Can neural networks understand monotonicity reasoning? H Yanaka, K Mineshima, D Bekki, K Inui, S Sekine, L Abzianidze, J Bos arXiv preprint arXiv:1906.06448, 2019 | 80 | 2019 |
HELP: A dataset for identifying shortcomings of neural models in monotonicity reasoning H Yanaka, K Mineshima, D Bekki, K Inui, S Sekine, L Abzianidze, J Bos arXiv preprint arXiv:1904.12166, 2019 | 56 | 2019 |
Do neural models learn systematicity of monotonicity inference in natural language? H Yanaka, K Mineshima, D Bekki, K Inui arXiv preprint arXiv:2004.14839, 2020 | 50 | 2020 |
Acquisition of phrase correspondences using natural deduction proofs H Yanaka, K Mineshima, P Martínez-Gómez, D Bekki arXiv preprint arXiv:1804.07656, 2018 | 24 | 2018 |
Exploring transitivity in neural NLI models through veridicality H Yanaka, K Mineshima, K Inui arXiv preprint arXiv:2101.10713, 2021 | 19 | 2021 |
Multimodal logical inference system for visual-textual entailment R Suzuki, H Yanaka, M Yoshikawa, K Mineshima, D Bekki arXiv preprint arXiv:1906.03952, 2019 | 16 | 2019 |
Compositional evaluation on Japanese textual entailment and similarity H Yanaka, K Mineshima Transactions of the Association for Computational Linguistics 10, 1266-1284, 2022 | 15 | 2022 |
Do grammatical error correction models realize grammatical generalization? M Mita, H Yanaka arXiv preprint arXiv:2106.03031, 2021 | 15 | 2021 |
SyGNS: A systematic generalization testbed based on natural language semantics H Yanaka, K Mineshima, K Inui arXiv preprint arXiv:2106.01077, 2021 | 13 | 2021 |
Assessing the generalization capacity of pre-trained language models through Japanese adversarial natural language inference H Yanaka, K Mineshima Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting …, 2021 | 10 | 2021 |
Determining semantic textual similarity using natural deduction proofs H Yanaka, K Mineshima, P Martínez-Gómez, D Bekki arXiv preprint arXiv:1707.08713, 2017 | 8 | 2017 |
Compositional semantics and inference system for temporal order based on Japanese CCG T Sugimoto, H Yanaka arXiv preprint arXiv:2204.09245, 2022 | 4 | 2022 |
Neural sentence generation from formal semantics K Manome, M Yoshikawa, H Yanaka, P Martínez-Gómez, K Mineshima, ... Proceedings of the 11th International Conference on Natural Language …, 2018 | 4 | 2018 |
Clustering documents on case vectors represented by predicate-argument structures-applied for eliciting technological problems from patents H Yanaka, Y Ohsawa 2016 Federated Conference on Computer Science and Information Systems …, 2016 | 3 | 2016 |
Is Japanese CCGBank empirically correct? A case study of passive and causative constructions D Bekki, H Yanaka arXiv preprint arXiv:2302.14708, 2023 | 2 | 2023 |
Annotating Japanese Numeral Expressions for a Logical and Pragmatic Inference Dataset K Koyano, H Yanaka, K Mineshima, D Bekki Proceedings of the 18th Joint ACL-ISO Workshop on Interoperable Semantic …, 2022 | 2 | 2022 |
Logical inference for counting on semi-structured tables T Kurosawa, H Yanaka arXiv preprint arXiv:2204.07803, 2022 | 2 | 2022 |
Medical Visual Textual Entailment for Numerical Understanding of Vision-and-Language Models H Yanaka, Y Nakamura, Y Chida, T Kurosawa Proceedings of the 5th Clinical Natural Language Processing Workshop, 8-18, 2023 | 1 | 2023 |
A neuro-symbolic approach for multimodal reference expression comprehension A Jain, AR Kondapally, K Yamada, H Yanaka arXiv preprint arXiv:2306.10717, 2023 | 1 | 2023 |
Logic-based inference with phrase abduction using vision-and-language models A Tomihari, H Yanaka IEEE Access, 2023 | 1 | 2023 |