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Paper Citation Record · LEDGER

Integer Binary-Range Alignment Neuron for Spiking Neural Networks

As of 10 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2506.05679.

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

pith.paper-citation-record.v1
2506.05679 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:21:54.043766Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

49 of 49 outbound references displayed

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External citation measurements

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Outbound references

Observation 2f2d121f-4805-442f-b8a7-2193bbd78e4f · outbound

This paper cites Enhancing train- ing of spiking neural network with stochastic latency.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Enhancing train- ing of spiking neural network with stochastic latency

Reference 1

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Observation 4835d836-84d7-469f-bd6e-1ece032c7e25 · outbound

This paper cites Optimal ann-snn conversion for high- accuracy and ultra-low-latency spiking neural networks.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Optimal ann-snn conversion for high- accuracy and ultra-low-latency spiking neural networks

Reference 2

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Observation f4525fb1-bf84-4840-99b6-358d041d92f3 · outbound

This paper cites Spiking deep convolutional neural networks for energy-efficient ob- ject recognition.International Journal of Computer Vision, 113:54–66, 2015.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Spiking deep convolutional neural networks for energy-efficient ob- ject recognition.International Journal of Computer Vision, 113:54–66, 2015

Reference 3

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Observation 42b1fa25-0b6b-45c1-a0d2-d2a19cc09f91 · outbound

This paper cites End-to- end object detection with transformers.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks End-to- end object detection with transformers

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6f759622-cb3f-4224-a403-ea76f0c939a4 · outbound

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

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Imagenet: A large-scale hierarchical image database

Reference 5

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T10:21:53.955107Z digest=sha256:5b7d112f3757a4c23274b7943d93da83b67980013d28ad9feb4481d717f40024

Observation f9a7d1af-f17f-4160-a8b2-cab9fa5ca326 · outbound

This paper cites Deep residual learning in spiking neural networks.Advances in Neural Information Processing Systems, 34:21056–21069, 2021.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Deep residual learning in spiking neural networks.Advances in Neural Information Processing Systems, 34:21056–21069, 2021

Reference 6

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Observation d1a524f4-022f-45f5-9c65-f78e3ff7045b · outbound

This paper cites Incorporating learnable membrane time constant to enhance learning of spiking neu- ral networks.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Incorporating learnable membrane time constant to enhance learning of spiking neu- ral networks

Reference 7

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation eb20e9a2-221b-43f2-b13e-a007d88f8c93 · outbound

This paper cites Im-loss: information maximization loss for spiking neural networks.Advances in Neural Information Processing Systems, 35:156–166, 2022.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Im-loss: information maximization loss for spiking neural networks.Advances in Neural Information Processing Systems, 35:156–166, 2022

Reference 8

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Source-reported events for the cited work

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Observation c8db83ad-465d-4c83-a3aa-b012e0b9454f · outbound

This paper cites Reducing information loss for spiking neural networks.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Reducing information loss for spiking neural networks

Reference 9

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 8f4ab19c-041d-4c8a-81e4-ba3b0a7270ab · outbound

This paper cites Real spike: Learning real-valued spikes for spiking neural net- works.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Real spike: Learning real-valued spikes for spiking neural net- works

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 7419b9e9-24e4-4aad-9992-a17293ceedef · outbound

This paper cites Rmp- loss: Regularizing membrane potential distribution for spik- ing neural networks.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Rmp- loss: Regularizing membrane potential distribution for spik- ing neural networks

Reference 11

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Source-reported events for the cited work

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Observation b4e55554-5671-4b6c-b9a5-d589a811f8fc · outbound

This paper cites Joint a-snn: Joint training of artificial and spiking neural networks via self- distillation and weight factorization.Pattern Recognition, 142:109639, 2023.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Joint a-snn: Joint training of artificial and spiking neural networks via self- distillation and weight factorization.Pattern Recognition, 142:109639, 2023

Reference 12

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Source-reported events for the cited work

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Observation 17567784-0adc-4cf8-b884-412716577c3d · outbound

This paper cites Mem- brane potential batch normalization for spiking neural net- works.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Mem- brane potential batch normalization for spiking neural net- works

