2 citations · 3 across the 2 of their papers we have counts for
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cs.CL2023
Learning to Model the World with Language
Jessy Lin, Yuqing Du, Olivia Watkins +4
To interact with humans and act in the world, agents need to understand the range of language that people use and relate it to the visual world. While current agents can learn to e…
cs.CL2023
Decision-Oriented Dialogue for Human-AI Collaboration
Jessy Lin, Nicholas Tomlin, Jacob Andreas +1
We describe a class of tasks called decision-oriented dialogues, in which AI assistants such as large language models (LMs) must collaborate with one or more humans via natural lan…
cs.CL2022★ 1 cited
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…