Paper Citation Record · LEDGER

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers

As of 16 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:1909.02384.

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

pith.paper-citation-record.v1
1909.02384 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:55:40.220649Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

verified exact1
verified fuzzy20
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 56340b36-44b1-4eee-8b1b-e6c8ae8cc5f2 · outbound

This paper cites Deep learning.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Deep learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.002519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 641fb860-9225-430f-84a8-f8ca44933c77 · outbound

This paper cites Image denoising and inpainting with deep neural networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Image denoising and inpainting with deep neural networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.910008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e49c68dc-11af-4539-bba6-75340e9d6dc1 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.888512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5f07f9a1-62a7-4764-810e-84d9bd9eac8e · outbound

This paper cites A uniﬁed archi- tecture for natural language processing: Deep neural networks with multitask learning.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers A uniﬁed archi- tecture for natural language processing: Deep neural networks with multitask learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.872036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 39f4c37b-2509-4b8b-9000-2ac0e49d629b · outbound

This paper cites Creating more intelligent robots through brain-inspired computing.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Creating more intelligent robots through brain-inspired computing

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.854564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4b858031-3ea5-46d6-bffd-71a857e2dabb · outbound

This paper cites Resiliency of Deep Neural Networks under Quantization.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Resiliency of Deep Neural Networks under Quantization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.032273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9817df7a-0064-4c2c-8fe4-b9275b9557ae · outbound

This paper cites Binaryconnect: Training deep neural networks with binary weights during propagations.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Binaryconnect: Training deep neural networks with binary weights during propagations

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.836268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c06fc462-d50c-4fba-b0db-d070854bfa42 · outbound

This paper cites Xnor-net: Imagenet classiﬁcation using binary convolutional neural networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Xnor-net: Imagenet classiﬁcation using binary convolutional neural networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.816459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f8b5225e-5af1-43af-84a8-7f031f0ac840 · outbound

This paper cites Extremely low bit neural network: Squeeze the last bit out with admm.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Extremely low bit neural network: Squeeze the last bit out with admm

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.798979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d9bfcb84-e71c-4990-b981-a95d825cc181 · outbound

This paper cites DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.054463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed344030-fc6c-4040-8475-ea146ae62916 · outbound

This paper cites Gxnor-net: Training deep neural networks with ternary weights and activations without full-precision memory under a uniﬁed discretization framework.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Gxnor-net: Training deep neural networks with ternary weights and activations without full-precision memory under a uniﬁed discretization framework

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.781718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a7048bfa-5013-4379-af02-c9ef3e9b793b · outbound

This paper cites Training deep neural networks with 8-bit ﬂoating point numbers.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Training deep neural networks with 8-bit ﬂoating point numbers

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.764354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 882ed9e3-b476-4be7-93d1-641f8a098414 · outbound

This paper cites Scalable methods for 8-bit training of neural networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Scalable methods for 8-bit training of neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.746428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9a42b818-b4c4-444c-884a-02e5a45b75f7 · outbound

This paper cites Mixed Precision Training.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Mixed Precision Training

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.076096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dedfcac-1d28-43ad-b376-4f933d1a8d95 · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.081586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db6c66e6-c6ea-4f71-a7bd-167175df4a7e · outbound

This paper cites Mixed Precision Training of Convolutional Neural Networks using Integer Operations.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Mixed Precision Training of Convolutional Neural Networks using Integer Operations

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.087288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbd3e87b-a798-4156-884b-1b3a08bf8dd5 · outbound

This paper cites Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-14T04:55:40.430403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0363ad4c-a7c8-4c31-b95f-270b8471b006 · outbound

This paper cites Training and Inference with Integers in Deep Neural Networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Training and Inference with Integers in Deep Neural Networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.097931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8472cee9-1909-4e7c-b19b-3e4c4b5b3139 · outbound

This paper cites Gradient-based learning applied to document recognition.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Gradient-based learning applied to document recognition

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.729263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f7ce22d1-251f-43dd-9c57-349934a018e2 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.110498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7462aca4-b72f-478d-8516-23f63ff9245b · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Imagenet classiﬁcation with deep convolutional neural networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.115929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27005cda-b09d-45b3-ba57-f359b8f44571 · outbound

This paper cites On the momentum term in gradient descent learning algorithms.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers On the momentum term in gradient descent learning algorithms

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.701140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0559da31-5e0a-4c40-bd64-178a21394dd2 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Adam: A Method for Stochastic Optimization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.126318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c65d1dc2-0deb-4dc6-8061-d099dcb8a68b · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Imagenet: A large-scale hierarchical image database

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.133278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ab60a63-eb1b-446a-a7bf-a0094aa2a956 · outbound

This paper cites Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.139318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac307faa-1483-4781-93d3-5dd985a01be2 · outbound

This paper cites Neural networks for machine learning.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Neural networks for machine learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.671001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2fba2dc1-a00f-4b7f-865b-81c120087dcb · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.152554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04700e4d-f39a-4818-93ca-e38e0ef61375 · outbound

This paper cites Quantized neural net- works: Training neural networks with low precision weights and activations.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Quantized neural net- works: Training neural networks with low precision weights and activations

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.652808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c68ea7c8-1550-4c8f-a141-0430df83a85a · outbound

This paper cites Balanced quantization: An effec- tive and efﬁcient approach to quantized neural net- works.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Balanced quantization: An effec- tive and efﬁcient approach to quantized neural net- works

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.636724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 97578bb7-ad9e-4672-8d10-7906ba0a6a3d · outbound

This paper cites Effective Quantization Methods for Recurrent Neural Networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Effective Quantization Methods for Recurrent Neural Networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.171457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8078d51f-9396-40e5-a5f2-0be8dff967c4 · outbound

This paper cites Delving deep into rectiﬁers: Surpassing human-level performance on imagenet classiﬁcation.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Delving deep into rectiﬁers: Surpassing human-level performance on imagenet classiﬁcation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.618854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2959e482-c4db-4459-8fa4-6ad32a10b9c9 · outbound

This paper cites Tbn: Convolutional neural network with ternary inputs and binary weights.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Tbn: Convolutional neural network with ternary inputs and binary weights

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.183242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a416904-c95e-46ec-8bcd-7b13a759682b · outbound

This paper cites Learning Sparse Low-Precision Neural Networks With Learnable Regularization.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Learning Sparse Low-Precision Neural Networks With Learnable Regularization

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.188754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 624e5afb-7177-4c57-a61a-8f658e4eb677 · outbound

This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-14T04:55:40.195575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27e7c669-3d03-4a43-9c6e-f493e8ce15fa · outbound

This paper cites Using learning rate schedules for deep learning models in python with keras, 2016.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Using learning rate schedules for deep learning models in python with keras, 2016

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.592786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a7d6e19a-7ffd-42c7-91dc-ff94b17d43b6 · outbound

This paper cites Learning rate schedules and adaptive learning rate methods for deep learning.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Learning rate schedules and adaptive learning rate methods for deep learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.575213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1a0478b5-6b47-404e-9633-0499f7b3fc5a · outbound

This paper cites Finite-time bound- edness of large-scale systems with actuator faults and gain ﬂuctuations.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Finite-time bound- edness of large-scale systems with actuator faults and gain ﬂuctuations

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.556895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 714f30a4-387e-4a76-8760-24089f2b3f11 · outbound

This paper cites Single precision in weather forecasting models: An evaluation with the ifs.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Single precision in weather forecasting models: An evaluation with the ifs

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:55:40.538897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.