A number of you mentioned in your intros that you’re interested in chatbots, so am starting this discussion.
There have been a number of recent papers on generating text / dialog with GANs, reinforcement learning, etc.
Are there any recent NLP / NLU papers that are essential reading? Hard to tell just searching in Arxiv and the like what is or isn’t a breakthrough paper.
Have any of these been implemented in beta or production systems and shown to lead to an actual improvement in UX for end users? (i.e. increased engagement duration, higher satisfaction / resolution scores)
Lack of real world context / knowledge stunts the effectiveness of most open-ended conversational chatbots. Developers of semi-decent ones compensate by hardcoding thousands of objects and their relationships and attributes. Can this concept modeling be done automatically / implicitly with an NN approach? Seems like you already acquire some level of semantic / topical relatedness just by looking at word vectors.
Some papers on adversarial learning / RL for dialog
Let me know others we can add.
Policy Networks With Two-Stage Training For Dialog Systems (from Maluuba / acquired by Microsoft)
Generating Text With Adversarial Training (Zhang, Gan, Carin)
Adversarial Methods For Semi-Supervised Text Classification (Miyato, Dai, Goodfellow)