Paper Citation Record · LEDGER

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study

As of 9 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2607.14041.

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

pith.paper-citation-record.v1
2607.14041 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T02:58:32.204668Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation b91ea6db-ae7a-4993-a776-c185bbfcf33a · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.043622Z

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Unavailable: canonical work link unavailable.

Observation ffa4438c-dfea-4f00-9c36-a6fb281628ea · outbound

This paper cites HHD-Ethiopic: A histor- ical handwritten dataset for Ethiopic OCR with baseline models and human-level perfor- mance.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study HHD-Ethiopic: A histor- ical handwritten dataset for Ethiopic OCR with baseline models and human-level perfor- mance

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.135340Z

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Observation eea3e77c-d047-4703-8849-483d2945bf07 · outbound

This paper cites Nougat: Neural Optical Understanding for Academic Documents.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Nougat: Neural Optical Understanding for Academic Documents

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.193500Z

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Observation 4382cd42-aafc-46c4-ae55-8107e1d1e252 · outbound

This paper cites Automated sign detection across the Electronic Babylonian Library: A large-scale dataset and end-to-end cuneiform OCR pipeline.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Automated sign detection across the Electronic Babylonian Library: A large-scale dataset and end-to-end cuneiform OCR pipeline

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.267831Z

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Observation c21006ec-3be9-4898-a2a2-2885d603d010 · outbound

This paper cites Finetuning Vision-Language Models as OCR Systems for Low-Resource Languages: A Case Study of Manchu.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Finetuning Vision-Language Models as OCR Systems for Low-Resource Languages: A Case Study of Manchu

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.387437Z

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Observation ed18a5cd-c818-406a-83b2-793d08fd2e1f · outbound

This paper cites an unresolved cited work.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.485947Z

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Observation 0d985be7-7fd6-47e0-b604-3b1ff4feb80a · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.609222Z

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Observation dde65477-af38-49a1-b2d7-54d813f50c73 · outbound

This paper cites Old Uyghur OCR: The first work-in-progress via reproducing fine-tuning of VLMs.Journal of Old Turkic Studies, 9(2):313–318, 2025.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Old Uyghur OCR: The first work-in-progress via reproducing fine-tuning of VLMs.Journal of Old Turkic Studies, 9(2):313–318, 2025

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.668801Z

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Observation 3d7da0de-eecb-4d09-99d3-c42a37f192d4 · outbound

This paper cites an unresolved cited work.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.739060Z

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Observation a6d62440-3a65-417c-b158-4c32c8f0e517 · outbound

This paper cites Switch transformers: Scaling to tril- lion parameter models with simple and effi- cient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Switch transformers: Scaling to tril- lion parameter models with simple and effi- cient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.853576Z

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Observation eef93a3d-78a7-4b8c-b64c-6718dda4478c · outbound

This paper cites Deep residual learning for im- age recognition.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Deep residual learning for im- age recognition

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:29.946714Z

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Observation 19c8f140-baf6-4e1c-818c-8479ec563668 · outbound

This paper cites Hopcroft, and Kilian Q.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Hopcroft, and Kilian Q

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.066463Z

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Observation 3b13b4c8-d1a5-43b3-9c7e-dcb98bbd2e51 · outbound

This paper cites Averaging weights leads to wider optima and better generalization.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Averaging weights leads to wider optima and better generalization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.130556Z

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Observation 19bf1b09-4591-4437-83fa-b15a52ef2455 · outbound

This paper cites Adaptive mixtures of local experts.Neural Computa- tion, 3(1):79–87, 1991.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Adaptive mixtures of local experts.Neural Computa- tion, 3(1):79–87, 1991

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.207135Z

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Observation d0e8576b-7114-49d4-9049-29547a74d419 · outbound

This paper cites Mixtral of Experts.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Mixtral of Experts

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.318625Z

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Observation 407ea213-d51b-4416-add7-6140700ac572 · outbound

This paper cites 9 Transkribus—a service platform for tran- scription, recognition and retrieval of historical documents.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study 9 Transkribus—a service platform for tran- scription, recognition and retrieval of historical documents

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.363781Z

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Observation f16b3e8c-c797-4eea-9b51-f0470b427958 · outbound

This paper cites GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.439368Z

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Observation cb9e17a5-d916-4cca-81dc-41fc9a3c02f9 · outbound

This paper cites AMADI LontarSet: The first handwritten Balinese palm leaf manuscripts dataset.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study AMADI LontarSet: The first handwritten Balinese palm leaf manuscripts dataset

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.489934Z

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Observation a4f2ba7b-fbe2-4d90-949b-36a4f1136356 · outbound

This paper cites Kraken—an universal text recognizer for the humanities.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Kraken—an universal text recognizer for the humanities

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.571053Z

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Observation 652d75ab-421c-4ff5-ab80-15d5185a33ad · outbound

This paper cites Ocr-free document understanding transformer.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Ocr-free document understanding transformer

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.623615Z

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Observation b121066a-ec91-4e85-8310-f27a841fd4c6 · outbound

This paper cites Pix2Struct: Screenshot parsing as pretraining for visual language understand- ing.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Pix2Struct: Screenshot parsing as pretraining for visual language understand- ing

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.726093Z

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Observation b25b095e-c6be-4a5f-9232-6edafe483109 · outbound

This paper cites TrOCR: Transformer-based optical character recogni- tion with pre-trained models.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study TrOCR: Transformer-based optical character recogni- tion with pre-trained models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.844158Z

