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Paper Citation Record · LEDGER

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

As of 22 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 9 inbound Pith citation observations for arXiv:2512.21095.

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

pith.paper-citation-record.v1
2512.21095 v2

Coverage vector

measured 87 of 87 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T14:16:50.918006Z

measured 96 of 96 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:04:30.193325Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T02:46:28.861677Z

Reference resolution

87 of 87 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved87
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce2b7591-0ec7-4762-9ab1-3ac1e62a453e · outbound

This paper cites GPT-4 Technical Report.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters GPT-4 Technical Report

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:16:50.706091Z digest=sha256:1ea50c9c88ec4c39368d901a3525784f2467b1b2fc277d950dd997e242282988

Observation 812a9b27-6325-4373-86ab-d22869842762 · outbound

This paper cites Qwen2.5-VL Technical Report.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Qwen2.5-VL Technical Report

Reference 2

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source=pdf_text observed=2026-08-03T14:16:50.709280Z digest=sha256:ec978c6c8710f9adeb11e256db7495647e1e51dcf71e843fadb5208f1a5922d4

Observation ce7a7e03-367e-4b58-9491-23aa319c020f · outbound

This paper cites Scene text recognition with permuted autoregressive sequence models.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Scene text recognition with permuted autoregressive sequence models

Reference 3

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source=pdf_text observed=2026-08-03T14:16:50.712261Z digest=sha256:17d96fd881cd913209ff93cb12e7db0348d38a43c4ac22b41c6af5a35070d6e6

Observation 5f038f96-9ab6-49e5-9683-ed420f4821ee · outbound

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

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Nougat: Neural Optical Understanding for Academic Documents

Reference 4

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source=pdf_text observed=2026-08-03T14:16:50.714937Z digest=sha256:ea0668238dcee47a66952615d14935748834e765342e269a1e970cf43901e9c8

Observation 161cf865-5fd8-4617-a274-40e0ee850090 · outbound

This paper cites Pix2text.https://github.com/breezedeus/Pix2Text, 2022.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Pix2text.https://github.com/breezedeus/Pix2Text, 2022

Reference 5

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source=pdf_text observed=2026-08-03T14:16:50.717930Z digest=sha256:c18cd0aef2b9c74a4ebc8cdc887d07c917a04b16d43f5c2f2bbe14647957fdb2

Observation 2fdfaa40-8c72-4109-b811-c69bbeed68de · outbound

This paper cites Ocrflux.https://github.com/chatdoc-com/OCRFlux, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Ocrflux.https://github.com/chatdoc-com/OCRFlux, 2025

Reference 6

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source=pdf_text observed=2026-08-03T14:16:50.720644Z digest=sha256:3bf5968373ed9da37ac57f24e53249d92bdb4a5043e6e0dff8bc846dcfd84b06

Observation 158a39c1-ba1f-4bdb-bbfb-83db6cf9faef · outbound

This paper cites Ocean-OCR: Towards General OCR Application via a Vision-Language Model.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Ocean-OCR: Towards General OCR Application via a Vision-Language Model

Reference 7

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source=pdf_text observed=2026-08-03T14:16:50.723234Z digest=sha256:d90ac674e7312d2034145a509b70b34b5cee6ffbe2164d9c01e0b62d8eb1d4d0

Observation 7cad0f91-d263-40d7-9de3-56a142d21a6c · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 8

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source=pdf_text observed=2026-08-03T14:16:50.725886Z digest=sha256:13bfda7de0f8a3b448d773028c4db1a781e8b885704d16de2d54daea45871a8d

Observation 6d6b3bba-7e49-4e24-b1e7-b902b0206cf1 · outbound

This paper cites Paddleocr-vl: Boosting multilingual document parsing via a 0.9 b ultra-compact vision-language model.arXivpreprintarXiv:2510.14528, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Paddleocr-vl: Boosting multilingual document parsing via a 0.9 b ultra-compact vision-language model.arXivpreprintarXiv:2510.14528, 2025

Reference 9

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source=pdf_text observed=2026-08-03T14:16:50.728416Z digest=sha256:e493d3aa9d69a3d12cf6f64c87a5e8e637fdfd8961e28a97beeef1e930d33827

Observation 04562bf1-19b0-43b4-af68-37448fcbcafd · outbound

This paper cites PaddleOCR 3.0 Technical Report.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters PaddleOCR 3.0 Technical Report

Reference 10

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source=pdf_text observed=2026-08-03T14:16:50.730919Z digest=sha256:865097febda5d942a7e252acd3fa36f0b6d03e32f34a90d8cc5a067b69e3ebe1

Observation d4983ca0-6b3b-436b-ae5a-2d3f24afa246 · outbound

This paper cites Image-to-markup generation with coarse-to- fine attention.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Image-to-markup generation with coarse-to- fine attention

Reference 11

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source=pdf_text observed=2026-08-03T14:16:50.733667Z digest=sha256:c205267cf785d1e6add53b80959ee980137bf926dc83be462ccc39ceddb16f3e

Observation 4b6b94c7-a8cb-466b-a70b-90906489bddb · outbound

This paper cites SVTR: Scene text recognition with a single visual model.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters SVTR: Scene text recognition with a single visual model

Reference 12

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source=pdf_text observed=2026-08-03T14:16:50.736049Z digest=sha256:87f3c78ce4ba34d70e8236df1cf0b6adcdec84fc250f7b610ee01e7b1975bf9f

