Thu Aug 10th 08:30 AM -- 05:30 PM @ C4.11
Learning to Generate Natural Language
Yishu Miao · Wang Ling · Tsung-Hsien Wen · Kris Cao · Daniela Gerz · Phil Blunsom · Chris Dyer

Research on natural language generation is rapidly growing due to the increasing demand for human-machine communication in natural language. This workshop aims to promote the discussion, exchange, and dissemination of ideas on the topic of text generation, touching several important aspects in this modality: learning schemes and evaluation, model design and structures, advanced decoding strategies, and natural language generation applications. This workshop aims to be a venue for the exchange of ideas regarding data-driven machine learning approaches for text generation, including mainstream tasks such as dialogue generation, instruction generation, and summarization; and for establishing new directions and ideas with potential for impact in the fields of machine learning, deep learning, and NLP.

08:30 AM Tim Baldwin: Learning to Label Documents (Invited Talk)
09:15 AM Dani Yogatama (Invited Talk)
10:00 AM Coffee Break & Poster session 1
10:30 AM Andre Martins: Beyond Softmax: Sparsemax, Constrained Softmax, Differentiable Easy-First (Invited Talk)
11:15 AM Spotlight Paper Presentation (Presentation)
12:00 PM Lunch Break & Poster session 2