no code implementations • ECNLP (ACL) 2022 • Xiaoyu Shen, Gianni Barlacchi, Marco del Tredici, Weiwei Cheng, Bill Byrne, Adrià Gispert
In this paper, we build a benchmark with annotations for both evidence selection and answer generation covering 6 information sources.
no code implementations • ECNLP (ACL) 2022 • Xiaoyu Shen, Gianni Barlacchi, Marco del Tredici, Weiwei Cheng, Adrià Gispert
To fill in this blank, here we study how to effectively incorporate semi-structured answer sources for PQA and focus on presenting answers in a natural, fluent sentence.
1 code implementation • 17 Sep 2021 • Julia Rozanova, Deborah Ferreira, Krishna Dubba, Weiwei Cheng, Dell Zhang, Andre Freitas
Even though BERT and similar pre-trained language models have excelled in several NLP tasks, their use has not been widely explored for the UI grounding domain.
no code implementations • 17 Aug 2020 • Michael Sejr Schlichtkrull, Weiwei Cheng
Generating diverse and relevant questions over text is a task with widespread applications.
no code implementations • SEMEVAL 2018 • Nam Khanh Tran, Weiwei Cheng
In addition to syntactic trees, we also investigate the use of Abstract Meaning Representation in tree-structured models, in order to incorporate both syntactic and semantic information from the sentence.
no code implementations • ACL 2017 • Nedelina Teneva, Weiwei Cheng
Topical PageRank (TPR) uses latent topic distribution inferred by Latent Dirichlet Allocation (LDA) to perform ranking of noun phrases extracted from documents.
no code implementations • 17 Oct 2013 • Willem Waegeman, Krzysztof Dembczynski, Arkadiusz Jachnik, Weiwei Cheng, Eyke Hullermeier
The F-measure, which has originally been introduced in information retrieval, is nowadays routinely used as a performance metric for problems such as binary classification, multi-label classification, and structured output prediction.
no code implementations • NeurIPS 2012 • Weiwei Cheng, Eyke Hüllermeier, Willem Waegeman, Volkmar Welker
Several machine learning methods allow for abstaining from uncertain predictions.
no code implementations • NeurIPS 2011 • Krzysztof J. Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier
The F-measure, originally introduced in information retrieval, is nowadays routinely used as a performance metric for problems such as binary classification, multi-label classification, and structured output prediction.