Observation 321ebb37-c762-40f0-a848-65bb29bab31b · outbound

This paper cites Out of length text recognition with sub-string matching.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Out of length text recognition with sub-string matching

Reference 13

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source=pdf_text observed=2026-08-03T14:16:50.738629Z digest=sha256:b99ff09c07635f970f17736725ebf9a1b8202dceb4370732d6403adfc7137df4

Observation acd732ac-b4f1-4cc0-8d76-e3447fedc867 · outbound

This paper cites Contextperception parallel decoder for scene text recognition.IEEE Trans.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Contextperception parallel decoder for scene text recognition.IEEE Trans

Reference 14

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source=pdf_text observed=2026-08-03T14:16:50.740920Z digest=sha256:b7c5a874eb5ba93b5300fbd1c80be3625fbf34b0b13e27246de4766310ba9050

Observation a98e9fd1-dc39-4bc0-bcdd-d7a96f8d5322 · outbound

This paper cites Instruction-guided scene text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Instruction-guided scene text recognition

Reference 15

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source=pdf_text observed=2026-08-03T14:16:50.743124Z digest=sha256:f7782c451449b88661e35c17f192ff918c7d00ba9c7ddb59db2083d0105ffe86

Observation 235639c2-7bd0-4eb5-8adc-669d7ffd5a6e · outbound

This paper cites SVTRv2: Ctc beats encoder-decoder models in scene text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters SVTRv2: Ctc beats encoder-decoder models in scene text recognition

Reference 16

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source=pdf_text observed=2026-08-03T14:16:50.745341Z digest=sha256:ed471ace44aae5c79573036c6ea4954ad06935f900fad8fdf6df5fa17151a70c

Observation ae66434f-1617-47de-9439-d85db33413e0 · outbound

This paper cites LaTeX rainbow: Universal LaTeX to PDF document semantic & layout annotation framework.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters LaTeX rainbow: Universal LaTeX to PDF document semantic & layout annotation framework

Reference 17

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source=pdf_text observed=2026-08-03T14:16:50.747565Z digest=sha256:2836b0e2102907111b90ea18f70e56e7c2bf28b2086fed8b6b32845c92ccd49f

Observation b6841d8f-813b-494a-9c45-d458faac63fa · outbound

This paper cites Readlikehumans: Autonomous, bidirectional and iterative language modeling for scene text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Readlikehumans: Autonomous, bidirectional and iterative language modeling for scene text recognition

Reference 18

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source=pdf_text observed=2026-08-03T14:16:50.749764Z digest=sha256:bf53ea593bb96a14c31097724f24c7c0d8c6cba5f68603c37aa3ab55c151e66f

Observation 715c769a-da9a-4b1b-8716-da12c7cac9d0 · outbound

This paper cites ABINet++: Autonomous, bidirectional and iterative language modeling for scene text spotting.IEEETrans.PatternAnal.Mach.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters ABINet++: Autonomous, bidirectional and iterative language modeling for scene text spotting.IEEETrans.PatternAnal.Mach

Reference 19

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source=pdf_text observed=2026-08-03T14:16:50.752208Z digest=sha256:ad4c0103bc075d1c38c52f3c079a38ff1302ca2b6a22e5f640ce68765b4529d5

Observation 70068584-e253-4fed-8c28-d604d219d824 · outbound

This paper cites Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting

Reference 20

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source=pdf_text observed=2026-08-03T14:16:50.754455Z digest=sha256:38855c8b82b4ef6c20a7c561d17d38bf0eb6dd50cad7efcba1968360e89613b8

Observation d12a2af6-343d-4560-a216-291ab6f8a296 · outbound

This paper cites open-parse.https://github.com/Filimoa/open-parse, 2024.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters open-parse.https://github.com/Filimoa/open-parse, 2024

Reference 21

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source=pdf_text observed=2026-08-03T14:16:50.757147Z digest=sha256:58e3ccea36547da4dabb7d081b92afa25fd6916f6223dd351bcb35a1a2f13a66

Observation 33f0f506-f924-49cb-9150-66d973f3f9aa · outbound

This paper cites Gemini 2.5.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Gemini 2.5

Reference 22

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source=pdf_text observed=2026-08-03T14:16:50.759710Z digest=sha256:f712f5f2739ceec8ccef473f8d89bd0b3279b28a46e81a424e102f35043b7f07

Observation d369fac4-92bb-4ee2-8ae9-df20c7702121 · outbound

This paper cites Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks

Reference 23

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source=pdf_text observed=2026-08-03T14:16:50.761995Z digest=sha256:d01602ce7d228c889c2b1da8aedceba90c38f17b9a7b39b3da6f41b6636c2550

Observation 131d07fa-1bf6-4517-958e-30d4323a9ac7 · outbound

This paper cites Self-Supervised Character-to- Character distillation for text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Self-Supervised Character-to- Character distillation for text recognition

Reference 24

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source=pdf_text observed=2026-08-03T14:16:50.764589Z digest=sha256:4d222a03667d78ce68e825b9d2e6363cb2e855b006de8204e14dc36ff4a7d473

Observation 00b8b6ef-d0be-4677-88e4-d814d681dd06 · outbound

This paper cites Seed1.5-VL Technical Report.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Seed1.5-VL Technical Report

