{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:31:32Z","timestamp":1723015892564},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,8]]},"abstract":"<jats:p>Recurrent neural networks (RNNs) have enjoyed great success in speech recognition, natural language processing, etc. Many variants of RNNs have been proposed, including vanilla RNNs, LSTMs, and GRUs. However, current architectures are not particularly  adept at dealing with tasks involving multi-faceted contents. In this work, we solve this problem by proposing Multiple-Weight RNNs and LSTMs, which rely on multiple weight matrices in an attempt to mimic the human ability of switching between contexts. We present a framework for adapting RNN-based models and analyze the properties of this approach. Our detailed experimental results show that our model outperforms previous work across a range of different tasks and datasets.<\/jats:p>","DOI":"10.24963\/ijcai.2017\/205","type":"proceedings-article","created":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T05:14:07Z","timestamp":1501218847000},"page":"1483-1489","source":"Crossref","is-referenced-by-count":3,"title":["Multiple-Weight Recurrent Neural Networks"],"prefix":"10.24963","author":[{"given":"Zhu","family":"Cao","sequence":"first","affiliation":[{"name":"Tsinghua University"}]},{"given":"Linlin","family":"Wang","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Gerard","family":"de Melo","sequence":"additional","affiliation":[{"name":"Rutgers University"}]}],"member":"10584","event":{"number":"26","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)","University of Technology Sydney (UTS)","Australian Computer Society (ACS)"],"acronym":"IJCAI-2017","name":"Twenty-Sixth International Joint Conference on Artificial Intelligence","start":{"date-parts":[[2017,8,19]]},"theme":"Artificial Intelligence","location":"Melbourne, Australia","end":{"date-parts":[[2017,8,26]]}},"container-title":["Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T07:52:46Z","timestamp":1501228366000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2017\/205"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2017,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2017\/205","relation":{},"subject":[],"published":{"date-parts":[[2017,8]]}}}