activity
20152023
most citedText to 3D Scene Generation with Rich Lexical Grounding

32 citations · 86 across the 18 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

cs.CL2020

DynaSent: A Dynamic Benchmark for Sentiment Analysis

Christopher Potts, Zhengxuan Wu, Atticus Geiger +1

We introduce DynaSent ('Dynamic Sentiment'), a new English-language benchmark task for ternary (positive/negative/neutral) sentiment analysis. DynaSent combines naturally occurring…

cs.MA2020

Learning Compositional Negation in Populations of Roth-Erev and Neural Agents

Graham Todd, Shane Steinert-Threlkeld, Christopher Potts

Agent-based models and signalling games are useful tools with which to study the emergence of linguistic communication in a tractable setting. These techniques have been used to st…

cs.CL2020

Modeling Subjective Assessments of Guilt in Newspaper Crime Narratives

Elisa Kreiss, Zijian Wang, Christopher Potts

Crime reporting is a prevalent form of journalism with the power to shape public perceptions and social policies. How does the language of these reports act on readers? We seek to…

cs.CL2020

Data and Representation for Turkish Natural Language Inference

Emrah Budur, Rıza Özçelik, Tunga Güngör +1

Large annotated datasets in NLP are overwhelmingly in English. This is an obstacle to progress in other languages. Unfortunately, obtaining new annotated resources for each task in…

cs.CL2020

Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation

Atticus Geiger, Kyle Richardson, Christopher Potts

We address whether neural models for Natural Language Inference (NLI) can learn the compositional interactions between lexical entailment and negation, using four methods: the beha…

cs.CL2020

Pragmatic Issue-Sensitive Image Captioning

Allen Nie, Reuben Cohn-Gordon, Christopher Potts

Image captioning systems have recently improved dramatically, but they still tend to produce captions that are insensitive to the communicative goals that captions should meet. To…