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Paper Citation Record · LEDGER

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network

As of 13 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2412.16219.

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

pith.paper-citation-record.v1
2412.16219 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:00:10.676929Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d35d84a4-ba2f-4090-8f88-0458876f5b89 · outbound

This paper cites an unresolved cited work.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:00:10.818174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T13:00:10.664945Z digest=sha256:3692ba3d9f5c8eddba186b982d6bbecd203246fcc524a5b0800ef4e602721759

Observation f3c04ba3-2ee2-4134-b25f-f74fc1105ca7 · outbound

This paper cites Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T13:00:10.640149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:00:10.640149Z digest=sha256:2be570a42e7322a88b3159fc4764ac4aeebdeafe2e6aeb7316fd78faf4a31287

Observation f0103bd0-f57b-46ed-bef3-5c221cf2af8b · outbound

This paper cites In 2021 58th ACM/IEEE Design Automation Conference (DAC), 793–798.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network In 2021 58th ACM/IEEE Design Automation Conference (DAC), 793–798

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:00:10.830441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T13:00:10.652961Z digest=sha256:01c8c6f7607aa3f18dbf9607e3c5a9781ada529865d53c51df2ac2dc168e8a9b

Observation 486f2c81-cc6d-4167-8bfc-dbc0efb619c2 · outbound

This paper cites Neuromorphic Data Augmentation for Training Spiking Neural Networks.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network Neuromorphic Data Augmentation for Training Spiking Neural Networks

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T13:00:10.732116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T13:00:10.656696Z digest=sha256:c948c0b68699844c527b39ca8a976150b57798a54fbd9dde3aa6124cc7a1dc1a

Observation 2853fb32-fd14-4866-a7a8-44200cfe31cb · outbound

This paper cites Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T13:00:10.660754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:00:10.660754Z digest=sha256:02e873bcc589e2d5a63b0183f3bceeb921ec184ef9df2393a66bf205be33581c

Observation 6a645fe2-3e83-4821-9d62-98ac4994973c · outbound

This paper cites Spikformer: When Spiking Neural Network Meets Transformer.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network Spikformer: When Spiking Neural Network Meets Transformer

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T13:00:10.676929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:00:10.676929Z digest=sha256:2dc6b65b4ca399a5a255b9b36c974f5978c083ca91df788ed3bc2d51daeb180c

Observation 0c53f6eb-fdc8-45a9-8dfd-16df97bdfd87 · outbound

This paper cites In 2009 IEEE Conference on Computer Vision and Pattern Recognition, 248–255.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network In 2009 IEEE Conference on Computer Vision and Pattern Recognition, 248–255

Reference 2009

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:00:10.842911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T13:00:10.626722Z digest=sha256:46a02a147177d80086e5d995f231f2b20f6bacf7eecafd9290e82e4df6134684

Observation 994972d3-6776-4c74-a7c0-077a3d0146b5 · outbound

This paper cites In 2016 23rd international conference on pattern recognition (ICPR), 2464–2469.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network In 2016 23rd international conference on pattern recognition (ICPR), 2464–2469

Reference 2016

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:00:10.794232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T13:00:10.672923Z digest=sha256:db16119546e4ad2a36c6969b1d951e74f9fb690d31b13e833cc463699d323ad5

Observation 678dc369-f4be-4906-b361-63b40cef750a · outbound

This paper cites In Proceedings of the 56th Annual Design Automation Conference 2019, 1–6.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network In Proceedings of the 56th Annual Design Automation Conference 2019, 1–6

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:00:10.806117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T13:00:10.668822Z digest=sha256:150ff6eaaa26850c10d28d9012a5b02e06875e1e07bd8b25d2987b431d653ce9

Observation 59476cf0-4ffa-4352-af21-8c184fdd9eeb · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-11T13:00:10.644664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:00:10.644664Z digest=sha256:9f33a74307c785a6902bb4833ec922591c83ad43de9e4eccfeb155cd86f55f1e

Observation 5a04d83f-43fb-40ae-b22e-76e0376dc849 · outbound

This paper cites Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-11T13:00:10.631286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:00:10.631286Z digest=sha256:84ee6892c13427e733323bd192316c8c30be2bbe90c48446d17a57b35c666cbf

Observation 429e8f9b-bbc6-4ac2-a343-df3008208bf5 · outbound

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

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T13:00:10.635742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:00:10.635742Z digest=sha256:1206f6494b16b66ba0c714a2a764704c10c96d8f6753cda87214d611d82f6a1c

Observation a74347d3-3ae8-4167-83f5-5daf32f47e20 · outbound

This paper cites Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model.

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T13:00:10.648722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:00:10.648722Z digest=sha256:e68107a97b6f4911f991788453832d4a7f6390d1dabc5c5e5189e0d1f1edbb57

Pith citing papers

No inbound Pith citation observations are available.