activity
20112023
most citedNatural Language Processing (almost) from Scratch

5.2k citations · 10k across the 79 of their papers we have counts for

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Showing 2020 · cs.CLShow all

9 papers · 2 filters

cs.CL2020★ 9 cited

I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling

Yixin Nie, Mary Williamson, Mohit Bansal +2

To quantify how well natural language understanding models can capture consistency in a general conversation, we introduce the DialoguE COntradiction DEtection task (DECODE) and a…

cs.CL2020

Multi-Modal Open-Domain Dialogue

Kurt Shuster, Eric Michael Smith, Da Ju +1

Recent work in open-domain conversational agents has demonstrated that significant improvements in model engagingness and humanness metrics can be achieved via massive scaling in b…

cs.CL2020★ 97 cited

Recipes for Safety in Open-domain Chatbots

Jing Xu, Da Ju, Margaret Li +3

Models trained on large unlabeled corpora of human interactions will learn patterns and mimic behaviors therein, which include offensive or otherwise toxic behavior and unwanted bi…

cs.CL2020

How to Motivate Your Dragon: Teaching Goal-Driven Agents to Speak and Act in Fantasy Worlds

Prithviraj Ammanabrolu, Jack Urbanek, Margaret Li +3

We seek to create agents that both act and communicate with other agents in pursuit of a goal. Towards this end, we extend LIGHT (Urbanek et al. 2019) -- a large-scale crowd-source…

cs.CL2020★ 42 cited

Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions

Stephen Roller, Y-Lan Boureau, Jason Weston +13

We present our view of what is necessary to build an engaging open-domain conversational agent: covering the qualities of such an agent, the pieces of the puzzle that have been bui…

cs.CL2020

Multi-Dimensional Gender Bias Classification

Emily Dinan, Angela Fan, Ledell Wu +3

Machine learning models are trained to find patterns in data. NLP models can inadvertently learn socially undesirable patterns when training on gender biased text. In this work, we…