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20112023
most citedOn the Opportunities and Risks of Foundation Models

2.3k citations · 4.7k across the 88 of their papers we have counts for

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Showing 2019 · cs.CLShow all

7 papers · 2 filters

cs.CL2019

Characterizing the dynamics of learning in repeated reference games

Robert D. Hawkins, Michael C. Frank, Noah D. Goodman

The language we use over the course of conversation changes as we establish common ground and learn what our partner finds meaningful. Here we draw upon recent advances in natural…

cs.CL2019

Continual adaptation for efficient machine communication

Robert D. Hawkins, Minae Kwon, Dorsa Sadigh +1

To communicate with new partners in new contexts, humans rapidly form new linguistic conventions. Recent neural language models are able to comprehend and produce the existing conv…

cs.CL2019

Analyzing machine-learned representations: A natural language case study

Ishita Dasgupta, Demi Guo, Samuel J. Gershman +1

As modern deep networks become more complex, and get closer to human-like capabilities in certain domains, the question arises of how the representations and decision rules they le…

cs.CL2019★ 4 cited

Learning to Explain: Answering Why-Questions via Rephrasing

Allen Nie, Erin D. Bennett, Noah D. Goodman

Providing plausible responses to why questions is a challenging but critical goal for language based human-machine interaction. Explanations are challenging in that they require ma…

cs.CL2019

ShapeGlot: Learning Language for Shape Differentiation

Panos Achlioptas, Judy Fan, Robert X. D. Hawkins +2

In this work we explore how fine-grained differences between the shapes of common objects are expressed in language, grounded on images and 3D models of the objects. We first build…

cs.CL2019★ 2 cited

When redundancy is useful: A Bayesian approach to 'overinformative' referring expressions

Judith Degen, Robert D. Hawkins, Caroline Graf +2

Referring is one of the most basic and prevalent uses of language. How do speakers choose from the wealth of referring expressions at their disposal? Rational theories of language…

cs.CL2019★ 3 cited

Lost in Machine Translation: A Method to Reduce Meaning Loss

Reuben Cohn-Gordon, Noah Goodman

A desideratum of high-quality translation systems is that they preserve meaning, in the sense that two sentences with different meanings should not translate to one and the same se…