Lawrence Phillips

According to our database, Lawrence Phillips authored at least 15 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Towards a Realistic Long-Term Benchmark for Open-Web Research Agents.

Peter Mühlbacher, Nikos I. Bosse, Lawrence Phillips

CoRR, 2024

2021

Intrinsic uncertainties and where to find them.

Francesco Farina, Lawrence Phillips, Nicola J. Richmond

CoRR, 2021

2019

Explanatory Masks for Neural Network Interpretability.

Lawrence Phillips, Garrett B. Goh, Nathan O. Hodas

CoRR, 2019

Metric-Based Few-Shot Learning for Video Action Recognition.

Chris Careaga, Brian Hutchinson, Nathan Oken Hodas, Lawrence Phillips

CoRR, 2019

Sparse hierarchical representation learning on molecular graphs.

Matthias Bal, Hagen Triendl, Mariana Assmann, Michael Craig, Lawrence Phillips, Jarvist Moore Frost, Usman Bashir, Noor Shaker, Vid Stojevic

CoRR, 2019

2018

Few-Shot Learning with Metric-Agnostic Conditional Embeddings.

Nathan Hilliard, Lawrence Phillips, Scott Howland, Artëm Yankov, Courtney D. Corley, Nathan O. Hodas

CoRR, 2018

Predicting Foreign Language Usage from English-Only Social Media Posts.

Svitlana Volkova, Stephen Ranshous, Lawrence Phillips

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

2017

Using Social Media to Predict the Future: A Systematic Literature Review.

Lawrence Phillips, Chase Dowling, Kyle Shaffer, Nathan Oken Hodas, Svitlana Volkova

CoRR, 2017

Intrinsic and Extrinsic Evaluation of Spatiotemporal Text Representations in Twitter Streams.

Lawrence Phillips, Kyle Shaffer, Dustin Arendt, Nathan Oken Hodas, Svitlana Volkova

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks.

Lawrence Phillips, Nathan Oken Hodas

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2015

The Role of Empirical Evidence in Modeling Speech Segmentation.

Lawrence Phillips

PhD thesis, 2015

The Utility of Cognitive Plausibility in Language Acquisition Modeling: Evidence From Word Segmentation.

Lawrence Phillips, Lisa Pearl

Cogn. Sci., 2015

Utility-based evaluation metrics for models of language acquisition: A look at speech segmentation.

Lawrence Phillips, Lisa Pearl

Proceedings of the 6th Workshop on Cognitive Modeling and Computational Linguistics, 2015

2014

Bayesian inference as a viable cross-linguistic word segmentation strategy: It's all about what's useful.

Lawrence Phillips, Lisa Pearl

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014

2012

"Less is More" in Bayesian Word Segmentation: When cognitively plausible learners outperform the ideal.

Lawrence Phillips, Lisa Pearl

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012