Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2004.09602.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:49:37.533756Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
218
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation 1b7ac546-f2c6-47a8-94d8-29d51490788e · inbound
LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 170
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7f7950c7-18ea-4467-ab28-d3572da8b7d6 · inbound
FP8 Formats for Deep Learning Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 23
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 6987a822-5131-46eb-8a78-4b2cbcec28c5 · inbound
Adaptive Semantic Token Communication for Transformer-based Edge Inference Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 30
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) Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 5
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 46
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 37
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) Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 22
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 64
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 29
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 171
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 2020
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 56
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 40
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b11c958c-c8e7-41db-be04-b9420632ae17 · inbound
Quantamination: Dynamic Quantization Leaks Your Data Across the Batch Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 298aa269-ad3f-4f13-b0ef-4502da03ce3b · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d5c3725f-3028-447b-afa4-a2894fe57f4f · inbound
QuIDE: Mastering the Quantized Intelligence Trade-off via Active Optimization Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 92293adb-0d91-4667-9e23-3c8a73a98f9e · inbound
QuantSR+: Pushing the Limit of Quantized Image Super-Resolution Networks Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 55
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 75f74f80-d2c1-4287-a2da-7561e066b15b · inbound
Transformers Provably Learn to Internalize Chain-of-Thought Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 51
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e7c9e099-038b-4cdc-81b4-76f93b3a840d · inbound
Learning through Internalization Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 15487451-e522-402f-8682-57d9ced1c672 · inbound
Jack of All Scales: A Versatile FPGA Tensor Block for MXFP Precisions Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 4
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 2018
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 28
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 Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.