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Paper Citation Record · LEDGER

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions

As of 17 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2504.13524.

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

pith.paper-citation-record.v1
2504.13524 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:10:33.746821Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

59 of 59 outbound references displayed

  • verified exact0
  • verified fuzzy44
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e0e59206-af19-4b4a-ad9b-0561d51d0fa0 · outbound

This paper cites Obc306:Alarge-scaleoraclebonecharacterrecognition dataset.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Obc306:Alarge-scaleoraclebonecharacterrecognition dataset

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 2751afaa-bf50-46df-9905-b4ad6aac01e6 · outbound

This paper cites Comparison of different image denoising algorithms for chinese calligraphy images.Neurocomputing, 188:102–112, 2016.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Comparison of different image denoising algorithms for chinese calligraphy images.Neurocomputing, 188:102–112, 2016

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c0ace882-31c9-4d66-a4e5-36077d9d725c · outbound

This paper cites Restora- tion method of characters on jiagu rubbings based on poisson distri- bution and fractal geometry.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Restora- tion method of characters on jiagu rubbings based on poisson distri- bution and fractal geometry

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 62273c0e-49d1-4c78-a36f-b54e001dfaf1 · outbound

This paper cites Restoration of degraded historical document image: Anadaptive multilayer-informationbinarization technique.J.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Restoration of degraded historical document image: Anadaptive multilayer-informationbinarization technique.J

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 168663c9-7b97-48fe-8d51-e6299c5ddf66 · outbound

This paper cites Robust kronecker-decomposablecomponentanalysisforlow-rankmodeling.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Robust kronecker-decomposablecomponentanalysisforlow-rankmodeling

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 4cef4f56-5cca-43f3-9c42-94b31cabcbca · outbound

This paper cites Robust kroneckercomponentanalysis.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Robust kroneckercomponentanalysis

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 864964d7-aa12-4a7d-bfc2-ed8f5d8c82ef · outbound

This paper cites Kroneckercomponentwithrobustlow-rank dictionary for image denoising.Displays, 74:102194, 2022.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Kroneckercomponentwithrobustlow-rank dictionary for image denoising.Displays, 74:102194, 2022

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 2ce92237-8edd-440f-8e5e-5bfd70fc0f7b · outbound

This paper cites Robust low-rank analysis with adaptive weighted tensor for image denoising.Displays, 73:102200, 2022.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Robust low-rank analysis with adaptive weighted tensor for image denoising.Displays, 73:102200, 2022

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.528102Z digest=sha256:b5c33396b64f5eca7d1dfd779bf8d6b3fe2158d1b8036ca6408cc3d386dbf692

Observation e7d99f1f-1ad9-4e21-9b1d-0311c855150a · outbound

This paper cites Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:10:33.532622Z digest=sha256:28d036c7d27b05d9941a8e75c3da34964b6594551513d25c2e606551c9af7ce4

Observation 57e7945a-8589-48b7-9766-74c65403364f · outbound

This paper cites Restormer: Efficient transformer for high-resolution image restoration.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Restormer: Efficient transformer for high-resolution image restoration

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.536575Z digest=sha256:d578ae35b5b726df35779b636743f0043c03e24e5e08a9f947de28adb7a75c7f

Observation e7de51be-b656-4c03-a12d-e3e92a1d241d · outbound

This paper cites Rcrn: Real-world character image restoration network via skeleton extraction.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Rcrn: Real-world character image restoration network via skeleton extraction

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 653ad3c1-e91a-48b5-bbc7-777b69f78f9b · outbound

This paper cites Charformer: A glyph fusion based attentive framework for high-precision character image denoising.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Charformer: A glyph fusion based attentive framework for high-precision character image denoising

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation f0ce02fa-18a3-47d7-968b-7a22d741da84 · outbound

This paper cites Self-supervised learning of orc-bert augmentator for recog- nizing few-shot oracle characters.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Self-supervised learning of orc-bert augmentator for recog- nizing few-shot oracle characters

