Search Results for author: Reuben Cohn-Gordon

Found 7 papers, 4 papers with code

Pragmatic Issue-Sensitive Image Captioning

1 code implementation Findings of the Association for Computational Linguistics 2020 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.

Descriptive Image Captioning +2

Lexical Learning as an Online Optimal Experiment: Building Efficient Search Engines through Human-Machine Collaboration

no code implementations30 Oct 2019 Jacopo Tagliabue, Reuben Cohn-Gordon

Information retrieval (IR) systems need to constantly update their knowledge as target objects and user queries change over time.

Information Retrieval Retrieval

Communication-based Evaluation for Natural Language Generation

1 code implementation SCiL 2020 Benjamin Newman, Reuben Cohn-Gordon, Christopher Potts

Natural language generation (NLG) systems are commonly evaluated using n-gram overlap measures (e. g. BLEU, ROUGE).

Text Generation

Lost in Machine Translation: A Method to Reduce Meaning Loss

1 code implementation NAACL 2019 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 sentence in another language.

Machine Translation Sentence +1

An Incremental Iterated Response Model of Pragmatics

no code implementations WS 2019 Reuben Cohn-Gordon, Noah D. Goodman, Christopher Potts

Recent Iterated Response (IR) models of pragmatics conceptualize language use as a recursive process in which agents reason about each other to increase communicative efficiency.

Referring Expression Referring expression generation

Pragmatically Informative Image Captioning with Character-Level Inference

no code implementations NAACL 2018 Reuben Cohn-Gordon, Noah Goodman, Christopher Potts

We combine a neural image captioner with a Rational Speech Acts (RSA) model to make a system that is pragmatically informative: its objective is to produce captions that are not merely true but also distinguish their inputs from similar images.

Image Captioning Rolling Shutter Correction

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