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation f8e3ed80-7e98-4574-bec7-47f0a5ee8387 · outbound

This paper cites Ternary spike: Learning ternary spikes for spiking neural networks.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Ternary spike: Learning ternary spikes for spiking neural networks

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 44e2f3c7-db9b-4c2c-b492-84b8e7f69785 · outbound

This paper cites Deep spiking neural network: Energy efficiency through time based coding.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Deep spiking neural network: Energy efficiency through time based coding

Reference 15

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c5628eec-7a48-44aa-b44c-7bf618573c0d · outbound

This paper cites Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural net- work.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural net- work

Reference 16

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 51452714-9b1c-4787-8353-75fe72f50212 · outbound

This paper cites Reducing ann-snn conversion error through residual membrane potential.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Reducing ann-snn conversion error through residual membrane potential

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 7e5e3c6f-0ff5-474a-8203-6a683f65b535 · outbound

This paper cites A progressive training framework for spiking neural networks with learnable multi-hierarchical model.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks A progressive training framework for spiking neural networks with learnable multi-hierarchical model

Reference 18

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Source-reported events for the cited work

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Observation e74458ee-1077-4411-9c1f-073dab828404 · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal co- variate shift.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Batch normalization: Accelerating deep network training by reducing internal co- variate shift

Reference 19

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Observation 0a689bfc-95e7-4b6e-a39f-bfc7c1b6f11f · outbound

This paper cites A unified optimization framework of 9 ann-snn conversion: towards optimal mapping from activa- tion values to firing rates.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks A unified optimization framework of 9 ann-snn conversion: towards optimal mapping from activa- tion values to firing rates

Reference 20

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Observation 436a6ba6-3a51-474a-8ff6-9f85ee999a2d · outbound

This paper cites Tab: Temporal accumulated batch normal- ization in spiking neural networks.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Tab: Temporal accumulated batch normal- ization in spiking neural networks

Reference 21

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Observation 8e0755e3-5589-4871-a843-f648a7133c45 · outbound

This paper cites Towards fast and accurate object detection in bio-inspired spiking neural networks through bayesian optimization.IEEE Access, 9:2633–2643, 2020.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Towards fast and accurate object detection in bio-inspired spiking neural networks through bayesian optimization.IEEE Access, 9:2633–2643, 2020

Reference 22

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 914db46b-4f28-489a-bfab-8f16d624f82d · outbound

This paper cites Spiking-yolo: spiking neural network for energy- efficient object detection.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Spiking-yolo: spiking neural network for energy- efficient object detection

Reference 23

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3c8b5ffa-1987-4baa-8c75-70549b7c994d · outbound

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

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Learning multiple layers of features from tiny images

Reference 24

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Source-reported events for the cited work

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Observation a5742936-e862-466e-a48c-0db9366501e0 · outbound

This paper cites Cifar10-dvs: an event-stream dataset for ob- ject classification.Frontiers in neuroscience, 11:309, 2017.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Cifar10-dvs: an event-stream dataset for ob- ject classification.Frontiers in neuroscience, 11:309, 2017

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 430022cf-3d02-4a3d-a720-78b30d2089f7 · outbound

This paper cites Efficient and accurate conversion of spiking neural network with burst spikes.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Efficient and accurate conversion of spiking neural network with burst spikes

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 5e500c58-0e98-4dc6-803d-aa7fad8c98d2 · outbound

This paper cites A free lunch from ann: Towards efficient, accurate spiking neural networks calibration.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks A free lunch from ann: Towards efficient, accurate spiking neural networks calibration

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 67676293-5b31-4d34-b00a-ff82a62b6cf5 · outbound

This paper cites Spike Calibration: Fast and Accurate Conversion of Spiking Neural Network for Object Detection and Segmentation.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Spike Calibration: Fast and Accurate Conversion of Spiking Neural Network for Object Detection and Segmentation

Reference 28

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verified exact
local_arxiv, observed 2026-08-07T10:21:54.075985Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 63248d31-67ad-475a-a9ea-397a95e37001 · outbound