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.548925Z digest=sha256:caa6bbe1c8fa07ec6888b5398dd72ec6bbbbc7ed82faec30ee6cc74ec217fbb0

Observation 02a89305-8098-4f96-a191-2f9c351764f7 · outbound

This paper cites Unsupervised structure-texture separation network for oracle character recognition.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Unsupervised structure-texture separation network for oracle character recognition

Reference 14

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raw_fallback, observed 2026-08-16T12:10:34.324178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 42fca2ab-b1e7-4fea-93a8-3f43243205ff · outbound

This paper cites Obi- bench:Canlmmsaidinstudyofancientscriptonoraclebones?,2025.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Obi- bench:Canlmmsaidinstudyofancientscriptonoraclebones?,2025

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation f0a5df26-8147-464d-a67d-4caeb3a1b133 · outbound

This paper cites Hwobc-ahandwritingoraclebonecharacterrecognition database.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Hwobc-ahandwritingoraclebonecharacterrecognition database

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 1c13ca44-08c1-47da-b750-4a8e5c3d9776 · outbound

This paper cites Study on the evolution of chinese characters based on few-shot learning: From oracle bone inscriptions to regular script.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Study on the evolution of chinese characters based on few-shot learning: From oracle bone inscriptions to regular script

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 0c8038ef-40d9-4471-83db-14d1a0c4c0d9 · outbound

This paper cites Dy- namic dataset augmentation for deep learning-based oracle bone inscriptions recognition.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Dy- namic dataset augmentation for deep learning-based oracle bone inscriptions recognition

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.573383Z digest=sha256:b0dbfb74b8c55cd75c3a495dd11c645cbd919f1804c7715a951abe363330180d

Observation 683f73f8-1511-4fef-916b-84f91120adb4 · outbound

This paper cites An open dataset for the evolution of oracle bone characters: EVOBC.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions An open dataset for the evolution of oracle bone characters: EVOBC

Reference 19

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no resolver link, observed 2026-08-16T12:10:33.577888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:10:33.577888Z digest=sha256:e652661cbfddf0e5cf0d851f0717c1729b757eaf2c525065abbd6f903b760154

Observation d21c4852-0056-4072-b00d-b7acf821d054 · outbound

This paper cites Building hierarchical representations for oracle character and sketch recognition.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Building hierarchical representations for oracle character and sketch recognition

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation daf3a12e-31e6-458b-951b-377270fbbcce · outbound

This paper cites Accurateoracleclassificationbasedondeepconvolu- tionalneuralnetwork.In 2018IEEE18thInternationalConferenceon Communication Technology (ICCT), pages 1188–1191.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Accurateoracleclassificationbasedondeepconvolu- tionalneuralnetwork.In 2018IEEE18thInternationalConferenceon Communication Technology (ICCT), pages 1188–1191

Reference 21

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.585994Z digest=sha256:a255775f39c0efd75aa1a6713aef8d5f393af0a5a6c52fb128f9a903089775bc

Observation b2b06f1d-7aa2-4be0-ad26-9c379fac6631 · outbound

This paper cites Deep self-supervised learning for oracle bone inscriptions features representation.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Deep self-supervised learning for oracle bone inscriptions features representation

Reference 22

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raw_fallback, observed 2026-08-16T12:10:34.237726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.589680Z digest=sha256:2e1f09f4d99d6201c976b390367167377b5abb1b0354f4e695c5c03987fc17e3

Observation 6c14b8ab-fca2-4ef7-8069-89a9970e7216 · outbound

This paper cites Large-scale oracle bone inscriptions dataset construc- tionandalgorithmresearch.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Large-scale oracle bone inscriptions dataset construc- tionandalgorithmresearch

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:34.224410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.594377Z digest=sha256:344fe47b4dee95049ba6659ac49e71f8df4699e77d53c8da2e66b0743b92d9a5

