33 citations · 85 across the 12 of their papers we have counts for
10 papers · 1 filter
AutoReply: Detecting Nonsense in Dialogue Introspectively with Discriminative Replies
Weiyan Shi, Emily Dinan, Adi Renduchintala +4
Existing approaches built separate classifiers to detect nonsense in dialogues. In this paper, we show that without external classifiers, dialogue models can detect errors in their…
Inferring Rewards from Language in Context
Jessy Lin, Daniel Fried, Dan Klein +1
In classic instruction following, language like "I'd like the JetBlue flight" maps to actions (e.g., selecting that flight). However, language also conveys information about a user…
Reference-Centric Models for Grounded Collaborative Dialogue
Daniel Fried, Justin T. Chiu, Dan Klein
We present a grounded neural dialogue model that successfully collaborates with people in a partially-observable reference game. We focus on a setting where two agents each observe…
Cross-Domain Generalization of Neural Constituency Parsers
Daniel Fried, Nikita Kitaev, Dan Klein
Neural parsers obtain state-of-the-art results on benchmark treebanks for constituency parsing -- but to what degree do they generalize to other domains? We present three results a…
Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation
Ronghang Hu, Daniel Fried, Anna Rohrbach +3
Vision-and-Language Navigation (VLN) requires grounding instructions, such as "turn right and stop at the door", to routes in a visual environment. The actual grounding can connect…
Pragmatically Informative Text Generation
Sheng Shen, Daniel Fried, Jacob Andreas +1
We improve the informativeness of models for conditional text generation using techniques from computational pragmatics. These techniques formulate language production as a game be…