| Few-Shot Learning with Metric-Agnostic Conditional Embeddings N Hilliard, L Phillips, S Howland, A Yankov, CD Corley, NO Hodas arXiv preprint arXiv:1802.04376, 2018 | 201 | 2018 |
| Using social media to predict the future: a systematic literature review L Phillips, C Dowling, K Shaffer, N Hodas, S Volkova arXiv preprint arXiv:1706.06134, 2017 | 95 | 2017 |
| The utility of cognitive plausibility in language acquisition modeling: Evidence from word segmentation L Phillips, L Pearl Cognitive science 39 (8), 1824-1854, 2015 | 42 | 2015 |
| Metric-Based Few-Shot Learning for Video Action Recognition C Careaga, B Hutchinson, N Hodas, L Phillips arXiv preprint arXiv:1909.09602, 2019 | 33 | 2019 |
| Perceptual adaptation to sinewave-vocoded speech across languages. T Bent, JL Loebach, L Phillips, DB Pisoni Journal of Experimental Psychology: Human perception and performance 37 (5 …, 2011 | 22 | 2011 |
| Predicting foreign language usage from english-only social media posts S Volkova, S Ranshous, L Phillips Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 17 | 2018 |
| Bayesian inference as a cross-linguistic word segmentation strategy: Always learning useful things L Phillips, L Pearl Proceedings of the 5th Workshop on Cognitive Aspects of Computational …, 2014 | 17 | 2014 |
| Proposal-based few-shot sound event detection for speech and environmental sounds with perceivers P Wolters, L Sizemore, C Daw, B Hutchinson, L Phillips arXiv preprint arXiv:2107.13616, 2021 | 16 | 2021 |
| Bayesian inference as a viable cross-linguistic word segmentation strategy: It¢s all about what¢s useful L Phillips, L Pearl Proceedings of the Annual Meeting of the Cognitive Science Society 36 (36), 2014 | 16 | 2014 |
| Less is more in Bayesian word segmentation: When cognitively plausible learners outperform the ideal L Phillips, L Pearl Proceedings of the Annual Meeting of the Cognitive Science Society 34 (34), 2012 | 15 | 2012 |
| Less is more in Bayesian word segmentation: When cognitively plausible learners outperform the ideal L Phillips, L Pearl Proceedings of the Annual Meeting of the Cognitive Science Society 34 (34), 2012 | 15 | 2012 |
| A study of few-shot audio classification P Wolters, C Careaga, B Hutchinson, L Phillips arXiv preprint arXiv:2012.01573, 2020 | 11 | 2020 |
| Utility-based evaluation metrics for models of language acquisition: A look at speech segmentation L Phillips, L Pearl Proceedings of the 6th workshop on cognitive modeling and computational …, 2015 | 11 | 2015 |
| Explanatory Masks for Neural Network Interpretability L Phillips, G Goh, N Hodas arXiv preprint arXiv:1911.06876, 2019 | 6 | 2019 |
| Evaluating language acquisition models: A utility-based look at Bayesian segmentation L Pearl, L Phillips Language, cognition, and computational models, 185-224, 2018 | 6 | 2018 |
| Fuzzy simplicial networks: A topology-inspired model to improve task generalization in few-shot learning H Kvinge, Z New, N Courts, JH Lee, LA Phillips, CD Corley, A Tuor, ... AAAI Workshop on Meta-Learning and MetaDL Challenge, 77-89, 2021 | 3 | 2021 |
| Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks L Phillips, N Hodas arXiv preprint arXiv:1706.01839, 2017 | 3 | 2017 |
| The role of empirical evidence in modeling speech segmentation L Phillips University of California, Irvine, 2015 | 3 | 2015 |
| Evaluating language acquisition strategies: A cross-linguistic look at early segmentation L Phillips, L Pearl Ms., UC Irvine, 2015 | 2 | 2015 |
| Recursive Decoding: A Situated Cognition Approach to Compositional Generation in Grounded Language Understanding M Setzler, S Howland, L Phillips arXiv preprint arXiv:2201.11766, 2022 | 1 | 2022 |