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Observation 4c0a7a59-a6a6-4c23-9c44-dba5c6d51ab2 · outbound

This paper cites Om- niOCR: Generalist OCR for ethnic minority languages.arXiv preprint arXiv:2602.21042, 2026.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Om- niOCR: Generalist OCR for ethnic minority languages.arXiv preprint arXiv:2602.21042, 2026

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.873545Z

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Observation 924ae60c-e57a-4115-b291-cebe5017fd65 · outbound

This paper cites Visual instruction tun- ing.Advances in neural information process- ing systems, 36, 2024.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Visual instruction tun- ing.Advances in neural information process- ing systems, 36, 2024

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.914654Z

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Observation ad987fdd-86ef-40e7-a4a4-e14abcc0413e · outbound

This paper cites KOSMOS-2.5: A Multimodal Literate Model.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study KOSMOS-2.5: A Multimodal Literate Model

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:30.989588Z

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Observation e8ed565a-ac8d-4fef-ae45-bc262b4c5ad3 · outbound

This paper cites Ancient but Digitized: Developing Handwritten Optical Character Recognition for East Syriac Script Through Creating KHAMIS Dataset.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Ancient but Digitized: Developing Handwritten Optical Character Recognition for East Syriac Script Through Creating KHAMIS Dataset

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.064339Z

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Observation 7c539c87-3b19-419c-8043-6e431b7c6f2f · outbound

This paper cites A survey of historical document image datasets.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study A survey of historical document image datasets

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.171390Z

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Observation f77764ba-804d-4ee3-91e6-d44084be4ebc · outbound

This paper cites OpenITI MAKHZAN: An open annotated dataset of Arabic, Persian, Ottoman Turkish, and Urdu print and manuscript data.Zenodo, 2025.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study OpenITI MAKHZAN: An open annotated dataset of Arabic, Persian, Ottoman Turkish, and Urdu print and manuscript data.Zenodo, 2025

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.237347Z

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Observation aeaee9ed-1c0a-4066-ac2f-d04449974f50 · outbound

This paper cites Dhali, and Lam- bert Schomaker.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Dhali, and Lam- bert Schomaker

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.345313Z

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Observation 2cd4dfee-bfc7-4169-b88b-99318d375f18 · outbound

This paper cites Indiscapes: Instance segmentation net- works for layout parsing of historical Indic manuscripts.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Indiscapes: Instance segmentation net- works for layout parsing of historical Indic manuscripts

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.443613Z

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Observation 7cdd34e3-771e-42c8-a554-e2b0d6de2cdf · outbound

This paper cites A text recognition dataset from Sahidic Coptic ancient manuscripts.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study A text recognition dataset from Sahidic Coptic ancient manuscripts

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.499980Z

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Observation cc74b4f5-defd-4da9-a420-a3ff08c9f65d · outbound

This paper cites Advancing Offline Handwritten Text Recognition: A Systematic Review of Data Augmentation and Generation Techniques.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Advancing Offline Handwritten Text Recognition: A Systematic Review of Data Augmentation and Generation Techniques

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.545533Z

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Observation 2393dcfa-eec1-4cd1-ac89-ec390d7c0c82 · outbound

This paper cites Scaling vision with sparse mixture of experts.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Scaling vision with sparse mixture of experts

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.595265Z

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Observation 6eea48be-c9f6-4b1f-a18a-832922354cb8 · outbound

This paper cites Outrageously large neural networks: The sparsely-gated mixture- of-experts layer.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Outrageously large neural networks: The sparsely-gated mixture- of-experts layer

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.647332Z

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Observation 1598e88e-54da-4909-a7cd-e0247b25cd0b · outbound

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Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Unresolved cited work

Reference 35

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Observation b88d0a8b-301b-4cd4-923b-b5d113babfec · outbound

This paper cites An overview of the Tesseract OCR engine.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study An overview of the Tesseract OCR engine

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.753759Z

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Observation 64a39722-cc4b-4eac-884a-087fa13edefb · outbound

This paper cites Few shots are all you need: A progressive learn- ing approach for low resource handwritten text recognition.Pattern Recognition Letters, 160:43–49, 2022.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Few shots are all you need: A progressive learn- ing approach for low resource handwritten text recognition.Pattern Recognition Letters, 160:43–49, 2022

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.804055Z

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Observation 65d83001-1141-4287-bed1-d6ccec5a510b · outbound

This paper cites ManchuOCR: An OCR system for the Manchu script.https://github.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study ManchuOCR: An OCR system for the Manchu script.https://github

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.891038Z

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Observation 8e098712-e3cc-4968-8954-ac5b03472fb9 · outbound

This paper cites QARI-OCR: High-Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study QARI-OCR: High-Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:31.981494Z

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Observation cea1a149-72a3-40d7-8737-1d6faa99ee2c · outbound

This paper cites General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:32.052229Z

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Observation 9fb0af92-964d-457f-b093-b580861a8118 · outbound

This paper cites Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, and Ludwig Schmidt.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, and Ludwig Schmidt

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:32.132445Z

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Observation 6bc36594-d4d0-4ee6-b2f9-e1f7de5b43a4 · outbound

This paper cites OCR with the deep CNN model for ligature script-based lan- guages like Manchu.Scientific Programming, 2021:5520338, 2021.

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study OCR with the deep CNN model for ligature script-based lan- guages like Manchu.Scientific Programming, 2021:5520338, 2021

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T02:58:32.204668Z

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Pith citing papers

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