Paper Citation Record · LEDGER

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators

As of 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2602.22352.

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

pith.paper-citation-record.v1
2602.22352 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:47:52.010550Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

19 of 19 outbound references displayed

verified exact0
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 149b56eb-febf-4e38-a660-8b45d2499c53 · outbound

This paper cites FINN: A framework for fast, scalable binarized neural network inference.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators FINN: A framework for fast, scalable binarized neural network inference

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:50.521086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d59770c5-b490-4668-b202-6a70ac3a57bf · outbound

This paper cites FINN-R: An end-to-end deep-learning frame- work for fast exploration of quantized neural networks.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators FINN-R: An end-to-end deep-learning frame- work for fast exploration of quantized neural networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:50.651140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b192046-ac01-41c6-a1a2-1fda3e92ec40 · outbound

This paper cites Bitwise Systolic Array Architecture for Runtime-Reconfigurable Multi-Precision Quantized Multiplication on Hardware Accelerators.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Bitwise Systolic Array Architecture for Runtime-Reconfigurable Multi-Precision Quantized Multiplication on Hardware Accelerators

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:50.745626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a53eef20-5c48-445e-9276-55cbea287cd5 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators The mnist database of handwritten digit images for machine learning research

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:50.821633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55a50913-55e7-45db-87e7-68861ebf994c · outbound

This paper cites Sigmoid-weighted lin- ear units for neural network function approximation in reinforcement learning.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Sigmoid-weighted lin- ear units for neural network function approximation in reinforcement learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:50.889534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c4e25d1-5fad-4734-91fb-244782d18a32 · outbound

This paper cites Neural networks with digital LUT activation functions.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Neural networks with digital LUT activation functions

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:50.969543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89aaa6c3-135a-4d8a-8adc-4442f4c19e5d · outbound

This paper cites Design and FPGA Implementation of the LUT based Sigmoid Function for DNN Applications.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Design and FPGA Implementation of the LUT based Sigmoid Function for DNN Applications

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.053837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c1d8a3f-de35-405a-bcdb-7d6d63f901aa · outbound

This paper cites An optimized lookup-table for the evaluation of sigmoid function for artificial neural networks.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators An optimized lookup-table for the evaluation of sigmoid function for artificial neural networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.121950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82a87ef1-702c-4f0f-8674-c5e7dc569f41 · outbound

This paper cites Sig- moid generators for neural computing using piecewise approxima- tions.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Sig- moid generators for neural computing using piecewise approxima- tions

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.202564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55060a08-6197-4962-9a2a-255ebe8460e6 · outbound

This paper cites FPGA Implementation for the Sigmoid with Piecewise Linear Fitting Method Based on Curvature Analysis.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators FPGA Implementation for the Sigmoid with Piecewise Linear Fitting Method Based on Curvature Analysis

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.296328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 962234c1-d7e5-47ed-a129-e9edc6d1485e · outbound

This paper cites Hardware Implementation of Sigmoid Activation Functions using FPGA.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Hardware Implementation of Sigmoid Activation Functions using FPGA

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.395155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b6f41f7-b752-4d46-9861-67ec8d485f78 · outbound

This paper cites Low Complexity Sigmoid Function Implementation Using Probability-Based Piecewise Linear Function.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Low Complexity Sigmoid Function Implementation Using Probability-Based Piecewise Linear Function

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.484940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afa220af-5b99-41c5-a32c-c8e599a34465 · outbound

This paper cites Cost effective Tanh activation function circuits based on fast piecewise linear logic.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Cost effective Tanh activation function circuits based on fast piecewise linear logic

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.544666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0e5eb6c-e04e-4574-b4b7-46a5cf60e6c6 · outbound

This paper cites Hardware Implementation of Tanh Exponential Activation Function using FPGA.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Hardware Implementation of Tanh Exponential Activation Function using FPGA

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.623183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8acb6229-e923-4a9f-9c3c-873ec0b23145 · outbound

This paper cites Power-of-Two Quantization for Low Bitwidth and Hardware Compliant Neural Networks.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Power-of-Two Quantization for Low Bitwidth and Hardware Compliant Neural Networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.706464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3290b408-9e7d-4521-8bb7-de67f77074fd · outbound

This paper cites Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.784991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 395c6437-a5b3-46d2-9283-7f4ec93e00d7 · outbound

This paper cites Jekel and Gerhard Venter.pwlf: A Python Library for Fitting 1D Continuous Piecewise Linear Functions.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Jekel and Gerhard Venter.pwlf: A Python Library for Fitting 1D Continuous Piecewise Linear Functions

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.868397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b6d6c4a-a604-4015-919d-696d19f0e145 · outbound

This paper cites an unresolved cited work.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.951548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a723fc4b-c60b-4df6-ac4d-dcd158c1e279 · outbound

This paper cites Learning multiple layers of features from tiny images.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Learning multiple layers of features from tiny images

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:52.010550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.