Paper Citation Record · LEDGER

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding

As of 19 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2506.20305.

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

pith.paper-citation-record.v1
2506.20305 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:59:59.002407Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

33 of 33 outbound references displayed

verified exact1
verified fuzzy25
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c844cb87-0b66-4145-9fd8-43ef8b3d2371 · outbound

This paper cites Global lyapunov functions: a long-standing open problem in mathematics, with symbolic transformers.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Global lyapunov functions: a long-standing open problem in mathematics, with symbolic transformers

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.554731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 87d6c692-5bc5-40a7-9107-d0cc3e4b89ec · outbound

This paper cites Linear algebra with transformers.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Linear algebra with transformers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.537610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8d472233-3f98-4d8c-bd6d-bc22b93a7f02 · outbound

This paper cites Learning the greatest common divisor: explaining transformer predictions.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Learning the greatest common divisor: explaining transformer predictions

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.521375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ff6e2909-a658-487d-b3b4-f59b85bc1067 · outbound

This paper cites A lightweight barcode detection algorithm based on deep learning.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding A lightweight barcode detection algorithm based on deep learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.504245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cb059400-94aa-4b55-90a8-c3b3c1069c98 · outbound

This paper cites Overcoming a theoretical limitation of self-attention.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Overcoming a theoretical limitation of self-attention

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.488442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bcacdc7f-4b8b-45b1-930e-9ed69f422f5c · outbound

This paper cites Qr code detection using convolutional neural networks.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Qr code detection using convolutional neural networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.472590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1e60a0ab-791f-4611-b7d8-257f28667b82 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding An image is worth 16x16 words: Transformers for image recognition at scale

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T22:59:58.879519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0acfde5-e815-40b0-abea-cb7c1f85ef01 · outbound

This paper cites A novel framework for qr code detection and decoding from obscure images using yolo object detection and real-esrgan image enhancement technique.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding A novel framework for qr code detection and decoding from obscure images using yolo object detection and real-esrgan image enhancement technique

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.446134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e1d9c1aa-c0af-4c13-b7bd-a45626f752ed · outbound

This paper cites Why are sensitive functions hard for transformers? In Proceedings of the Annual Meeting of the Association for Computational Linguistics, pages 14973--15008, 2024.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Why are sensitive functions hard for transformers? In Proceedings of the Annual Meeting of the Association for Computational Linguistics, pages 14973--15008, 2024

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.430577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ba4e3648-2cba-4979-85e4-24798fc7547a · outbound

This paper cites Information technology — automatic identification and data capture techniques — qr code bar code symbology specification, 2024.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Information technology — automatic identification and data capture techniques — qr code bar code symbology specification, 2024

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.415529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1519328e-80d6-4996-b9fb-6ebcdaa58999 · outbound

This paper cites Learning to compute gr \" o bner bases.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Learning to compute gr \" o bner bases

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.399643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 29f431bf-f38c-4077-81c7-4f19d8ad7910 · outbound

This paper cites Computational Algebra with Attention: Transformer Oracles for Border Basis Algorithms.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Computational Algebra with Attention: Transformer Oracles for Border Basis Algorithms

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:59:59.093798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1832e25c-34fb-4eaa-b586-0535869a88cd · outbound

This paper cites Transformers provably solve parity efficiently with chain of thought.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Transformers provably solve parity efficiently with chain of thought

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.383556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9dd99a92-bf2b-4d62-b8d3-d4299371cbbd · outbound

This paper cites An improvement on qr code limit angle detection using convolution neural network.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding An improvement on qr code limit angle detection using convolution neural network

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.367795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9084b371-3858-4cad-8513-10e65d1e4d3e · outbound

This paper cites Deep learning for symbolic mathematics.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Deep learning for symbolic mathematics

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.349989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eaa583f8-4c78-4a88-b804-e35316b2e9a5 · outbound

This paper cites Binary codes capable of correcting deletions, insertions and reversals.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Binary codes capable of correcting deletions, insertions and reversals

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.333906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 415208b5-e937-4699-88c0-b545bc071784 · outbound

This paper cites BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.317794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0a90d2f1-1271-4379-949f-9e09251bff8f · outbound

This paper cites Salsa verde: a machine learning attack on learning with errors with sparse small secrets.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Salsa verde: a machine learning attack on learning with errors with sparse small secrets

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.298858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eebe2ee8-caf0-4dd7-ac1a-58d90329ced2 · outbound

This paper cites Salsapicante: A machine learning attack on lwe with binary secrets.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Salsapicante: A machine learning attack on lwe with binary secrets

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.283388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4882fde3-6fa2-4971-bfe6-a766814d68f6 · outbound

This paper cites Decoupled weight decay regularization.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Decoupled weight decay regularization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T22:59:58.940563Z

Source-reported events for the cited work

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Observation 74ba4f13-bc33-4431-9ce2-3f22f65939ee · outbound

This paper cites Qr code detection with faster-rcnn based on fpn.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Qr code detection with faster-rcnn based on fpn

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.255718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e3ff60e2-fe53-474d-9466-191f89922837 · outbound

This paper cites Tranco: A Research-Oriented Top Sites Ranking Hardened Against Manipulation.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Tranco: A Research-Oriented Top Sites Ranking Hardened Against Manipulation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T22:59:58.949499Z

Source-reported events for the cited work

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Observation 54b40457-ba3d-4e26-9909-131b691e402a · outbound

This paper cites Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T22:59:58.954543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7b95cf4-174b-4766-becf-b35a8ca4f085 · outbound

This paper cites Quick response barcode deblurring via doubly convolutional neural network.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Quick response barcode deblurring via doubly convolutional neural network

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.239564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9a510c64-8e6c-487f-b7d3-3212b8dad95a · outbound

This paper cites Robust speech recognition via large-scale weak supervision.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Robust speech recognition via large-scale weak supervision

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.222437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a8eb8acc-93e1-422a-9809-7aeff54a45c6 · outbound

This paper cites Failures of gradient-based deep learning.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Failures of gradient-based deep learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.204897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4dc9c142-d200-414c-91c6-8a17a778f5df · outbound

This paper cites Positional Description Matters for Transformers Arithmetic.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Positional Description Matters for Transformers Arithmetic

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T22:59:58.973372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6593a72-a1d6-41d6-aa0a-4764446f51fb · outbound

This paper cites Super resolution for qr code images.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Super resolution for qr code images

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.187919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fd7417aa-69bf-409b-966a-e2d5476f4861 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T22:59:58.984251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5e34a81-4620-45a0-8250-1df6fd8f617f · outbound

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Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:59:59.160970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3023445e-3351-4c68-a3f2-39fb36b43162 · outbound

This paper cites Ehfp-gan: Edge-enhanced hierarchical feature pyramid network for damaged qr code reconstruction.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Ehfp-gan: Edge-enhanced hierarchical feature pyramid network for damaged qr code reconstruction

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.144816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 27382ffd-fc0d-481b-bec2-09f77fa82539 · outbound

This paper cites Susskind, Samy Bengio, and Preetum Nakkiran.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Susskind, Samy Bengio, and Preetum Nakkiran

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.127989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6e6c9bb9-d87b-49d5-8877-1227f2dd0763 · outbound

This paper cites Detrs with collaborative hybrid assignments training.

Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding Detrs with collaborative hybrid assignments training

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:59:59.111735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.