Zobrazeno 1 - 10
of 200
pro vyhledávání: '"Chitta Baral"'
Publikováno v:
PLoS ONE, Vol 7, Iss 7, p e40946 (2012)
With the large amount of pharmacological and biological knowledge available in literature, finding novel drug indications for existing drugs using in silico approaches has become increasingly feasible. Typical literature-based approaches generate new
Externí odkaz:
https://doaj.org/article/2fd686fdafb44556945f0c76903058ca
Publikováno v:
Logical Methods in Computer Science, Vol Volume 2, Issue 4 (2006)
We present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains and employ a three-valued characterization of domains with sensing actions to
Externí odkaz:
https://doaj.org/article/2b975e62efd1480087f8f24b422f02b5
Autor:
Chitta Baral
Knowledge management and knowledge-based intelligence are areas of importance in the economy and society, and to exploit them fully and efficiently it is necessary both to represent and reason about knowledge via a declarative interface whose input l
Publikováno v:
ACM Transactions on Computing for Healthcare. 2:1-24
In this work, we formulated the named entity recognition (NER) task as a multi-answer knowledge guided question-answer task (KGQA) and showed that the knowledge guidance helps to achieve state-of-the-art results for 11 of 18 biomedical NER datasets.
Autor:
Swaroop Mishra, Arindam Mitra, Neeraj Varshney, Bhavdeep Sachdeva, Peter Clark, Chitta Baral, Ashwin Kalyan
Given the ubiquitous nature of numbers in text, reasoning with numbers to perform simple calculations is an important skill of AI systems. While many datasets and models have been developed to this end, state-of-the-art AI systems are brittle; failin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1eb4da3a8aab4511504ebd0af2d174c4
http://arxiv.org/abs/2204.05660
http://arxiv.org/abs/2204.05660
Publikováno v:
Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing.
Autor:
Tejas Gokhale, Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Chitta Baral, Yezhou Yang
To be successful in single source domain generalization, maximizing diversity of synthesized domains has emerged as one of the most effective strategies. Many of the recent successes have come from methods that pre-specify the types of diversity that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f56053c131d686aef4beff8ed82515a
Information retrieval (IR) is essential in search engines and dialogue systems as well as natural language processing tasks such as open-domain question answering. IR serve an important function in the biomedical domain, where content and sources of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc0aaab49d6ab692907258c7b06abf1c
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers).
Publikováno v:
Findings of the Association for Computational Linguistics: ACL 2022.