This paper cites Microsoft coco: Common objects in context.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Microsoft coco: Common objects in context

Reference 29

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unresolved
no resolver link, observed 2026-08-07T10:21:54.003621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:54.003621Z digest=sha256:3e868c59caf7ecd3049c05d6a4508642950205915728af3624add635179cd1b7

Observation 02ffef53-8f6a-46d6-a8ef-b3abae9f2886 · outbound

This paper cites Integer-valued training and spike-driven inference spiking neural network for high-performance and energy-efficient object detection.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Integer-valued training and spike-driven inference spiking neural network for high-performance and energy-efficient object detection

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ec54d304-3b3a-4d8d-822e-63d617a2747e · outbound

This paper cites Training high- performance low-latency spiking neural networks by dif- ferentiation on spike representation.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Training high- performance low-latency spiking neural networks by dif- ferentiation on spike representation

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 71658ba4-8658-4e13-80f8-b5e140d9ef5b · outbound

This paper cites Towards memory-and time-efficient backpropagation for training spiking neural networks.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Towards memory-and time-efficient backpropagation for training spiking neural networks

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 81061fa7-711f-40f8-95ce-c8c101d3c274 · outbound

This paper cites Sign gradient descent-based neuronal dynamics: ANN-to-SNN conversion beyond reLU network.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Sign gradient descent-based neuronal dynamics: ANN-to-SNN conversion beyond reLU network

Reference 33

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raw_fallback, observed 2026-08-07T10:21:54.175598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.011636Z digest=sha256:ee4fffc07bbbced159a24acef90655a078f32b68d2d0b968bcdafac7f8a8b795

Observation 52147e91-ca9b-408d-a26f-18f9a55ce193 · outbound

This paper cites Gated attention coding for training high-performance and efficient spiking neural net- works.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Gated attention coding for training high-performance and efficient spiking neural net- works

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.168253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.013561Z digest=sha256:48e6adfb4f0e06013470befb7b3b1a85579ce878b00780db59ff9c032d7778d8

Observation 785a2b58-f04d-4041-b2c0-f63b6d755404 · outbound

This paper cites Enabling deep spiking neural net- works with hybrid conversion and spike timing dependent backpropagation.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Enabling deep spiking neural net- works with hybrid conversion and spike timing dependent backpropagation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.161311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.015391Z digest=sha256:27a11f0de43185ab77ff3171f7bbf4e948f501fb4176c6a56dac0745ede8428b

Observation d641968e-2b94-4654-9fea-9cfde9208d0d · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.IEEE transactions on pattern analysis and machine intelligence, 39(6):1137–1149, 2016.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Faster r-cnn: Towards real-time object detection with region proposal networks.IEEE transactions on pattern analysis and machine intelligence, 39(6):1137–1149, 2016

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:54.017349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:54.017349Z digest=sha256:0d3cb8ae9fbabb5c0b1fbae91e080d096ed41c2df225087ec79df9dd77baceaf

Observation d074ed90-3837-4e82-a7b1-22d1d35f03a7 · outbound

This paper cites Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:21:54.066988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.019277Z digest=sha256:acb33a685a83fce05d18c795aafe8e75b627ba4be938429d15e126228b37ebd8

Observation 1bff3ad9-9a70-4af9-85b9-15fe6d880866 · outbound

This paper cites Going deeper in spiking neural networks: Vgg and residual architectures.Frontiers in neuroscience, 13:95,.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Going deeper in spiking neural networks: Vgg and residual architectures.Frontiers in neuroscience, 13:95,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.150854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.021447Z digest=sha256:ab981a7f23f057b6b3076e79c9ecedafe7c90fd6357160fbf204635d8f2cc5d6

Observation 6c0f5cda-9463-49e9-9365-e7e932f21e06 · outbound

This paper cites Large language models encode clinical knowledge.Nature, 620 (7972):172–180, 2023.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Large language models encode clinical knowledge.Nature, 620 (7972):172–180, 2023

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:54.023453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:54.023453Z digest=sha256:56ca1097bb3b01b7b60a20796bb3ca37702711c17d50aa9683058685ee8617f1

