We present the task of Simultaneous Translation and Paraphrasing for Language Education (STAPLE).
Contextual influences on language often exhibit substantial cross-lingual regularities; for example, we are more verbose in situations that require finer distinctions.
For the best setting, the proposed system is able to identify scam ICO projects with 0. 83 precision.
We present a model of pragmatic referring expression interpretation in a grounded communication task (identifying colors from descriptions) that draws upon predictions from two recurrent neural network classifiers, a speaker and a listener, unified by a recursive pragmatic reasoning framework.
We show that from such a set of subsystems, one can use reinforcement learning to build a system that tailors its output to different input contexts at test time.
We introduce a simple, general strategy to manipulate the behavior of a neural decoder that enables it to generate outputs that have specific properties of interest (e. g., sequences of a pre-specified length).
In this paper, drawing intuition from the Turing test, we propose using adversarial training for open-domain dialogue generation: the system is trained to produce sequences that are indistinguishable from human-generated dialogue utterances.
Ranked #1 on Dialogue Generation on Amazon-5
While neural networks have been successfully applied to many natural language processing tasks, they come at the cost of interpretability.
We further propose a variation that is capable of automatically adjusting its diversity decoding rates for different inputs using reinforcement learning (RL).
Recent neural models of dialogue generation offer great promise for generating responses for conversational agents, but tend to be shortsighted, predicting utterances one at a time while ignoring their influence on future outcomes.
The Rational Speech Acts (RSA) model treats language use as a recursive process in which probabilistic speaker and listener agents reason about each other's intentions to enrich the literal semantics of their language along broadly Gricean lines.
The ability to map descriptions of scenes to 3D geometric representations has many applications in areas such as art, education, and robotics.