Reference 25

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source=pdf_text observed=2026-08-03T14:16:50.766906Z digest=sha256:8ac2698f35bb8bbdf7aec050115358869b7578434a694a862afe4ae8b9bc6b1e

Observation 9a37434c-ee30-4cff-84b6-e85325c8dee2 · outbound

This paper cites ICPR2018 contest on robust reading for multi-type web images.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters ICPR2018 contest on robust reading for multi-type web images

Reference 26

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source=pdf_text observed=2026-08-03T14:16:50.769394Z digest=sha256:b68ed5ff550fc6ae1793862dd35f11be5f1d7f11aa0e2cceed0b7a3c298de8a4

Observation 0c90d904-7f18-4194-ad37-f33035ce7229 · outbound

This paper cites Gtc: Guided training of ctc towards efficient and accurate scene text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Gtc: Guided training of ctc towards efficient and accurate scene text recognition

Reference 27

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source=pdf_text observed=2026-08-03T14:16:50.771835Z digest=sha256:a0f12b4e9e01df206ffbed458b942afa9eab6f0f3c5cc36dde67c44c2243cb90

Observation fa8d85a4-e36c-400e-8da2-6cf1368016f5 · outbound

This paper cites Ocr-free document understanding transformer.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Ocr-free document understanding transformer

Reference 28

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source=pdf_text observed=2026-08-03T14:16:50.774185Z digest=sha256:46bcd9816749eea8860f76c6323a7e3d1ae62ca950e82ea4c023c7a20783ee70

Observation ab6069bf-6a6c-4f41-8b87-2392cb1b3652 · outbound

This paper cites Show, attend and read: A simple and strong baseline for irregular text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Show, attend and read: A simple and strong baseline for irregular text recognition

Reference 29

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source=pdf_text observed=2026-08-03T14:16:50.776508Z digest=sha256:77789bdd5d6d7b712024b9a20dc73143af7d610c435bca904792831baf69abc6

Observation 29aa65cb-d5bc-443a-8b02-2c3918dd2c88 · outbound

This paper cites dots.ocr: Multilingual document layout parsing in a single vision-language model, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters dots.ocr: Multilingual document layout parsing in a single vision-language model, 2025

Reference 30

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source=pdf_text observed=2026-08-03T14:16:50.778715Z digest=sha256:f805573a422126caf1e4e2f560ec88a8a07a2c4770c46c6c7babd717e354c96a

Observation f4bec852-4365-45a2-b85b-4430b59f19ef · outbound

This paper cites Monkeyocr: Documentparsingwithastructure-recognition-relationtripletparadigm.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Monkeyocr: Documentparsingwithastructure-recognition-relationtripletparadigm

Reference 31

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source=pdf_text observed=2026-08-03T14:16:50.781457Z digest=sha256:8908c29ea180a64c6ac64a18a632ad664643f6390e96f24c4462bb60a2c8593f

Observation 05d35b62-ed76-4d65-a604-af5dde9efe32 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 32

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source=pdf_text observed=2026-08-03T14:16:50.783819Z digest=sha256:21950dcb801d2bafaa4fa67afcd1451ab1f6a5f1aa4fa30b2a19dddecb297643

Observation 054d8ded-f234-4d17-819d-a969057cef13 · outbound

This paper cites Casia online and offline chinese handwriting databases.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Casia online and offline chinese handwriting databases

Reference 33

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source=pdf_text observed=2026-08-03T14:16:50.786462Z digest=sha256:8a84e5040f7cb30e249bf0c1e117b3bfa0126a2faafedacf3003a872e11b8765

Observation 97769deb-fd86-43e5-8f63-1cee51cff3d4 · outbound

This paper cites TextMonkey: An OCR-Free Large Multimodal Model for Understanding Document.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters TextMonkey: An OCR-Free Large Multimodal Model for Understanding Document

Reference 34

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source=pdf_text observed=2026-08-03T14:16:50.788856Z digest=sha256:31103edea26039c78dc3ebbeb1303ce5afe38c878bd50cd13f09e9052ae8e862

Observation 8eb03a78-fa9a-4584-bf86-eef964761523 · outbound

This paper cites Towards end-to-end unified scene text detection and layout analysis.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Towards end-to-end unified scene text detection and layout analysis

Reference 35

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source=pdf_text observed=2026-08-03T14:16:50.791849Z digest=sha256:50580551e538544d25024bf32c07c276b0403c7a4d6a357b4082a6a4a443c10c

Observation 7dff6b1e-03b7-4da0-9a74-c0b07e7130bb · outbound

This paper cites Decoupled weight decay regularization.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Decoupled weight decay regularization

Reference 36

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source=pdf_text observed=2026-08-03T14:16:50.794183Z digest=sha256:92474ce488656fdac946a3ff5ca65e19365a6984cb73f6dbddaa82a3f5cd92e1

Observation fe4165a5-d32b-4b0e-ba4b-620cb4c10010 · outbound

This paper cites pix2tex - latex ocr.https://github.com/lukas-blecher/LaTeX-OCR, 2022.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters pix2tex - latex ocr.https://github.com/lukas-blecher/LaTeX-OCR, 2022

Reference 37

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source=pdf_text observed=2026-08-03T14:16:50.796453Z digest=sha256:8a19882d5bed3bf1d2bb41adea4d64f13d7588e5f85dfa2129aac9d43f48f5b4

