{"action":"created","issue":{"url":"https://api.github.com/repos/harvardnlp/seq2seq-attn/issues/18","repository_url":"https://api.github.com/repos/harvardnlp/seq2seq-attn","labels_url":"https://api.github.com/repos/harvardnlp/seq2seq-attn/issues/18/labels{/name}","comments_url":"https://api.github.com/repos/harvardnlp/seq2seq-attn/issues/18/comments","events_url":"https://api.github.com/repos/harvardnlp/seq2seq-attn/issues/18/events","html_url":"https://github.com/harvardnlp/seq2seq-attn/issues/18","id":150480796,"number":18,"title":"Local Attention Model and Content-based Function","user":{"login":"giancds","id":3305726,"avatar_url":"https://avatars.githubusercontent.com/u/3305726?v=3","gravatar_id":"","url":"https://api.github.com/users/giancds","html_url":"https://github.com/giancds","followers_url":"https://api.github.com/users/giancds/followers","following_url":"https://api.github.com/users/giancds/following{/other_user}","gists_url":"https://api.github.com/users/giancds/gists{/gist_id}","starred_url":"https://api.github.com/users/giancds/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/giancds/subscriptions","organizations_url":"https://api.github.com/users/giancds/orgs","repos_url":"https://api.github.com/users/giancds/repos","events_url":"https://api.github.com/users/giancds/events{/privacy}","received_events_url":"https://api.github.com/users/giancds/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":1,"created_at":"2016-04-22T22:01:08Z","updated_at":"2016-04-23T06:37:47Z","closed_at":null,"body":"Hello guys,\r\n\r\nThanks for sharing this amazing repository with us! It will be very useful for a lot of people :-)\r\n\r\nQuick questions:\r\n\r\n1) Which of the content-based functions are you using: dot, general or concat?\r\n\r\n2) Do you guys have any plans of implementing the local attention part of Luong's et al. (2015) paper?\r\n\r\nThanks again for sharing the code\r\n"},"comment":{"url":"https://api.github.com/repos/harvardnlp/seq2seq-attn/issues/comments/213675438","html_url":"https://github.com/harvardnlp/seq2seq-attn/issues/18#issuecomment-213675438","issue_url":"https://api.github.com/repos/harvardnlp/seq2seq-attn/issues/18","id":213675438,"user":{"login":"yoonkim","id":5378003,"avatar_url":"https://avatars.githubusercontent.com/u/5378003?v=3","gravatar_id":"","url":"https://api.github.com/users/yoonkim","html_url":"https://github.com/yoonkim","followers_url":"https://api.github.com/users/yoonkim/followers","following_url":"https://api.github.com/users/yoonkim/following{/other_user}","gists_url":"https://api.github.com/users/yoonkim/gists{/gist_id}","starred_url":"https://api.github.com/users/yoonkim/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yoonkim/subscriptions","organizations_url":"https://api.github.com/users/yoonkim/orgs","repos_url":"https://api.github.com/users/yoonkim/repos","events_url":"https://api.github.com/users/yoonkim/events{/privacy}","received_events_url":"https://api.github.com/users/yoonkim/received_events","type":"User","site_admin":false},"created_at":"2016-04-23T06:37:47Z","updated_at":"2016-04-23T06:37:47Z","body":"Hi!\r\n1) we use the 'general' attention model. we've found it to perform similarly to the concat model while being more memory efficient and faster.\r\n2) we do not have plans to implement the local attention part "}}