29 citations · 60 across the 12 of their papers we have counts for
9 papers · 1 filter
Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent
Ethan A. Chi, Ashwin Paranjape, Abigail See +18
We present Chirpy Cardinal, an open-domain social chatbot. Aiming to be both informative and conversational, our bot chats with users in an authentic, emotionally intelligent way.…
Contextual Semantic Parsing for Multilingual Task-Oriented Dialogues
Mehrad Moradshahi, Victoria Tsai, Giovanni Campagna +1
Robust state tracking for task-oriented dialogue systems currently remains restricted to a few popular languages. This paper shows that given a large-scale dialogue data set in one…
Grounding Open-Domain Instructions to Automate Web Support Tasks
Nancy Xu, Sam Masling, Michael Du +4
Grounding natural language instructions on the web to perform previously unseen tasks enables accessibility and automation. We introduce a task and dataset to train AI agents from…
Localizing Open-Ontology QA Semantic Parsers in a Day Using Machine Translation
Mehrad Moradshahi, Giovanni Campagna, Sina J. Semnani +2
We propose Semantic Parser Localizer (SPL), a toolkit that leverages Neural Machine Translation (NMT) systems to localize a semantic parser for a new language. Our methodology is t…
AutoQA: From Databases To QA Semantic Parsers With Only Synthetic Training Data
Silei Xu, Sina J. Semnani, Giovanni Campagna +1
We propose AutoQA, a methodology and toolkit to generate semantic parsers that answer questions on databases, with no manual effort. Given a database schema and its data, AutoQA au…
A Few-Shot Semantic Parser for Wizard-of-Oz Dialogues with the Precise ThingTalk Representation
Giovanni Campagna, Sina J. Semnani, Ryan Kearns +3
Previous attempts to build effective semantic parsers for Wizard-of-Oz (WOZ) conversations suffer from the difficulty in acquiring a high-quality, manually annotated training set.…
Zero-Shot Transfer Learning with Synthesized Data for Multi-Domain Dialogue State Tracking
Giovanni Campagna, Agata Foryciarz, Mehrad Moradshahi +1
Zero-shot transfer learning for multi-domain dialogue state tracking can allow us to handle new domains without incurring the high cost of data acquisition. This paper proposes new…
Schema2QA: High-Quality and Low-Cost Q&A Agents for the Structured Web
Silei Xu, Giovanni Campagna, Jian Li +1
Building a question-answering agent currently requires large annotated datasets, which are prohibitively expensive. This paper proposes Schema2QA, an open-source toolkit that can g…
Genie: A Generator of Natural Language Semantic Parsers for Virtual Assistant Commands
Giovanni Campagna, Silei Xu, Mehrad Moradshahi +2
To understand diverse natural language commands, virtual assistants today are trained with numerous labor-intensive, manually annotated sentences. This paper presents a methodology…