Observation 3a2c17b6-2e44-4b2e-b4d1-e809cdc4bb1a · outbound

This paper cites Deep directly-trained spik- ing neural networks for object detection.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Deep directly-trained spik- ing neural networks for object detection

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.140555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.025315Z digest=sha256:2c1600261a5755246d6b1abd5234cfccd253e93f9ee033be8e10e2ec0e7401fc

Observation f938f005-db88-496b-b0ad-5b0fa7a97ed7 · outbound

This paper cites YOLOv5: A state-of-the-art real-time object de- tection system.https://docs.ultralytics.com,.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks YOLOv5: A state-of-the-art real-time object de- tection system.https://docs.ultralytics.com,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.133313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.027303Z digest=sha256:2e8f87d64ae21278848103a740505e96d2508d0d62917039ab6b20cc8c6e9bc0

Observation 9ef24e24-4716-4d08-91e7-e3c372eb6669 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:54.031656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:54.031656Z digest=sha256:a69f50bb5baa9d2fa48363869565eb4c9e8fa4a1ddde8d6a695df43eea1e599e

Observation 24706358-ea4b-421f-b209-f661aee9e797 · outbound

This paper cites Direct training for spiking neural networks: Faster, larger, better.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Direct training for spiking neural networks: Faster, larger, better

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.116436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.034276Z digest=sha256:70a6ae4e4a7e1f78b98a72fd770611d3f065ba8c8da1c38067e11f84def7c92e

Observation c761b18f-4be6-4eaa-aceb-cb923cd95ceb · outbound

This paper cites Bkdsnn: Enhancing the performance of learning-based spiking neural networks training with blurred knowledge dis- tillation.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Bkdsnn: Enhancing the performance of learning-based spiking neural networks training with blurred knowledge dis- tillation

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.110206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.036246Z digest=sha256:0320ca6653b2ebfbeb142009c4b335fd98270f50192f9e070ffeb4e6d6d5572c

Observation db544578-55c4-46ad-ba5e-97fc664fda38 · outbound

This paper cites Spike-driven 10 transformer v2: Meta spiking neural network architecture in- spiring the design of next-generation neuromorphic chips.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Spike-driven 10 transformer v2: Meta spiking neural network architecture in- spiring the design of next-generation neuromorphic chips

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.103363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.038024Z digest=sha256:6b70bebec1b8d42ba16a2cd4d617fffb34d8f9c545dac128384d71a072aefdf9

Observation 53012280-1e20-466d-93de-b0fd7162101e · outbound

This paper cites Scaling spike-driven transformer with efficient spike firing approximation training.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Scaling spike-driven transformer with efficient spike firing approximation training.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.096551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.039954Z digest=sha256:ba8e4178cff30e1fff147619ec9910231bc9278e0d7af09a5e98dbff18f97f0a

Observation 3496b15e-7c1b-4a38-b47e-5d836e9cf655 · outbound

This paper cites Enhancing repre- sentation of spiking neural networks via similarity-sensitive contrastive learning.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Enhancing repre- sentation of spiking neural networks via similarity-sensitive contrastive learning

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.089484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.041890Z digest=sha256:797bd21d4c51d0e4871bd49c9823a9e6f926406e70c19839fcb6d833bafac4fe

Observation c3acc8b8-1228-4abb-8a80-0a16f8b9ed7d · outbound

This paper cites Going deeper with directly-trained larger spiking neural net- works.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Going deeper with directly-trained larger spiking neural net- works

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:54.083026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.043766Z digest=sha256:d0368f1f5ef74073edf6e0fc078d6fd7e8a30737bbb2b2ab5b58a9a95991e3ca

Observation 6de9408d-e7d4-47cd-93ff-a364343b2117 · outbound

This paper cites an unresolved cited work.

Integer Binary-Range Alignment Neuron for Spiking Neural Networks Unresolved cited work

Reference 2021

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:21:54.126907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T10:21:54.029537Z digest=sha256:dc02ab6edae16a86dd7d2333404d7e5f0c8dce99b6716d8921b6eb1ea7f8ed42

Pith citing papers

No inbound Pith citation observations are available.