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- University College LondonGB2 papers
- American UniversityUS1 paper
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- École Polytechnique Fédérale de LausanneCH1 paper
- GoodAI (Czechia)CZ1 paper
- Indian Institute of Technology IndoreIN1 paper
- Indian Institute of Technology PatnaIN1 paper
- Michigan Technological UniversityUS1 paper
- National and Kapodistrian University of AthensGR1 paper
- Novartis (China)CN1 paper
- Thompson Rivers UniversityCA1 paper
- Trinity College DublinIE1 paper
4 papers · 1 filter
Accenture at CheckThat! 2021: Interesting claim identification and ranking with contextually sensitive lexical training data augmentation
Evan Williams, Paul Rodrigues, Sieu Tran
This paper discusses the approach used by the Accenture Team for CLEF2021 CheckThat! Lab, Task 1, to identify whether a claim made in social media would be interesting to a wide au…
Can Taxonomy Help? Improving Semantic Question Matching using Question Taxonomy
Deepak Gupta, Rajkumar Pujari, Asif Ekbal +4
In this paper, we propose a hybrid technique for semantic question matching. It uses our proposed two-layered taxonomy for English questions by augmenting state-of-the-art deep lea…
Bi-ISCA: Bidirectional Inter-Sentence Contextual Attention Mechanism for Detecting Sarcasm in User Generated Noisy Short Text
Prakamya Mishra, Saroj Kaushik, Kuntal Dey
Many online comments on social media platforms are hateful, humorous, or sarcastic. The sarcastic nature of these comments (especially the short ones) alters their actual implied s…
Accenture at CheckThat! 2020: If you say so: Post-hoc fact-checking of claims using transformer-based models
Evan Williams, Paul Rodrigues, Valerie Novak
We introduce the strategies used by the Accenture Team for the CLEF2020 CheckThat! Lab, Task 1, on English and Arabic. This shared task evaluated whether a claim in social media te…