1 code implementation • 16 Feb 2023 • Yoichi Aoki, Keito Kudo, Tatsuki Kuribayashi, Ana Brassard, Masashi Yoshikawa, Keisuke Sakaguchi, Kentaro Inui
Neural reasoning accuracy improves when generating intermediate reasoning steps.
1 code implementation • 15 Feb 2023 • Keito Kudo, Yoichi Aoki, Tatsuki Kuribayashi, Ana Brassard, Masashi Yoshikawa, Keisuke Sakaguchi, Kentaro Inui
Compositionality is a pivotal property of symbolic reasoning.
1 code implementation • 17 Jan 2023 • Yuta Matsumoto, Benjamin Heinzerling, Masashi Yoshikawa, Kentaro Inui
Previous research has shown that information about intermediate values of these inputs can be extracted from the activations of the models, but it is unclear where that information is encoded and whether that information is indeed used during inference.
no code implementations • 28 Sep 2021 • Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi, Sho Yokoi, Tatsuki Kuribayashi, Masashi Yoshikawa, Kentaro Inui
Interpretable rationales for model predictions are crucial in practical applications.
no code implementations • ACL 2019 • Riko Suzuki, Hitomi Yanaka, Masashi Yoshikawa, Koji Mineshima, Daisuke Bekki
A large amount of research about multimodal inference across text and vision has been recently developed to obtain visually grounded word and sentence representations.
no code implementations • ACL 2019 • Masashi Yoshikawa, Hiroshi Noji, Koji Mineshima, Daisuke Bekki
We propose a new domain adaptation method for Combinatory Categorial Grammar (CCG) parsing, based on the idea of automatic generation of CCG corpora exploiting cheaper resources of dependency trees.
1 code implementation • 15 Nov 2018 • Masashi Yoshikawa, Koji Mineshima, Hiroshi Noji, Daisuke Bekki
In logic-based approaches to reasoning tasks such as Recognizing Textual Entailment (RTE), it is important for a system to have a large amount of knowledge data.
no code implementations • WS 2018 • Kana Manome, Masashi Yoshikawa, Hitomi Yanaka, Pascual Mart{\'\i}nez-G{\'o}mez, Koji Mineshima, Daisuke Bekki
In this paper, we present a sequence-to-sequence model for generating sentences from logical meaning representations based on event semantics.
no code implementations • NAACL 2018 • Masashi Yoshikawa, Koji Mineshima, Hiroshi Noji, Daisuke Bekki
In formal logic-based approaches to Recognizing Textual Entailment (RTE), a Combinatory Categorial Grammar (CCG) parser is used to parse input premises and hypotheses to obtain their logical formulas.
1 code implementation • ACL 2017 • Masashi Yoshikawa, Hiroshi Noji, Yuji Matsumoto
Our model achieves the state-of-the-art results on English and Japanese CCG parsing.