Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model | Paper Citation Record

Observation 11908882-3a4b-48e8-acdc-a2931cbf8400 · outbound

This paper cites A multilayer convolutional encoder-decoder neural network for grammati- cal error correction.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model A multilayer convolutional encoder-decoder neural network for grammati- cal error correction

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:32.114050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 42c947c9-121a-45d5-9065-bbc06180dba1 · outbound

This paper cites Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:29.671856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 526034ff-99b1-4bed-8583-5c3c50c56082 · outbound

This paper cites Challenges in arabic natural language processing.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Challenges in arabic natural language processing

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:32.102505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f4e09f36-9430-47fb-bfaa-5c87869722a6 · outbound

This paper cites The first qalb shared task on automatic text correction for arabic.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model The first qalb shared task on automatic text correction for arabic

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:32.091082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5831c810-21eb-487e-9e8d-bb90496a1ab2 · outbound

This paper cites The second qalb shared task on automatic text correction for arabic.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model The second qalb shared task on automatic text correction for arabic

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:32.078254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 682e2c6e-5634-4d25-9cd7-8b528d32f674 · outbound

This paper cites Cmuq@ qalb-2014: An smt-based system for automatic arabic error correction.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Cmuq@ qalb-2014: An smt-based system for automatic arabic error correction

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:32.067625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1b0f43ec-e042-4214-b209-780a8ab3ace5 · outbound

This paper cites A web-based annotation framework for large-scale text correction.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model A web-based annotation framework for large-scale text correction

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:32.054752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d87ad25e-7bf9-42ba-9f56-4ae9ce87c7e5 · outbound

This paper cites Synthetic data with neural machine translation for automatic correction in arabic grammar.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Synthetic data with neural machine translation for automatic correction in arabic grammar

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:32.041398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation eaf0fc8e-3e76-482f-a85d-0bb56e742791 · outbound

This paper cites Automatic arabic grammatical error correction based on expectation-maximization routing and target-bidirectional agreement.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Automatic arabic grammatical error correction based on expectation-maximization routing and target-bidirectional agreement

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:32.024721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 486d6a3d-25dd-40c0-9efc-3efebdf4a0fe · outbound

This paper cites Optimizing the impact of data augmentation for low-resource grammatical error correction.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Optimizing the impact of data augmentation for low-resource grammatical error correction

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:32.005843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 19c875e4-b574-46b0-8cf0-30af8b96bbf5 · outbound

This paper cites ChatGPT for Arabic Grammatical Error Correction.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model ChatGPT for Arabic Grammatical Error Correction

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-08T19:53:30.768568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 021fefab-b7b1-48ff-84f6-6299784a62ad · outbound

This paper cites Automatic Error Type Annotation for Arabic.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Automatic Error Type Annotation for Arabic

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-08T19:53:30.577531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 995283e8-21a7-4812-9066-0d508e612e76 · outbound

This paper cites Arabic grammatical error detection using transformers-based pretrained language models.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Arabic grammatical error detection using transformers-based pretrained language models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.908732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2e39168d-03ca-4cdd-971c-e49021555d8c · outbound

This paper cites A7’ ta: Data on a monolingual arabic parallel corpus for grammar checking.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model A7’ ta: Data on a monolingual arabic parallel corpus for grammar checking

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.754904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c24f1bbf-9984-4a02-81f6-fd674ae56fce · outbound

This paper cites Arabert: Transformer-based model for arabic language under- standing.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Arabert: Transformer-based model for arabic language under- standing

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.741914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8fe5a1f8-3b6c-4809-a0c4-0515590d318a · outbound

This paper cites Leveraging offensive language for sarcasm and sentiment detection in arabic.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Leveraging offensive language for sarcasm and sentiment detection in arabic

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.687711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f6e9a928-82b2-4256-b14b-b239bbd671b0 · outbound

This paper cites ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.048476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c218d7f-fff0-45b7-bcf1-8858538fe6dd · outbound

This paper cites The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.090899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 995a9ae2-2e2d-4f5b-8816-ed93d8dde357 · outbound

This paper cites DeBERTa: Decoding-enhanced BERT with Disentangled Attention.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model DeBERTa: Decoding-enhanced BERT with Disentangled Attention

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.105209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 834a7d28-0ae4-4652-89ce-0dd21dd0e0c1 · outbound

This paper cites DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.117686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85add96f-a29f-4c5b-97b1-2639ab704375 · outbound

This paper cites 1.5 billion words Arabic Corpus.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model 1.5 billion words Arabic Corpus

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.122696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f788973c-67c0-46ea-a1a8-52358ebffd53 · outbound

