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Masahiro Kaneko
Masahiro Kaneko
Verified email at nlp.c.titech.ac.jp - Homepage
Title
Cited by
Cited by
Year
Encoder-decoder models can benefit from pre-trained masked language models in grammatical error correction
M Kaneko, M Mita, S Kiyono, J Suzuki, K Inui
arXiv preprint arXiv:2005.00987, 2020
1452020
Gender-preserving debiasing for pre-trained word embeddings
M Kaneko, D Bollegala
arXiv preprint arXiv:1906.00742, 2019
1422019
Debiasing pre-trained contextualised embeddings
M Kaneko, D Bollegala
arXiv preprint arXiv:2101.09523, 2021
1092021
Unmasking the mask–evaluating social biases in masked language models
M Kaneko, D Bollegala
Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 11954 …, 2022
502022
Multi-head multi-layer attention to deep language representations for grammatical error detection
M Kaneko, M Komachi
Computación y Sistemas 23 (3), 883-891, 2019
392019
Gender bias in masked language models for multiple languages
M Kaneko, A Imankulova, D Bollegala, N Okazaki
arXiv preprint arXiv:2205.00551, 2022
382022
Dictionary-based debiasing of pre-trained word embeddings
M Kaneko, D Bollegala
arXiv preprint arXiv:2101.09525, 2021
362021
Grammatical Error Detection Using Error-and Grammaticality-Specific Word Embeddings
M Kaneko, Y Sakaizawa, M Komachi
Proceedings of the Eighth International Joint Conference on Natural Language …, 2017
352017
Debiasing isn't enough!--On the Effectiveness of Debiasing MLMs and their Social Biases in Downstream Tasks
M Kaneko, D Bollegala, N Okazaki
arXiv preprint arXiv:2210.02938, 2022
302022
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models---Is Single-Corpus Evaluation Enough?
M Mita, T Mizumoto, M Kaneko, R Nagata, K Inui
arXiv preprint arXiv:1904.02927, 2019
262019
Sense Embeddings are also Biased--Evaluating Social Biases in Static and Contextualised Sense Embeddings
Y Zhou, M Kaneko, D Bollegala
arXiv preprint arXiv:2203.07523, 2022
232022
TMU transformer system using BERT for re-ranking at BEA 2019 grammatical error correction on restricted track
M Kaneko, K Hotate, S Katsumata, M Komachi
Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building …, 2019
212019
Interpretability for language learners using example-based grammatical error correction
M Kaneko, S Takase, A Niwa, N Okazaki
arXiv preprint arXiv:2203.07085, 2022
192022
Sentence concatenation approach to data augmentation for neural machine translation
S Kondo, K Hotate, M Kaneko, M Komachi
arXiv preprint arXiv:2104.08478, 2021
182021
SOME: Reference-less sub-metrics optimized for manual evaluations of grammatical error correction
R Yoshimura, M Kaneko, T Kajiwara, M Komachi
Proceedings of the 28th International Conference on Computational …, 2020
172020
A self-refinement strategy for noise reduction in grammatical error correction
M Mita, S Kiyono, M Kaneko, J Suzuki, K Inui
arXiv preprint arXiv:2010.03155, 2020
142020
Outfox: Llm-generated essay detection through in-context learning with adversarially generated examples
R Koike, M Kaneko, N Okazaki
Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21258 …, 2024
122024
Generating diverse corrections with local beam search for grammatical error correction
K Hotate, M Kaneko, M Komachi
Proceedings of the 28th International Conference on Computational …, 2020
122020
Autoencoding improves pre-trained word embeddings
M Kaneko, D Bollegala
arXiv preprint arXiv:2010.13094, 2020
122020
Exploring effectiveness of gpt-3 in grammatical error correction: A study on performance and controllability in prompt-based methods
M Loem, M Kaneko, S Takase, N Okazaki
arXiv preprint arXiv:2305.18156, 2023
102023
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