1 code implementation • 1 Feb 2022 • Joydeep Munshi, Alexander Rakowski, Benjamin H Savitzky, Steven E Zeltmann, Jim Ciston, Matthew Henderson, Shreyas Cholia, Andrew M Minor, Maria KY Chan, Colin Ophus
Implementation of a fast, robust, and fully-automated pipeline for crystal structure determination and underlying strain mapping for crystalline materials is important for many technological applications.
We introduce Span-ConveRT, a light-weight model for dialog slot-filling which frames the task as a turn-based span extraction task.
Building conversational systems in new domains and with added functionality requires resource-efficient models that work under low-data regimes (i. e., in few-shot setups).
General-purpose pretrained sentence encoders such as BERT are not ideal for real-world conversational AI applications; they are computationally heavy, slow, and expensive to train.
Ranked #1 on Conversational Response Selection on PolyAI AmazonQA
We present PolyResponse, a conversational search engine that supports task-oriented dialogue.
Despite their popularity in the chatbot literature, retrieval-based models have had modest impact on task-oriented dialogue systems, with the main obstacle to their application being the low-data regime of most task-oriented dialogue tasks.
Progress in Machine Learning is often driven by the availability of large datasets, and consistent evaluation metrics for comparing modeling approaches.
Sellers in user to user marketplaces can be inundated with questions from potential buyers.
This paper presents a computationally efficient machine-learned method for natural language response suggestion.