113 citations · 336 across the 20 of their papers we have counts for
7 papers · 1 filter
Answering Open-Domain Questions of Varying Reasoning Steps from Text
Peng Qi, Haejun Lee, Oghenetegiri "TG" Sido +1
We develop a unified system to answer directly from text open-domain questions that may require a varying number of retrieval steps. We employ a single multi-task transformer model…
Neural Generation Meets Real People: Towards Emotionally Engaging Mixed-Initiative Conversations
Ashwin Paranjape, Abigail See, Kathleen Kenealy +7
We present Chirpy Cardinal, an open-domain dialogue agent, as a research platform for the 2019 Alexa Prize competition. Building an open-domain socialbot that talks to real people…
Entity and Evidence Guided Relation Extraction for DocRED
Kevin Huang, Guangtao Wang, Tengyu Ma +1
Document-level relation extraction is a challenging task which requires reasoning over multiple sentences in order to predict relations in a document. In this paper, we pro-pose a…
Do Syntax Trees Help Pre-trained Transformers Extract Information?
Devendra Singh Sachan, Yuhao Zhang, Peng Qi +1
Much recent work suggests that incorporating syntax information from dependency trees can improve task-specific transformer models. However, the effect of incorporating dependency…
Biomedical and Clinical English Model Packages in the Stanza Python NLP Library
Yuhao Zhang, Yuhui Zhang, Peng Qi +2
We introduce biomedical and clinical English model packages for the Stanza Python NLP library. These packages offer accurate syntactic analysis and named entity recognition capabil…
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages
Peng Qi, Yuhao Zhang, Yuhui Zhang +2
We introduce Stanza, an open-source Python natural language processing toolkit supporting 66 human languages. Compared to existing widely used toolkits, Stanza features a language-…
Stay Hungry, Stay Focused: Generating Informative and Specific Questions in Information-Seeking Conversations
Peng Qi, Yuhao Zhang, Christopher D. Manning
We investigate the problem of generating informative questions in information-asymmetric conversations. Unlike previous work on question generation which largely assumes knowledge…