Observation 78935b64-f810-48fc-9db9-8e64afe530c4 · outbound

This paper cites Oracle bone inscriptions recognition based on deep convolutional neural network.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Oracle bone inscriptions recognition based on deep convolutional neural network

Reference 24

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raw_fallback, observed 2026-08-16T12:10:34.208274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.598622Z digest=sha256:5432fdc18b8a09f1a5a33d5a365fe8a657e158d662b0060b991c9ed9043d8c38

Observation 2ebb71c4-54b3-4381-a1e1-f627ec689423 · outbound

This paper cites Ai-powered oracle bone inscriptions recognition and fragments rejoining.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Ai-powered oracle bone inscriptions recognition and fragments rejoining

Reference 25

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raw_fallback, observed 2026-08-16T12:10:34.194170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 0bd35278-10b1-457f-ade7-df2b81ca5c4f · outbound

This paper cites Recognition of oracle bone inscriptions by using two deep learning models.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Recognition of oracle bone inscriptions by using two deep learning models

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:10:34.180148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.607959Z digest=sha256:c30e9db0871dec9d0d90caa06cffcfd980a35d3fcad9218e9ba8d97358482565

Observation 1a74f79c-669c-4753-8f56-d860fff4cabf · outbound

This paper cites Data-driven oracle bone rejoining: A dataset and practical self-supervised learning scheme.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Data-driven oracle bone rejoining: A dataset and practical self-supervised learning scheme

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:10:34.167582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.612044Z digest=sha256:ea3e4e011c52e1a7f91a4d44e448050df7ce75b3252e0dbc822cbafb3b0a3c02

Observation 2bf9da9c-1424-4508-95e8-f31a2ce8ef99 · outbound

This paper cites A dataset of oracle characters for benchmarking machine learning algorithms.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions A dataset of oracle characters for benchmarking machine learning algorithms

Reference 28

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raw_fallback, observed 2026-08-16T12:10:34.154073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.616123Z digest=sha256:5e3ee9a3996e7dae4d1e06d3f4e6e6b625171cbaa800a733c3734217407a8de2

Observation c3ae7128-d405-4713-9d9b-ab698177891c · outbound

This paper cites An open dataset for oracle bone script recognition and decipherment.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions An open dataset for oracle bone script recognition and decipherment

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:33.620760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:10:33.620760Z digest=sha256:3fbcbaf18afbdaee420675f16e9fedec28ee1b4e52cefd46a9ef244385a8d5bb

Observation 8a1571f7-2463-44a8-a074-611385366f0b · outbound

This paper cites Mitigating long-tail distribution in oracle bone inscriptions: Dataset, model, and benchmark, 2025.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Mitigating long-tail distribution in oracle bone inscriptions: Dataset, model, and benchmark, 2025

Reference 30

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raw_fallback, observed 2026-08-16T12:10:34.141276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.625291Z digest=sha256:af47f8aa672648da0da7925ae628d6078a07b4705599c4013bf020f8b40a2329

Observation 6f7fefe6-7747-4626-ba29-117bf458d506 · outbound

This paper cites Oracle bone inscriptions in the collection of shanghai museum (volume i), 2009.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Oracle bone inscriptions in the collection of shanghai museum (volume i), 2009

Reference 31

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raw_fallback, observed 2026-08-16T12:10:34.128609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.629155Z digest=sha256:bd1eaf6561569d9620dc685db9a3e3a77055b24acad537f54840617f91657a95

Observation b715ccbc-faa9-4566-940a-d484cd134256 · outbound

This paper cites Gradient-based learning applied to document recognition.Proceed- ings of the IEEE, 86(11):2278–2324, 1998.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Gradient-based learning applied to document recognition.Proceed- ings of the IEEE, 86(11):2278–2324, 1998

