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Sho Takase
Sho Takase
LINE Corporation
Verified email at nlp.c.titech.ac.jp - Homepage
Title
Cited by
Cited by
Year
Neural headline generation on abstract meaning representation
S Takase, J Suzuki, N Okazaki, T Hirao, M Nagata
Proceedings of the 2016 conference on empirical methods in natural language …, 2016
1892016
Positional encoding to control output sequence length
S Takase, N Okazaki
arXiv preprint arXiv:1904.07418, 2019
1132019
Lessons on parameter sharing across layers in transformers
S Takase, S Kiyono
arXiv preprint arXiv:2104.06022, 2021
582021
Improving truthfulness of headline generation
K Matsumaru, S Takase, N Okazaki
arXiv preprint arXiv:2005.00882, 2020
462020
Direct output connection for a high-rank language model
S Takase, J Suzuki, M Nagata
arXiv preprint arXiv:1808.10143, 2018
422018
Rethinking perturbations in encoder-decoders for fast training
S Takase, S Kiyono
arXiv preprint arXiv:2104.01853, 2021
402021
Handling multiword expressions in causality estimation
S Sasaki, S Takase, N Inoue, N Okazaki, K Inui
Proceedings of the 12th International Conference on Computational Semantics …, 2017
322017
Character n-gram embeddings to improve RNN language models
S Takase, J Suzuki, M Nagata
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5074-5082, 2019
282019
Multi-task learning for cross-lingual abstractive summarization
S Takase, N Okazaki
arXiv preprint arXiv:2010.07503, 2020
232020
Fast and large-scale unsupervised relation extraction
S Takase, N Okazaki, K Inui
Proceedings of the 29th Pacific Asia Conference on Language, Information and …, 2015
232015
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
An empirical study of building a strong baseline for constituency parsing
J Suzuki, S Takase, H Kamigaito, M Morishita, M Nagata
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
192018
Joint optimization of tokenization and downstream model
T Hiraoka, S Takase, K Uchiumi, A Keyaki, N Okazaki
arXiv preprint arXiv:2105.12410, 2021
162021
All word embeddings from one embedding
S Takase, S Kobayashi
Advances in Neural Information Processing Systems 33, 3775-3785, 2020
162020
Optimizing word segmentation for downstream task
T Hiraoka, S Takase, K Uchiumi, A Keyaki, N Okazaki
Findings of the Association for Computational Linguistics: EMNLP 2020, 1341-1351, 2020
152020
Modeling semantic compositionality of relational patterns
S Takase, N Okazaki, K Inui
Engineering Applications of Artificial Intelligence 50, 256-264, 2016
152016
Composing distributed representations of relational patterns
S Takase, N Okazaki, K Inui
ACL, 2276-2286, 2016
122016
Source-side prediction for neural headline generation
S Kiyono, S Takase, J Suzuki, N Okazaki, K Inui, M Nagata
arXiv preprint arXiv:1712.08302, 2017
112017
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
On layer normalizations and residual connections in transformers
S Takase, S Kiyono, S Kobayashi, J Suzuki
arXiv preprint arXiv:2206.00330, 2022
92022
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