We present open domain response generation with meta-words. A meta-word is a structured record that describes various attributes of a response, and thus allows us to explicitly model the one-to-many relationship within open domain dialogues and perform response generation in an explainable and controllable manner. To incorporate meta-words into generation, we enhance the sequence-to-sequence architecture with a goal tracking memory network that formalizes meta-word expression as a goal and manages the generation process to achieve the goal with a state memory panel and a state controller. Experimental results on two large-scale datasets indicate that our model can significantly outperform several state-ofthe-art generation models in terms of response relevance, response diversity, accuracy of oneto-many modeling, accuracy of meta-word expression, and human evaluation. * Corresponding author. Message: last week I have a nice trip to New York! Meta-word: Act: yes-no question | Len: 8 | Copy: true | Utts: false | Spe: medium Response 1: Is New York more expensive than California? Meta-word: Act: wh-question | Len: 17 | Copy: false | Utts: true | Spe: high Response 2: Cool, sounds great! What is the tallest building in this city, Chrysler building? Meta-word: Act: statement | Len: 13 | Copy: false | Utts: true | Spe: low Response 3: I don't know what you are talking about. But it seems good.

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