Implications of the Convergence of Language and Vision Model Geometries
暂无分享,去创建一个
[1] Manu Srinath Halvagal,et al. The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks , 2023, bioRxiv.
[2] Alexander G. Huth,et al. Predictive Coding or Just Feature Discovery? An Alternative Account of Why Language Models Fit Brain Data , 2022, Neurobiology of Language.
[3] Ellie Pavlick,et al. Linearly Mapping from Image to Text Space , 2022, ICLR.
[4] S. Piantadosi,et al. Meaning without reference in large language models , 2022, ArXiv.
[5] J. King,et al. Brains and algorithms partially converge in natural language processing , 2022, Communications Biology.
[6] Ross B. Girshick,et al. Masked Autoencoders Are Scalable Vision Learners , 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[7] Shachar Mirkin,et al. Emergent Structures and Training Dynamics in Large Language Models , 2022, BIGSCIENCE.
[8] Alexandre Gramfort,et al. Long-range and hierarchical language predictions in brains and algorithms , 2021, ArXiv.
[9] Anders Sogaard,et al. Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color , 2021, CONLL.
[10] Anders Sandholm,et al. Analogy Training Multilingual Encoders , 2021, AAAI.
[11] Magnus Sahlgren,et al. The Singleton Fallacy: Why Current Critiques of Language Models Miss the Point , 2021, Frontiers in Artificial Intelligence.
[12] Charles Foster,et al. The Pile: An 800GB Dataset of Diverse Text for Language Modeling , 2020, ArXiv.
[13] Mary Williamson,et al. Recipes for Building an Open-Domain Chatbot , 2020, EACL.
[14] B. Lake,et al. Self-supervised learning through the eyes of a child , 2020, NeurIPS.
[15] Emily M. Bender,et al. Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data , 2020, ACL.
[16] Omer Levy,et al. Emergent linguistic structure in artificial neural networks trained by self-supervision , 2020, Proceedings of the National Academy of Sciences.
[17] Jeremy Blackburn,et al. The Pushshift Reddit Dataset , 2020, ICWSM.
[18] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[19] Ming-Wei Chang,et al. Well-Read Students Learn Better: On the Importance of Pre-training Compact Models , 2019 .
[20] Omer Levy,et al. RoBERTa: A Robustly Optimized BERT Pretraining Approach , 2019, ArXiv.
[21] Gosse Minnema,et al. From Brain Space to Distributional Space: The Perilous Journeys of fMRI Decoding , 2019, ACL.
[22] Ilya Sutskever,et al. Language Models are Unsupervised Multitask Learners , 2019 .
[23] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[24] Jonas Kubilius,et al. Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like? , 2018, bioRxiv.
[25] Anders Søgaard,et al. Why is unsupervised alignment of English embeddings from different algorithms so hard? , 2018, EMNLP.
[26] Quoc V. Le,et al. A Simple Method for Commonsense Reasoning , 2018, ArXiv.
[27] Eneko Agirre,et al. A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings , 2018, ACL.
[28] Anders Søgaard,et al. On the Limitations of Unsupervised Bilingual Dictionary Induction , 2018, ACL.
[29] Lior Wolf,et al. An Iterative Closest Point Method for Unsupervised Word Translation , 2018, ArXiv.
[30] Anders Søgaard,et al. Limitations of Cross-Lingual Learning from Image Search , 2017, Rep4NLP@ACL.
[31] Marie-Francine Moens,et al. Multi-Modal Representations for Improved Bilingual Lexicon Learning , 2016, ACL.
[32] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Stephen Clark,et al. Visual Bilingual Lexicon Induction with Transferred ConvNet Features , 2015, EMNLP.
[34] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[35] Léon Bottou,et al. Learning Image Embeddings using Convolutional Neural Networks for Improved Multi-Modal Semantics , 2014, EMNLP.
[36] Angeliki Lazaridou,et al. Is this a wampimuk? Cross-modal mapping between distributional semantics and the visual world , 2014, ACL.
[37] Simone Paolo Ponzetto,et al. BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network , 2012, Artif. Intell..
[38] Benjamin Van Durme,et al. Learning Bilingual Lexicons Using the Visual Similarity of Labeled Web Images , 2011, IJCAI.
[39] Alexandros Nanopoulos,et al. Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data , 2010, J. Mach. Learn. Res..
[40] S. Harnad. Symbol grounding problem , 1990, Scholarpedia.
[41] P. Lodge,et al. Stepping Back Inside Leibniz's Mill , 1998 .
[42] John R. Searle,et al. Minds, brains, and programs , 1980, Behavioral and Brain Sciences.
[43] P. Schönemann,et al. A generalized solution of the orthogonal procrustes problem , 1966 .