Recognising Textual Entailment with Robust Logical Inference
By Johan Bos, Katja Markert. 2005
30 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Yejin Choi
- Noah A. Smith
- Mohit Bansal
- Caiming Xiong
- Richard Socher
- Luke S. Zettlemoyer
- Percy Liang
- Jianfeng Gao
In Information Systems
- Caiming Xiong
- Richard Socher
- Malvina Nissim
- Johannes Bjerva
- Rob van der Goot
- Yejin Choi
- Noah A. Smith
- Bryan McCann
In Natural Language Processing
- Yejin Choi
- Noah A. Smith
- Caiming Xiong
- Mohit Bansal
- Richard Socher
- Graham Neubig
- Luke S. Zettlemoyer
- Yulia Tsvetkov
Citations in the corpus
- The Natural Language Decathlon: Multitask Learning as Question Answering (2018, background): “Natural Language Inference NLI has a long history playing roles in tasks like information retrieval and semantic parsing [Fyodorov et al., 2000, Condoravdi et al., 2003, Bos and Markert, 2005, Dagan et al., 2005, MacCartney and Manning, 2009].”
- The Meaning Factory: Formal Semantics for Recognizing Textual Entailment and Determining Semantic Similarity (2014, methodology): “This is essentially an improved version of the framework introduced by Bos & Markert (2006).”
- Event2Mind: Commonsense Inference on Events, Intents, and Reactions (2018, background): “Previous work in natural language inference has focused on linguistic entailment (Bowman et al., 2015; Bos and Markert, 2005) while ours focuses on commonsense-based inference.”