Observation dc39c52d-fef8-46ab-81e6-64770fe6806b · outbound

This paper cites MORAN: A multi-object rectified attention network for scene text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters MORAN: A multi-object rectified attention network for scene text recognition

Reference 38

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source=pdf_text observed=2026-08-03T14:16:50.798762Z digest=sha256:07944c8d53c6ebc2b0dbf907d892128f613520a153651650b9d76652f51f9b54

Observation 98c0d70a-e2bc-45b0-a735-8b81e1c932af · outbound

This paper cites Nanonets-ocr-s: A model for transforming documents into structured markdown with intelligent content recognition and semantic tagging, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Nanonets-ocr-s: A model for transforming documents into structured markdown with intelligent content recognition and semantic tagging, 2025

Reference 39

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source=pdf_text observed=2026-08-03T14:16:50.800989Z digest=sha256:94d4c54d8357d93ab14aafa2090757ab05339c5cd65b5e437d6b0d0a63090f43

Observation 91bf6949-dab5-42dc-97bb-b2c7458ac6d5 · outbound

This paper cites Mathpix snip: Convert images and pdfs to latex, docx, and more.https://mathpix.com/, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Mathpix snip: Convert images and pdfs to latex, docx, and more.https://mathpix.com/, 2025

Reference 40

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source=pdf_text observed=2026-08-03T14:16:50.803311Z digest=sha256:c2c51ae1075a9db245afdf4c701b07d947fd4c7a2af526af01c0c3fc2d0c9a26

Observation 1a8d3d5e-c9d9-4741-bad0-dea1ffb02914 · outbound

This paper cites SmolDocling: An ultra-compact vision-language model for end-to-end multi-modal document conversion.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters SmolDocling: An ultra-compact vision-language model for end-to-end multi-modal document conversion

Reference 41

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source=pdf_text observed=2026-08-03T14:16:50.805641Z digest=sha256:fa4586f47296929207560d974b097456b550aa43f5eec8a22ec4d115dadc0ca2

Observation 7b66e0d8-457f-4a8e-9507-8d98c1bbc67c · outbound

This paper cites MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing

Reference 42

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source=pdf_text observed=2026-08-03T14:16:50.808178Z digest=sha256:988830af3ba5cc63a116b003697bd3b23a17a65257b0303d7f5a77f2b1e98a6b

Observation ce385e2a-3a62-49b6-b921-9d2a4d1af510 · outbound

This paper cites Mineru2.0-2505-0.9b.https://huggingface.co/opendatalab/MinerU2.0-2505-0.9B, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Mineru2.0-2505-0.9b.https://huggingface.co/opendatalab/MinerU2.0-2505-0.9B, 2025

Reference 43

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source=pdf_text observed=2026-08-03T14:16:50.810808Z digest=sha256:b191054cbc530e7ae50599b249427f140b6196832c910da9ea9bfe04256eacaa

Observation 2c7dd6c0-c468-4e3c-99b0-36dab92a0d09 · outbound

This paper cites Omnidocbench: Benchmarking diverse pdf document parsing with comprehensive annotations.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Omnidocbench: Benchmarking diverse pdf document parsing with comprehensive annotations

Reference 44

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source=pdf_text observed=2026-08-03T14:16:50.813260Z digest=sha256:41419c26347a87f6950f226b5dce7e8b9d612e04bc5002bdd0172d45aaa584a1

Observation e381a954-261c-419c-917f-2fa0a766fcb5 · outbound

This paper cites Marker.https://github.com/datalab-to/marker, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Marker.https://github.com/datalab-to/marker, 2025

Reference 45

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source=pdf_text observed=2026-08-03T14:16:50.815609Z digest=sha256:355ea8ce9268b7c5b8b7273d8831efa3f593b7133ebdd1dc5ef2c4ce39e7b1f7

Observation 4765494e-e21d-4456-b21f-5e6d8f2173a0 · outbound

This paper cites olmocr: Unlocking trillions of tokens in pdfs with vision language models.arXiv preprint arXiv:2502.18443, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters olmocr: Unlocking trillions of tokens in pdfs with vision language models.arXiv preprint arXiv:2502.18443, 2025

Reference 46

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source=pdf_text observed=2026-08-03T14:16:50.817958Z digest=sha256:ac39bc7e9b5926d895ca70d495768d89ef783111397b37d094e44317f1dec32e

Observation 72e2e79e-6422-47e1-a560-6e61578b96e4 · outbound

This paper cites NRTR: A no-recurrence sequence-to-sequence model for scene text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters NRTR: A no-recurrence sequence-to-sequence model for scene text recognition

Reference 47

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source=pdf_text observed=2026-08-03T14:16:50.820400Z digest=sha256:a0fe367c49720e581450c08eb011e47f34ae0afcf0efb419d2775b54ecb9f873

Observation 0968b7f0-604a-4f7b-b4c8-fd7adfcaae72 · outbound

This paper cites An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition.IEEE Trans.PatternAnal.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition.IEEE Trans.PatternAnal

Reference 48

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source=pdf_text observed=2026-08-03T14:16:50.822678Z digest=sha256:d3f43889af838658cf086eb639bb30142e4e6bd557444432510de45b8ebbc05c

Observation 2ae39b67-5ef8-4651-8d63-838757deb200 · outbound

This paper cites ASTER: An attentional scene text recognizer with flexible rectification.IEEETrans.PatternAnal.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters ASTER: An attentional scene text recognizer with flexible rectification.IEEETrans.PatternAnal

