| 2023 | EACL | Empirical Investigation of Neural Symbolic Reasoning Strategies. | Yoichi Aoki, Keito Kudo, Tatsuki Kuribayashi, Ana Brassard, Masashi Yoshikawa, Keisuke Sakaguchi, Kentaro Inui |
| 2023 | EACL | Do Deep Neural Networks Capture Compositionality in Arithmetic Reasoning? | Keito Kudo, Yoichi Aoki, Tatsuki Kuribayashi, Ana Brassard, Masashi Yoshikawa, Keisuke Sakaguchi, Kentaro Inui |
| 2019 | AAAI | Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference. | Masashi Yoshikawa, Koji Mineshima, Hiroshi Noji, Daisuke Bekki |
| 2019 | ACL | Multimodal Logical Inference System for Visual-Textual Entailment. | Riko Suzuki, Hitomi Yanaka, Masashi Yoshikawa, Koji Mineshima, Daisuke Bekki |
| 2019 | ACL | Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation. | Masashi Yoshikawa, Hiroshi Noji, Koji Mineshima, Daisuke Bekki |
| 2019 | EDBT | Structural Change Point Detection Using A Large Random Matrix and Sparse Modeling. | Katsuya Ito, Akira Kinoshita, Masashi Yoshikawa |
| 2018 | INLG | Neural sentence generation from formal semantics. | Kana Manome, Masashi Yoshikawa, Hitomi Yanaka, Pascual Martnez-Gmez, Koji Mineshima, Daisuke Bekki |
| 2018 | NAACL | Consistent CCG Parsing over Multiple Sentences for Improved Logical Reasoning. | Masashi Yoshikawa, Koji Mineshima, Hiroshi Noji, Daisuke Bekki |
| 2017 | ACL | A* CCG Parsing with a Supertag and Dependency Factored Model. | Masashi Yoshikawa, Hiroshi Noji, Yuji Matsumoto |
| 2016 | EMNLP | Joint Transition-based Dependency Parsing and Disfluency Detection for Automatic Speech Recognition Texts. | Masashi Yoshikawa, Hiroyuki Shindo, Yuji Matsumoto |