Reference 32

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no resolver link, observed 2026-08-16T12:10:33.633328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:10:33.633328Z digest=sha256:e310300b67277cd34bfabbfbc021ea2a5a6ad37301aef15f6b269cb800c816f1

Observation d18b9195-6ed5-463a-b099-2fa578073676 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.Advances in neural information processing systems, 25, 2012.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Imagenet classification with deep convolutional neural networks.Advances in neural information processing systems, 25, 2012

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:10:33.637756Z digest=sha256:a710f1afbb7ed52f1a47b5ae667fa8c2066c2429b1b6187057f4467b008ee92d

Observation 63f96b8f-edd7-4a53-b8e4-5382b3f92870 · outbound

This paper cites Inception-v4, inception-resnet and the impact of residual connections on learning.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Inception-v4, inception-resnet and the impact of residual connections on learning

Reference 34

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source=pdf_text observed=2026-08-16T12:10:33.641562Z digest=sha256:4679f610cf9495b1ca248ba153e24327841f59aa2742acae65c8dc04002d8dc7

Observation bf3cb19e-247a-4f7f-9563-dbfb7df9afa1 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 35

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source=pdf_text observed=2026-08-16T12:10:33.646243Z digest=sha256:d3e0826a2720d324bbb7de9a7e24247791fcde787657c6a3d88fe1e1415bb0a5

Observation 733b1736-5ee3-48ba-ac7b-4894ac5b9d4c · outbound

This paper cites Deep residual learning for image recognition.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Deep residual learning for image recognition

Reference 36

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source=pdf_text observed=2026-08-16T12:10:33.651463Z digest=sha256:56867a3f1bb5d90a95e278ae393524635ab1e78d06dd1a928edadd9e8107c969

Observation ca818bcb-d65d-4704-ad18-a431530d449a · outbound

This paper cites Oracle character recognition by nearest neighbor classifica- tion with deep metric learning.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Oracle character recognition by nearest neighbor classifica- tion with deep metric learning

Reference 37

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raw_fallback, observed 2026-08-16T12:10:34.087245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.655789Z digest=sha256:9938c9b78ae445eeac73e4838f532249e6d95b29349b62ecb8fee20889a662ad

Observation 5eaa6a47-1873-4c26-bcc5-b52b21a9aaac · outbound

This paper cites Oraclecharacterrecognition using unsupervised discriminative consistency network.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Oraclecharacterrecognition using unsupervised discriminative consistency network

Reference 38

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raw_fallback, observed 2026-08-16T12:10:34.073314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.659614Z digest=sha256:5ed74695eb561f48145d3a863879e62f93f1e11a7f61f319afb18e171a49fbac

Observation 446b27b6-dc2d-4612-b751-a3571f388672 · outbound

This paper cites Statistical techniques for digital pre-processing of computed tomography medi- cal images: A current review.Displays, 85:102835, 2024.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Statistical techniques for digital pre-processing of computed tomography medi- cal images: A current review.Displays, 85:102835, 2024

Reference 39

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raw_fallback, observed 2026-08-16T12:10:34.060941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.664532Z digest=sha256:b277339c3c8c7eed21a2592622b945750eccb9ab00615edf1e7bb90ddb2015e8

Observation b1915253-2a7c-43d4-b84f-c9a2956824ba · outbound

This paper cites Lesion-inspired denoising network: Connecting medical image denoising and lesion detection.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Lesion-inspired denoising network: Connecting medical image denoising and lesion detection

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:34.049072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.668518Z digest=sha256:932a3575320ede3aca78da8e14c957eaba4657d030d55c93a0501d826de7471e

Observation 08ee20a3-4bbd-4056-9945-43ae24c3eade · outbound

This paper cites Indeandcoe:Aframeworkbasedonmulti-scalefeaturefusion and residual learning for interferometric sar remote sensing image denoising and coherence estimation.Displays, 79:102496, 2023.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Indeandcoe:Aframeworkbasedonmulti-scalefeaturefusion and residual learning for interferometric sar remote sensing image denoising and coherence estimation.Displays, 79:102496, 2023