Reference 49

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source=pdf_text observed=2026-08-03T14:16:50.827619Z digest=sha256:dca7bdf7433257ad7aa4146d171191b9b4892c3161c49fa67e74785d0c375528

Observation 9b522631-6fb5-47a3-bc9f-c0a245d611c0 · outbound

This paper cites ICDAR 2019 competition on large-scale street view text with partial labeling-rrc-lsvt.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters ICDAR 2019 competition on large-scale street view text with partial labeling-rrc-lsvt

Reference 50

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source=pdf_text observed=2026-08-03T14:16:50.830153Z digest=sha256:edabbe1249e28a2db48f7081609e61b9a17f1a669ea4b883b3c8582d91ca423c

Observation 1bf1d304-a532-4e4c-a03d-afdc02f848de · outbound

This paper cites Tal open dataset.https://ai.100tal.com/dataset, 2023.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Tal open dataset.https://ai.100tal.com/dataset, 2023

Reference 51

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source=pdf_text observed=2026-08-03T14:16:50.832621Z digest=sha256:f573ebb56aa10dd30275ad32f023bc3f30d37498a05e5599ee01016cdae163c5

Observation 39a57880-20f3-4ad5-ac6d-50b24c863880 · outbound

This paper cites Docling.https://github.com/docling-project/docling, 2024.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Docling.https://github.com/docling-project/docling, 2024

Reference 52

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source=pdf_text observed=2026-08-03T14:16:50.835038Z digest=sha256:01cae51abde2a40d07f2626f6515b30441c860bd5616fb34905328d650a132e4

Observation 9fc51d1b-e51d-49a0-9c61-68c8f20a4d7f · outbound

This paper cites Hunyuanocr technical report, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Hunyuanocr technical report, 2025

Reference 53

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source=pdf_text observed=2026-08-03T14:16:50.837293Z digest=sha256:dd4f1be55748503392f59a1e1b23d328cffaa00514ad4c5a0bbb4c38400a4e6a

Observation 84a80519-a6b0-4f5d-a9a4-f08b08442d62 · outbound

This paper cites Kimi-VL Technical Report.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Kimi-VL Technical Report

Reference 54

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source=pdf_text observed=2026-08-03T14:16:50.839790Z digest=sha256:f927a262813fb3dc7ca3b9445c967f541ef165db2bba513b2b2b16d905e30a8e

Observation 91ccdad2-096f-4c70-90e1-72f64bf22547 · outbound

This paper cites Hunyuan-0.5b.https://github.com/Tencent-Hunyuan/Hunyuan-0.5B, 2025.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Hunyuan-0.5b.https://github.com/Tencent-Hunyuan/Hunyuan-0.5B, 2025

Reference 55

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source=pdf_text observed=2026-08-03T14:16:50.842277Z digest=sha256:d3d3ea88c66f327772573dace9631099f84f9667540374cb7c8aef58ab15dba3

Observation aea05b97-e71a-42ac-b0fc-e4206e851fc3 · outbound

This paper cites unstructured.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters unstructured

Reference 56

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source=pdf_text observed=2026-08-03T14:16:50.844649Z digest=sha256:ec7b038110038a895752a371a9420519510fc32a23668e54b2994924117635a9

Observation 8d3a8578-b3b4-4cd3-99a8-27f6e14afe3a · outbound

This paper cites SGDR: stochastic gradient descent with warm restarts.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters SGDR: stochastic gradient descent with warm restarts

Reference 57

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source=pdf_text observed=2026-08-03T14:16:50.846996Z digest=sha256:87367f15a6c2f04cc63d5d1613d4adfd566cb29dda7e3fb42efd883e3e00ba14

Observation 29afa9fa-2fcd-4854-8ed0-4fc0731f3bb0 · outbound

This paper cites UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition

Reference 58

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source=pdf_text observed=2026-08-03T14:16:50.849246Z digest=sha256:dddbe21df29ebe949c1504b7e923bf47dbfe38693f365f7ac9aadcc001a93a0b

Observation 584891c8-84b3-4ab2-bcb6-e25791ac7de3 · outbound

This paper cites MinerU: An Open-Source Solution for Precise Document Content Extraction.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters MinerU: An Open-Source Solution for Precise Document Content Extraction

Reference 59

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source=pdf_text observed=2026-08-03T14:16:50.851889Z digest=sha256:e43fac6171540239918928ccb4dee11ac1e07bc64d2c6c12455f338a56652744

Observation eb1c63bf-b0ab-4c64-b2d1-3cf45bcaaf53 · outbound

This paper cites Multi-Granularity Prediction for scene text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Multi-Granularity Prediction for scene text recognition

Reference 60

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source=pdf_text observed=2026-08-03T14:16:50.854426Z digest=sha256:d67f6041e60d89c0a2f3c309f19d7a00aa6fa6f195f2548e0ca3b7731bc1e87d

Observation ebd85158-f4be-450b-927d-ad062c9ca45b · outbound

This paper cites PETR: Rethinking the capability of transformer-based language model in scene text recognition.IEEETrans.Image Process., 31:5585–5598, 2022.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters PETR: Rethinking the capability of transformer-based language model in scene text recognition.IEEETrans.Image Process., 31:5585–5598, 2022