This paper cites Osian: Open source international arabic news corpus-preparation and integration into the clarin-infrastructure.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Osian: Open source international arabic news corpus-preparation and integration into the clarin-infrastructure

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.516071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 90cd97df-a2de-407f-b955-1c7a7925d7e9 · outbound

This paper cites A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.129500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 246247e4-2ae8-48ff-9637-75f79543c926 · outbound

This paper cites Asynchronous pipeline for processing huge corpora on medium to low resource infrastructures.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Asynchronous pipeline for processing huge corpora on medium to low resource infrastructures

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.503523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c17fac36-b490-4943-abad-b7ff9d2acbdc · outbound

This paper cites Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.137139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f57c0a4d-b785-4d31-ae97-c37f314b2db6 · outbound

This paper cites Openwebtext corpus, 2019.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Openwebtext corpus, 2019

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.460938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c90955bd-0f09-4a04-bc3a-5fa97d647eb2 · outbound

This paper cites A Simple Method for Commonsense Reasoning.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model A Simple Method for Commonsense Reasoning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.144940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e44335a-055e-43a0-9bde-7cc18868b5a3 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.149612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 448d7c2e-5a14-4bbb-82c9-e8a770fc9daa · outbound

This paper cites mT5: A massively multilingual pre-trained text-to-text transformer.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model mT5: A massively multilingual pre-trained text-to-text transformer

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.153016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 849ceb4f-2001-4ab9-9d0d-442c89696683 · outbound

This paper cites Byt5: Towards a token-free future with pre-trained byte-to-byte models.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Byt5: Towards a token-free future with pre-trained byte-to-byte models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.340318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b0c47e7a-9b4d-4d26-b941-cf83a2720361 · outbound

This paper cites AraT5: Text-to-Text Transformers for Arabic Language Generation.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model AraT5: Text-to-Text Transformers for Arabic Language Generation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.159661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bae4a2fe-9056-4209-b829-5fcb736c3504 · outbound

This paper cites Arabic learner corpora (alc): a taxonomy of coding errors.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Arabic learner corpora (alc): a taxonomy of coding errors

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.247544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 909459f2-3093-4e81-b0a0-42c90bd11857 · outbound

This paper cites Arabic learners written corpus: A resource for research and learning.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Arabic learners written corpus: A resource for research and learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.221291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e0be9fbd-6647-4262-94db-29dd2b6794c3 · outbound

This paper cites Arabic tokenization, part-of-speech tagging and morphological disambiguation in one fell swoop.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Arabic tokenization, part-of-speech tagging and morphological disambiguation in one fell swoop

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:31.043303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f82beba7-a7d3-4ea9-8f91-a5a8b0239a91 · outbound

This paper cites Mada+ tokan: A toolkit for arabic tokenization, diacritization, morphological disambiguation, pos tagging, stemming and lemmatization.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Mada+ tokan: A toolkit for arabic tokenization, diacritization, morphological disambiguation, pos tagging, stemming and lemmatization

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:30.920199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d5ee187f-1b94-49da-94da-be52b9851a17 · outbound

This paper cites Zaebuc: An annotated arabic-english bilingual writer corpus.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Zaebuc: An annotated arabic-english bilingual writer corpus

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:30.909684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 74e422c9-1993-4f9c-a661-faeae5cbd866 · outbound

This paper cites Balancing Methods for Multi-label Text Classification with Long-Tailed Class Distribution.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Balancing Methods for Multi-label Text Classification with Long-Tailed Class Distribution

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T19:53:30.180765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0ccfde8-d00b-44bf-a3d2-a6e84f10b49e · outbound

This paper cites A unified view of multi-label performance measures.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model A unified view of multi-label performance measures

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:30.898776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 05d4e910-546f-4d3b-bf6c-ecd5792df187 · outbound

This paper cites An evaluation of statistical approaches to text categorization.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model An evaluation of statistical approaches to text categorization

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:30.886413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 490b338c-e175-4350-bc4a-03f0a186ee77 · outbound

This paper cites Multilabel classification.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Multilabel classification

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:30.875729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 160abc37-4893-4243-9888-08129549001d · outbound

This paper cites Effective multi-label active learning for text classification.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Effective multi-label active learning for text classification

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:30.862783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation de0703d3-d242-4fb7-b13a-927252935c3a · outbound

This paper cites Better evaluation for grammatical error correction.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Better evaluation for grammatical error correction

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:30.831192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 033a1654-f8e3-4f0d-a44a-d222312c19cf · outbound

This paper cites Transformers: State-of-the-art natural language processing.

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model Transformers: State-of-the-art natural language processing

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:53:30.806970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers