Search Results for author: Daphne Ippolito

Found 14 papers, 5 papers with code

Wordcraft: a Human-AI Collaborative Editor for Story Writing

no code implementations15 Jul 2021 Andy Coenen, Luke Davis, Daphne Ippolito, Emily Reif, Ann Yuan

As neural language models grow in effectiveness, they are increasingly being applied in real-world settings.

Few-Shot Learning

Deduplicating Training Data Makes Language Models Better

1 code implementation14 Jul 2021 Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini

As a result, over 1% of the unprompted output of language models trained on these datasets is copied verbatim from the training data.

Language Modelling

RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text

2 code implementations EMNLP 2020 Liam Dugan, Daphne Ippolito, Arun Kirubarajan, Chris Callison-Burch

In recent years, large neural networks for natural language generation (NLG) have made leaps and bounds in their ability to generate fluent text.

Human Detection Text Generation

Toward Better Storylines with Sentence-Level Language Models

1 code implementation ACL 2020 Daphne Ippolito, David Grangier, Douglas Eck, Chris Callison-Burch

We propose a sentence-level language model which selects the next sentence in a story from a finite set of fluent alternatives.

Language Modelling Sentence Embeddings +1

Trading Off Diversity and Quality in Natural Language Generation

no code implementations22 Apr 2020 Hugh Zhang, Daniel Duckworth, Daphne Ippolito, Arvind Neelakantan

For open-ended language generation tasks such as storytelling and dialogue, choosing the right decoding algorithm is critical to controlling the tradeoff between generation quality and diversity.

Text Generation

Contact Tracing Mobile Apps for COVID-19: Privacy Considerations and Related Trade-offs

no code implementations25 Mar 2020 Hyunghoon Cho, Daphne Ippolito, Yun William Yu

Importantly, though we discuss potential modifications, this document is not meant as a formal research paper, but instead is a response to some of the privacy characteristics of direct contact tracing apps like TraceTogether and an early-stage Request for Comments to the community.

Cryptography and Security

Comparison of Diverse Decoding Methods from Conditional Language Models

1 code implementation ACL 2019 Daphne Ippolito, Reno Kriz, Maria Kustikova, João Sedoc, Chris Callison-Burch

While conditional language models have greatly improved in their ability to output high-quality natural language, many NLP applications benefit from being able to generate a diverse set of candidate sequences.

ChatEval: A Tool for Chatbot Evaluation

no code implementations NAACL 2019 Jo{\~a}o Sedoc, Daphne Ippolito, Arun Kirubarajan, Jai Thirani, Lyle Ungar, Chris Callison-Burch

We introduce a unified framework for human evaluation of chatbots that augments existing tools and provides a web-based hub for researchers to share and compare their dialog systems.

Chatbot Open-Domain Dialog

Understanding image motion with group representations

no code implementations ICLR 2018 Andrew Jaegle, Stephen Phillips, Daphne Ippolito, Kostas Daniilidis

Our results demonstrate that this representation is useful for learning motion in the general setting where explicit labels are difficult to obtain.

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