Reference 61

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source=pdf_text observed=2026-08-03T14:16:50.856804Z digest=sha256:19f12d97b72b0e300b28c9057b8d6409cef5773b7d32d590d10fa7ee8cbe577f

Observation b19ebe6a-47ea-4785-8136-98a70a01bf87 · outbound

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

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model

Reference 62

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source=pdf_text observed=2026-08-03T14:16:50.859133Z digest=sha256:76389ac5827c64d8b4515e659237775cdba1810fe818314b2a97062069d60b18

Observation ffd972dd-6abc-4fa1-96c3-a92009561bbd · outbound

This paper cites DeepSeek-OCR: Contexts Optical Compression.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters DeepSeek-OCR: Contexts Optical Compression

Reference 63

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source=pdf_text observed=2026-08-03T14:16:50.861677Z digest=sha256:16418410675c33f8200161b7f5a39442af08cba9feec1678924b87f8b260b50f

Observation 2ead0d5c-5b9a-4e9c-a740-b353178b8187 · outbound

This paper cites Handwritten mathematical expression recognition via paired adversarial learning.IJCV, 128:2386–2401, 2020.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Handwritten mathematical expression recognition via paired adversarial learning.IJCV, 128:2386–2401, 2020

Reference 64

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source=pdf_text observed=2026-08-03T14:16:50.864152Z digest=sha256:fff46fcf32141db5c3cfb4c651a4650868e1de4b6eb806208446adbd4bbe07f4

Observation 40c91284-f6a7-45df-bf00-a968f2a80498 · outbound

This paper cites Qwen3 Technical Report.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Qwen3 Technical Report

Reference 65

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source=pdf_text observed=2026-08-03T14:16:50.866435Z digest=sha256:b779dd15cc26127b37a6272afd93fb2119ebaf4143dc003d4a7c175e1a8cf5ea

Observation 55bb90cd-8b5d-4e9f-b10a-f6b3d1cfef1f · outbound

This paper cites Kwai Keye-VL 1.5 Technical Report.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Kwai Keye-VL 1.5 Technical Report

Reference 66

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source=pdf_text observed=2026-08-03T14:16:50.869222Z digest=sha256:f6f46ae40ea35f87b9855f58426ced5f1499e540df9335c62a94df67b830a625

Observation 0aafe786-d5fc-44f4-8c7e-d383093b29d8 · outbound

This paper cites Focalmodulationnetworks.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Focalmodulationnetworks

Reference 67

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source=pdf_text observed=2026-08-03T14:16:50.871827Z digest=sha256:92566381a696f3765e561daa2fe207cfd704c841812d7569897d6a0f845cd981

Observation afcc3907-45d1-4d19-a156-ac4d694872da · outbound

This paper cites Towardsaccuratescenetextrecognition with semantic reasoning networks.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Towardsaccuratescenetextrecognition with semantic reasoning networks

Reference 68

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source=pdf_text observed=2026-08-03T14:16:50.874062Z digest=sha256:96e9d0d14c3f88de5cefe7111f786735db5bc38a01fb02334db7d157cf66c72a

Observation 8bc8be7e-a2c6-4ece-9f21-8bdd40fc8c85 · outbound

This paper cites RobustScanner: Dynamically enhancing positional clues for robust text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters RobustScanner: Dynamically enhancing positional clues for robust text recognition

Reference 69

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source=pdf_text observed=2026-08-03T14:16:50.876391Z digest=sha256:80432425389e35ac193c922eaf475d8a0642fb0caea330d6bf472a8b98548baf

Observation 7b084841-172f-4059-a7b4-95e7ff0e0b9c · outbound

This paper cites Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition.PR, 71: 196–206, 2017.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition.PR, 71: 196–206, 2017

Reference 70

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source=pdf_text observed=2026-08-03T14:16:50.878726Z digest=sha256:41b2590892e0975d1857e7be38391894d3ba33079f092edfda8dd9c37f8842b5

Observation b18b3f4d-aa0e-4290-8c3d-c7c2e57d766e · outbound

This paper cites A tree-structured decoder for image-to-markup generation.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters A tree-structured decoder for image-to-markup generation

Reference 71

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source=pdf_text observed=2026-08-03T14:16:50.880964Z digest=sha256:6f1a97804e7ec3ffd2c9ae547433e55d978fc7cd00a4a42f36f6cccfcb492067

Observation e97b92a3-9b0e-42be-86c4-0ee79ab6d7b4 · outbound

This paper cites Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction

Reference 72

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:16:50.883395Z digest=sha256:ba743ce2d1de333dee43e31decc223d9ba7b3b22d13cb5e7eda11578263815ab

Observation 520fcd9a-83a6-497b-adf3-ba86a8f47cbb · outbound

This paper cites Decoder pre-training with only text for scene text recognition.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Decoder pre-training with only text for scene text recognition

Reference 73

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source=pdf_text observed=2026-08-03T14:16:50.885831Z digest=sha256:97db643c8bf21d1e98712c283984361f14dc18b5e8f0e263c6f177255becbf39

Observation 84b97601-8e8b-4241-8dfc-d9833da66737 · outbound

This paper cites CLIP4STR: A simple baseline for scene text recognition with pre-trained vision-language model.IEEE Trans.ImageProcess., 33:6893–6904, 2024.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters CLIP4STR: A simple baseline for scene text recognition with pre-trained vision-language model.IEEE Trans.ImageProcess., 33:6893–6904, 2024

