laser for reducing energy consumption Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-31T23:58:12.963140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.