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Paper Citation Record · LEDGER

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks

As of 21 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2506.07720.

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

pith.paper-citation-record.v1
2506.07720 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:34:51.598958Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

24 of 24 outbound references displayed

  • verified exact5
  • verified fuzzy6
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 48e89eab-d4f6-465a-9364-f75bd4c8e961 · outbound

This paper cites Deep residual learning in spiking neural net- works.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Deep residual learning in spiking neural net- works

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-07T05:34:51.975239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 58106141-a74b-4fb6-812c-6a3a70c764ab · outbound

This paper cites URL https://doi.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks URL https://doi

Reference 7

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verified exact
doi, observed 2026-08-07T05:34:51.639158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation b783c2ab-d029-4776-a1d7-e1f58031851c · outbound

This paper cites Distilling the Knowledge in a Neural Network.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Distilling the Knowledge in a Neural Network

Reference 9

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Observation c324c524-c0c2-46cf-b98c-528f1575b524 · outbound

This paper cites Deep dive into gradients: Better optimization for 3d object detection with gradient- corrected iou supervision.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Deep dive into gradients: Better optimization for 3d object detection with gradient- corrected iou supervision

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-07T05:34:51.952033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7140832f-5975-4d28-a2f2-db57c2a45d5d · outbound

This paper cites an unresolved cited work.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Unresolved cited work

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 541ae0d9-2429-4a47-8252-9f914d9d4930 · outbound

This paper cites T2fsnn: Deep spiking neural networks with time-to-first-spike coding.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks T2fsnn: Deep spiking neural networks with time-to-first-spike coding

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 771c51d2-bab8-4aae-8bf1-787ac4b3cc7d · outbound

This paper cites Model compression via distillation and quantization.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Model compression via distillation and quantization

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation caaea0e3-dc82-4c6e-b058-b40dcfa5522d · outbound

This paper cites Spiking PointNet: Spiking Neural Networks for Point Clouds.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Spiking PointNet: Spiking Neural Networks for Point Clouds

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:34:51.790483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation b18d3427-8395-40dd-a845-28745f61ce0e · outbound

This paper cites net/forum?id=lJdOlWg8td.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks net/forum?id=lJdOlWg8td

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:34:51.581045Z digest=sha256:527ae526ce1782948592dcd24d2e9b7701ada88b0d7494315e6e6d635fc76f8e

Observation 664eef6b-8c6f-43b0-b902-8abcef9cf72c · outbound

This paper cites Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation

Reference 20

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local_arxiv, observed 2026-08-07T05:34:51.777193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation c1a19652-b635-485c-ad77-dc0e11b4c304 · outbound

This paper cites Training Spiking Neural Networks with Local Tandem Learning.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Training Spiking Neural Networks with Local Tandem Learning

Reference 21

Resolution
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local_arxiv, observed 2026-08-07T05:34:51.762911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 36bc2d67-5f0e-4085-aa2f-b32328c9c99c · outbound

This paper cites GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:34:51.749775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 63dd0b75-e172-488d-ae5d-b0cab6cc4ec4 · outbound

This paper cites Temporal Separation with Entropy Regularization for Knowledge Distillation in Spiking Neural Networks.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Temporal Separation with Entropy Regularization for Knowledge Distillation in Spiking Neural Networks

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:34:51.734193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:34:51.595208Z digest=sha256:30172e30186622c04d73439b7527ac4ae7c8214d40d82530503e065b7a376f09

Observation 912e1c17-00e7-4320-8d45-48d317399e3d · outbound

This paper cites Zhang, W.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Zhang, W

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0dc8dca5-e6e7-4d98-9246-a3e82b065654 · outbound

This paper cites doi: https://doi.org/10.1016/S0893-6080(97)00011-7.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks doi: https://doi.org/10.1016/S0893-6080(97)00011-7

Reference 1997

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no resolver link, observed 2026-08-07T05:34:51.550448Z

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Observation 5bdb933d-0a5e-4584-8126-e1b938293477 · outbound

This paper cites Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting

Reference 2009

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Unavailable: canonical work link unavailable.

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Observation ca45fcae-a075-4005-af26-604917759170 · outbound

This paper cites Simple online and realtime tracking.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Simple online and realtime tracking

Reference 2015

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:34:51.992882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 6bf481e1-1d63-4d2a-8f2e-7cf03af98a7d · outbound

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

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks A free lunch from ann: Towards efficient, accurate spiking neu- ral networks calibration

Reference 2017

Resolution
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raw_fallback, observed 2026-08-07T05:34:51.963747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:34:51.547191Z digest=sha256:b0b0a76823aad6ffee42e0236949a574404152e4699cb25a85fb20d5f4cdc2dd

Observation 1062327c-6733-4675-8617-f01ad5ac2ae5 · outbound

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

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Imagenet: A large-scale hierarchical image database

Reference 2018

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 67b64e3e-a6fd-4f8b-8ff0-596fd2db3edb · outbound

This paper cites Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks

Reference 2019

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 15447c8c-4558-4b66-b6ef-07921dfa6e63 · outbound

This paper cites Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation

Reference 2020

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Observation d7e1a140-6a9f-4440-97ce-5012d225ef96 · outbound

This paper cites an unresolved cited work.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks Unresolved cited work

Reference 2022

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source=pdf_text observed=2026-08-07T05:34:51.516414Z digest=sha256:0126db684e36903663d7988f80fff807bbeacf4388ebea17b72b4fb8c95a8ea5

Observation 4bb994a7-22eb-4316-972d-0446cc472d2c · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2023

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:34:51.527900Z digest=sha256:11d62feca2c438dc8f1681a7c3b2c3488290e21e90c624e44ed40d1538b5f3dc

Observation f21b8709-0dfc-4738-b2c1-04b0c9777414 · outbound

This paper cites DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks.

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks

Reference 2024

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Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.