Reference 74

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source=pdf_text observed=2026-08-03T14:16:50.888219Z digest=sha256:ae1e1ee0bf0bccb1c97717cd1ddeb3a19478ee57b2030fcc1f098a5453a5f629

Observation 81565d43-6b99-44e4-a736-b859730b279c · outbound

This paper cites Multi-modal in-context learning makes an ego-evolving scene text recognizer.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Multi-modal in-context learning makes an ego-evolving scene text recognizer

Reference 75

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source=pdf_text observed=2026-08-03T14:16:50.890446Z digest=sha256:3fda3aa0194c5884bde74d5b388fe394ba5e36e30172f9a461a905f443d1cf84

Observation 181e9864-85aa-4df5-8715-c0873e64feff · outbound

This paper cites CDistNet: Perceiving multi- domain character distance for robust text recognition.Int.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters CDistNet: Perceiving multi- domain character distance for robust text recognition.Int

Reference 76

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source=pdf_text observed=2026-08-03T14:16:50.892812Z digest=sha256:1c66be1e8dfd70d04112b962976c56bc05e0495bf280f38160499f9d5e32e367

Observation 0404cc8f-1a92-4f54-a842-7cc6c9581b7c · outbound

This paper cites Vl-reader: Vision and language reconstructor is an effective scene text recognizer.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Vl-reader: Vision and language reconstructor is an effective scene text recognizer

Reference 77

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no resolver link, observed 2026-08-03T14:16:50.895171Z

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source=pdf_text observed=2026-08-03T14:16:50.895171Z digest=sha256:82a809f08287f7899d3192e62201b7a0f6a56b1e570b260e4a7c1cd8a81d9104

Observation 6bc0de05-041f-416a-b5fd-1441d20ce038 · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 78

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source=pdf_text observed=2026-08-03T14:16:50.897448Z digest=sha256:92bc0c0167e1e45eb976cb29151eda7b2026082be64ae6a73224da970738f4e7

Observation 1a70e13d-4ba6-444e-a4ef-5fe4f0e81882 · outbound

This paper cites In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? UniRec-0.1B:.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? UniRec-0.1B:

Reference 80

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source=pdf_text observed=2026-08-03T14:16:50.900402Z digest=sha256:a15df67bd274ad831ee09a3632bc9e6d20db09d77019fff968b197f4816fb0fa

Observation eb0612b7-bf27-4b67-9ad5-bbef18978a11 · outbound

This paper cites In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? Dolphin-1.5-0.3B:.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? Dolphin-1.5-0.3B:

Reference 81

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source=pdf_text observed=2026-08-03T14:16:50.903048Z digest=sha256:1730bdfc06aa5521c3e02c2aa00468302fec85ded45736d2fd1126c2fa619d10

Observation c723b64b-2635-40d4-ab38-2264b6e73637 · outbound

This paper cites In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? PaddleOCR-VL-0.9B:.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? PaddleOCR-VL-0.9B:

Reference 82

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source=pdf_text observed=2026-08-03T14:16:50.905550Z digest=sha256:1c957569bb8c6185c5fc47d83b6dee4151121c8c782cb31f37e616e8189edd06

Observation d61bc5e5-04b4-4fb1-ad20-bfb9f5941858 · outbound

This paper cites In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? MinerU2.5 -1.2B:.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? MinerU2.5 -1.2B:

Reference 83

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no resolver link, observed 2026-08-03T14:16:50.908103Z

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source=pdf_text observed=2026-08-03T14:16:50.908103Z digest=sha256:1fb442b3326eff9c3611b0e049a289f283691ced1598b2b9f8d4d3ee979f1d4c

Observation 28f3cf33-ca20-4514-9d4f-71766a9c2a50 · outbound

This paper cites In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? MonkeyOCR-pro-3B:.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? MonkeyOCR-pro-3B:

Reference 84

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no resolver link, observed 2026-08-03T14:16:50.910533Z

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source=pdf_text observed=2026-08-03T14:16:50.910533Z digest=sha256:9a3bbac1da9c2a075d50d0ea864096e6f1bb02cfebd2ef8f40560ad6bfdf39f7

Observation 973d674e-2d7d-4145-bba3-3a220ca7dfea · outbound

This paper cites In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? dots.ocr-3B:.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? dots.ocr-3B:

Reference 85

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no resolver link, observed 2026-08-03T14:16:50.913066Z

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source=pdf_text observed=2026-08-03T14:16:50.913066Z digest=sha256:ea9fd333220843b8fa98aa71872a01bda7811ba6fc7887b11905b4e7f1400e38

Observation 0a9b107b-bf61-4b7e-8741-68c67ac1251b · outbound

This paper cites In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? Nanonets-OCR2-3B: $\frac{3}{7}$ DeepSeek-OCR-3B :.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters In all, what fraction of the number of bills that Bree received for her birthday were $10 or $20 bills? Nanonets-OCR2-3B: $\frac{3}{7}$ DeepSeek-OCR-3B :

Reference 86

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source=pdf_text observed=2026-08-03T14:16:50.915647Z digest=sha256:1ce76287c0468ec8551f849c38da9b52fafcf6cd7b81eb222a80f47277a7664c

Observation 5807490c-ace5-4891-8418-4fb19b3df8f0 · outbound

This paper cites a”, “b”, and “c.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters a”, “b”, and “c

Reference 87

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no resolver link, observed 2026-08-03T14:16:50.918006Z

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source=pdf_text observed=2026-08-03T14:16:50.918006Z digest=sha256:5c9a52cd023ddbed04c5b61f90dd26b235c090c8eac2955a8b94327f8d0848cb

Observation 19fb0172-02ee-401c-8c74-5f2341d8170c · outbound

This paper cites an unresolved cited work.

