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Paper Citation Record · LEDGER

Training and Inference with Integers in Deep Neural Networks

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1802.04680.

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

pith.paper-citation-record.v1
1802.04680 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:19:02.739548Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T23:06:37.351791Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 62640ac9-84f5-49c3-983e-5a3df540eaac · inbound

QUOTIENT: Two-Party Secure Neural Network Training and Prediction cites this paper.

QUOTIENT: Two-Party Secure Neural Network Training and Prediction Training and Inference with Integers in Deep Neural Networks

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-05-25T01:35:10.901131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-25T01:34:20.415209Z digest=sha256:ee6b786752e30992e0ec46894630c2be0025a805c0dd81d981b5f5e4e5c3b4a1

Observation 8a0ce02a-27cd-472c-ba16-c7bd071cb72f · inbound

Group Pruning using a Bounded-Lp norm for Group Gating and Regularization cites this paper.

Group Pruning using a Bounded-Lp norm for Group Gating and Regularization Training and Inference with Integers in Deep Neural Networks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-14T14:19:02.739548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:19:02.739548Z digest=sha256:6879d5d363b521b96594f1f5bc460d516c663be436484273c588e1fed1158479

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

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers cites this paper.

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.

source=pdf_text observed=2026-08-14T04:55:40.097931Z digest=sha256:f4ec007b35a6c9057ff9180478dfb40d9b301799e4021810a8ec7b69a6c6a68f

Observation c15abd36-b362-41b4-ac51-164b39a21e4e · inbound

Characterization and Mitigation of ADC Noise by Reference Tuning in RRAM-Based Compute-In-Memory cites this paper.

Characterization and Mitigation of ADC Noise by Reference Tuning in RRAM-Based Compute-In-Memory Training and Inference with Integers in Deep Neural Networks

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-08T17:19:05.726112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:19:05.726112Z digest=sha256:cfecab442d7183d47e2c225a79ccb0a56466b23b9c0a72f981c0f97c2598f160

Observation ed31636e-b0d1-4176-ad4b-9f299942cbcd · inbound

Exploring Vision Neural Network Pruning via Screening Methodology cites this paper.

Exploring Vision Neural Network Pruning via Screening Methodology Training and Inference with Integers in Deep Neural Networks

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-05-23T03:35:21.038411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-23T03:33:15.015365Z digest=sha256:aabe12d0b70f35dc316270e258ae2d5c7190c6920eca5db48682d80c3f25e023

Observation 37a05b00-9283-4024-9987-4eb4d9ec0293 · inbound

Refining Datapath for Microscaling ViTs cites this paper.

Refining Datapath for Microscaling ViTs Training and Inference with Integers in Deep Neural Networks

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:17.550384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:17.550384Z digest=sha256:42d46aeb88e5f789ead095b7e2bf8b751420f3a787ceb64b743425d12ae27177

Observation 8a7f6e0e-1eb1-43c2-977d-e86dc009be8f · inbound

A Comprehensive FP8 Training Recipe for Reasoning-Enhanced Language Models cites this paper.

A Comprehensive FP8 Training Recipe for Reasoning-Enhanced Language Models Training and Inference with Integers in Deep Neural Networks

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-04T14:51:29.998997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T14:51:29.998997Z digest=sha256:d7f430955a6ff37d5d1584803be7705a23999b8a9c397ad3a30f0acb48a37418

Observation dc152c6a-8e49-4ee8-9afe-af9a7abdbd0e · inbound

Latency-Constrained DNN Architecture Learning for Edge Systems using Zerorized Batch Normalization cites this paper.

Latency-Constrained DNN Architecture Learning for Edge Systems using Zerorized Batch Normalization Training and Inference with Integers in Deep Neural Networks

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-07-09T23:06:37.352960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-09T23:00:38.689966Z digest=sha256:78d6a9a75c44cee83619d48938710d524bc542ccd04c824a1b906a1e1a9865a9

Observation 7d6d94c7-b24b-4ff5-8902-0908deeff82e · inbound

APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning cites this paper.

APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning Training and Inference with Integers in Deep Neural Networks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T12:00:53.848227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:00:53.848227Z digest=sha256:ddc44e93db2faba9f43cc2a6e2449ef7bf12bff01a8652032146521faac31c51