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:34.035207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.672902Z digest=sha256:566f23d0c026432683f3e57a9c88fddb1599028320cfe99f7d5926bf41919a9d

Observation a4011a56-82ff-445b-9629-fd1b25fb6e5e · outbound

This paper cites Selectiveresidualm-netforrealimagedenoising.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Selectiveresidualm-netforrealimagedenoising

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:34.021971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.677172Z digest=sha256:acb585c49fb6f0b2ced51c24e1c85b91788ae1bbc1ad562699a8cd2ff937b36c

Observation 4c0c0267-c53f-4608-b6dd-8a230971d126 · outbound

This paper cites U-net: Con- volutional networks for biomedical image segmentation.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions U-net: Con- volutional networks for biomedical image segmentation

Reference 43

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:10:33.680995Z digest=sha256:846be4c379fcd7045a81de5ffc8f217343223f1d00fbbc47ca5b62ddc02291f0

Observation 254937ad-3067-4600-a8b1-a42a7e84763f · outbound

This paper cites KBNet: Kernel Basis Network for Image Restoration.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions KBNet: Kernel Basis Network for Image Restoration

Reference 44

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source=pdf_text observed=2026-08-16T12:10:33.684935Z digest=sha256:de6a5279f2ff8432154750fe0076d5546124a0c3f7eefcbe545d07908ca0ee10

Observation dfb17d89-65cb-4bea-9f94-efe27ff00912 · outbound

This paper cites Invertible denoising network: A light solution for real noise removal.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Invertible denoising network: A light solution for real noise removal

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:34.001455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.689468Z digest=sha256:f972eb299c49d933b8087529229e71026979a09b1da74c72b742b144b21a9ed8

Observation f5a7225a-2fa8-47e1-9815-f91e3c1bd528 · outbound

This paper cites Dual adversarial network: Toward real-world noise removal and noise generation.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Dual adversarial network: Toward real-world noise removal and noise generation

Reference 46

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:33.988328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.693924Z digest=sha256:5d8e1badaaa1440fff504becf39654a3ebcf63501ffeb89f756d3868e634122b

Observation 06e8d47c-875d-45a2-a91f-df6fe4ec8632 · outbound

This paper cites Animageisworth16x16words:Transformersfor image recognition at scale.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Animageisworth16x16words:Transformersfor image recognition at scale

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:33.975172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.697904Z digest=sha256:8548891e26b7b45e7473451ad73b5561b1346a3fd8a9422feb2c7d694fef32c3

Observation 918891aa-e1cb-443f-9f7d-1a3cabf3ebee · outbound

This paper cites Uformer: A general u-shaped transformer for image restoration.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Uformer: A general u-shaped transformer for image restoration

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:33.961818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.701991Z digest=sha256:5b2267d9cd9eb75bb4f941a3cabde01da26b8e1edb5917efd2c89c08bc45ee9e

Observation e8489153-8246-4e5e-857c-049a513973b8 · outbound

This paper cites Cascadedgaze: Efficiency in global context extraction for image restoration.Trans- actions on Machine Learning Research, 2024.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Cascadedgaze: Efficiency in global context extraction for image restoration.Trans- actions on Machine Learning Research, 2024

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:33.948611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.706117Z digest=sha256:8d27e0921b3f7f63d1ce7344d0e0d6832a7fb7db88bc2be626b6911bd1a98add

Observation ebf42736-e12a-43e6-b88e-921ca0757ea5 · outbound

This paper cites Selectivekernel networks.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Selectivekernel networks

Reference 50

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raw_fallback, observed 2026-08-16T12:10:33.931437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.709832Z digest=sha256:8389c49ca701cb7157cde30cd8e33dd25553e85f6e3db4f88a470b8d74acfd0a

Observation 489ea0d8-fc10-40ec-8d2e-53e184505e53 · outbound

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

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Imagenet: A large-scale hierarchical image database

Reference 51

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source=pdf_text observed=2026-08-16T12:10:33.713772Z digest=sha256:2180227c4af40ad18aab12f4fb1242ae6354dfd6aa688c1e762243bffd604234

Observation 64bddf79-24ff-45b7-a324-7cb762ef22e8 · outbound

This paper cites Chinesecharacters strokethinningandextractionbasedonmathematicalmorphology[j].