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters Unresolved cited work

Reference 2017

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source=pdf_text observed=2026-08-03T14:16:50.825341Z digest=sha256:8d4251d00bc1c4628d0d40528d057b40c2f56578e01ffeb57db7acd062966851

Pith citing papers

Observation af8e5767-68ca-4c5f-b215-18206842c89f · inbound

Boosting Document Parsing Efficiency and Performance with Coarse-to-Fine Visual Processing cites this paper.

Boosting Document Parsing Efficiency and Performance with Coarse-to-Fine Visual Processing UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Reference 12

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verified exact
arxiv_id, observed 2026-07-14T02:19:24.298662Z

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

source=pdf_text observed=2026-05-15T00:25:19.782732Z digest=sha256:3b9429fbbb9396be5c20ae769d994ecb8f51cbdc5e2c3ace13163d105558256b

Observation 16ae50cd-e768-4f97-b0d1-83057bd1be4e · inbound

MinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scale cites this paper.

MinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scale UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Reference 10

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verified exact
arxiv_id, observed 2026-07-14T02:19:24.298662Z

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

source=pdf_text observed=2026-05-10T18:58:41.377996Z digest=sha256:808e73bd5a60a8124429a3d97e8c18500492b298950311742f688006bbf648a7

Observation 9f7ff89d-acc1-4b56-9e1b-86e449ca2ce4 · inbound

How Far Is Document Parsing from Solved? PureDocBench: A Source-TraceableBenchmark across Clean, Degraded, and Real-World Settings cites this paper.

How Far Is Document Parsing from Solved? PureDocBench: A Source-TraceableBenchmark across Clean, Degraded, and Real-World Settings UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Reference 38

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arxiv_id, observed 2026-07-14T02:19:24.298662Z

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

source=pdf_text observed=2026-05-11T02:28:02.152600Z digest=sha256:886147bee7fe90a1c5f9bec315663989f993746631e97f4cd63b6b1af961490e

Observation 1aed0f58-41a7-4a5c-87ee-2e2a6b51a5bb · inbound

ABot-OCR Technical Report cites this paper.

ABot-OCR Technical Report UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Reference 10

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arxiv_id, observed 2026-07-14T02:19:24.298662Z

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

source=pdf_text observed=2026-06-29T13:29:17.221676Z digest=sha256:294a5341e752cfb50c5865373945b5c39e6295df340543d670ceb26a4ccfefb8

Observation bb9c2222-ea85-4509-970d-e3e5151a9315 · inbound

PaddleOCR-VL-1.6: Expanding the Frontier of Document Parsing with Under-Optimized Region Refinement and Progressive Post-Training cites this paper.

PaddleOCR-VL-1.6: Expanding the Frontier of Document Parsing with Under-Optimized Region Refinement and Progressive Post-Training UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Reference 37

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arxiv_id, observed 2026-07-14T02:19:24.298662Z

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

source=pdf_text observed=2026-06-28T10:39:14.444486Z digest=sha256:a0709ca78c17ef0df4ed205b8d85308f3d5c9fe9493a172ea485975c93334b86

Observation 59b938e5-6407-4d77-9935-3a041565c732 · inbound

MonkeyOCRv2: A Visual-Text Foundation Model for Document AI cites this paper.

MonkeyOCRv2: A Visual-Text Foundation Model for Document AI UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Reference 25

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no resolver link, observed 2026-07-14T04:45:32.682508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T04:45:32.682508Z digest=sha256:655d925db1f074865de2c2437eafb8356feb945769918e2770f3175a676f6ea2

Observation 5f496906-8501-48a0-a702-47aab7217bf7 · inbound

OvisOCR2 Technical Report cites this paper.

OvisOCR2 Technical Report UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Reference 38

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no resolver link, observed 2026-08-02T04:40:05.856964Z

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source=pdf_text observed=2026-08-02T04:40:05.856964Z digest=sha256:16e2875ca1de32c232cfb111ad8149f64107372eb3d5105e4233db73e1c4c431

Observation 58628b42-3139-4b04-a3aa-1c0c1dddb042 · inbound

HPD-Parsing: Hierarchical Parallel Document Parsing cites this paper.

HPD-Parsing: Hierarchical Parallel Document Parsing UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Reference 31

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no resolver link, observed 2026-08-01T14:16:08.206504Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:16:08.206504Z digest=sha256:6dd5f7a4d2a5c2ca551bd568f57093d152a54e383f68f7e7286399c933c1c469

Observation 1ea373c9-059f-4541-b818-24117a71f0b3 · inbound

NaviDC-OCR: Navigating Document Parsing Across Digital and Camera-Captured Documents cites this paper.

NaviDC-OCR: Navigating Document Parsing Across Digital and Camera-Captured Documents UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Reference 87

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no resolver link, observed 2026-08-15T21:04:30.193325Z

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source=arxiv_source observed=2026-08-15T21:04:30.193325Z digest=sha256:427e80766a224a220c3e4bca501f32f345c445c818266d33016203a26d17939c