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Chinesecharacters strokethinningandextractionbasedonmathematicalmorphology[j]

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:33.909660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.717733Z digest=sha256:772e04d6f020058b625e532e78715b75a4487770926eaf6a383840173419e788

Observation 283a3dc8-7fa1-4bbb-b55a-46621a356221 · outbound

This paper cites Jiaguwen zixing biao (a list of oracle characters).

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Jiaguwen zixing biao (a list of oracle characters)

Reference 53

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verified fuzzy
raw_fallback, observed 2026-08-16T12:10:33.896311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.722068Z digest=sha256:cc0e8aed66caeb7cdd087f9ab20c5222a9ce22ca36ea923012c4027382175681

Observation 5c9a3f49-1240-4c69-88e9-9eb14436de03 · outbound

This paper cites Decoupled Weight Decay Regularization.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Decoupled Weight Decay Regularization

Reference 54

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:10:33.726103Z digest=sha256:122bad76179ba9e36fe7cbca3241d2226e0b8163b65a86ea2480b259da89b627

Observation 943dc2be-849c-4930-a4e4-41817da30134 · outbound

This paper cites Quality Assessment in the Era of Large Models: A Survey.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Quality Assessment in the Era of Large Models: A Survey

Reference 55

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no resolver link, observed 2026-08-16T12:10:33.730197Z

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source=pdf_text observed=2026-08-16T12:10:33.730197Z digest=sha256:58a0555eed80a50014e286de55b0b80aa82f0f314bef0904dd981e1c81a938a6

Observation d86d2b7b-ab6c-40d5-a672-1d5d8d1c8dcd · outbound

This paper cites A-Bench: Are LMMs Masters at Evaluating AI-generated Images?.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions A-Bench: Are LMMs Masters at Evaluating AI-generated Images?

Reference 56

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no resolver link, observed 2026-08-16T12:10:33.734620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:10:33.734620Z digest=sha256:17e733ee1814d8960323817a6de4b1dfdf28f2fa5c728b5e8fa8bcaf4d6b18b9

Observation 23df172d-7c4a-4f0d-96a8-597794770167 · outbound

This paper cites Q-Bench-Video: Benchmarking the Video Quality Understanding of LMMs.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Q-Bench-Video: Benchmarking the Video Quality Understanding of LMMs

Reference 57

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T12:10:33.738860Z digest=sha256:56621b7e26086119c4b1bc8d7b32e6061a0245c85b6d87c4ce21c7c4ebd666c7

Observation c787c68a-42c1-4eef-a6ea-04fc55324794 · outbound

This paper cites Study of subjective and objective naturalness assessment of ai-generated images.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Study of subjective and objective naturalness assessment of ai-generated images

Reference 58

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raw_fallback, observed 2026-08-16T12:10:33.883688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.742953Z digest=sha256:4560605a4eb6f5a4355bbd2ad23790159e56555d50b319730018bd6a848f189e

Observation 34a11c54-842b-4b84-ae76-0a5ad4e2b0d7 · outbound

This paper cites Image quality metrics: Psnr vs.

OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions Image quality metrics: Psnr vs

Reference 59

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raw_fallback, observed 2026-08-16T12:10:33.871399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T12:10:33.746821Z digest=sha256:361ae1e461c6ade33ee5c2badf4c81682d60f853b212f62a2a861c73ee229c6e

Pith citing papers

No inbound Pith citation observations are available.