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This work explores whether language models encode meaningfully grounded representations of sounds of objects.
Bert rediscovers the classical nlp pipeline
Ian Tenney, Dipanjan Das, and Ellie Pavlick. 2019 · 1905
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What does bert look at? an analysis of bert’s attention
Kevin Clark, Urvashi Khandelwal, Omer Levy, and Christopher D Manning. 2019 · 1906
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Analyzing the structure of attention in a transformer language model
Jesse Vig and Yonatan Belinkov. 2019 · 1906
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A generalized solution of the orthogonal procrustes problem
Peter H. Schönemann. 1966 · 1966
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Probing Contextual Language Models for Common Ground with Visual Representations
Gabriel Ilharco, Rowan Zellers, Ali Farhadi, and Hannaneh Hajishirzi. 2021 · 2005
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Audio set: An ontology and human-labeled dataset for audio events
Jort F Gemmeke, Daniel PW Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R Channing Moore, Manoj Plakal, and Marvin Ritter. 2017 · 2017
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Geographical evaluation of word embeddings
Michal Konkol, Tomáš Brychcín, Michal Nykl, and Tomáš Hercig. 2017 · 2017
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Designing and interpreting probes with control tasks
John Hewitt and Percy Liang. 2019 · 2019
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What does bert learn about the structure of language?
Ganesh Jawahar, Benoît Sagot, and Djamé Seddah. 2019 · 2019
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Linguistic knowledge and transferability of contextual representations
Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, and Noah A. Smith. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data
Emily M. Bender and Alexander Koller. 2020 · 2020
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Panns: Large-scale pretrained audio neural networks for audio pattern recognition
Qiuqiang Kong, Yin Cao, Turab Iqbal, Yuxuan Wang, Wenwu Wang, and Mark D Plumbley. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Do language embeddings capture scales?
Xikun Zhang, Deepak Ramachandran, Ian Tenney, Yanai Elazar, and Dan Roth. 2020 · 2020
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Can language models encode perceptual structure without grounding? a case study in color
Mostafa Abdou, Artur Kulmizev, Daniel Hershcovich, Stella Frank, Ellie Pavlick, and Anders Søgaard. 2021 · 2021
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Fsd50k: an open dataset of human-labeled sound events
Eduardo Fonseca, Xavier Favory, Jordi Pons, Frederic Font, and Xavier Serra. 2021 · 2021
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What do tokens know about their characters and how do they know it?
Ayush Kaushal and Kyle Mahowald. 2022 · 2022
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Efficient training of audio transformers with patchout
Khaled Koutini, Jan Schlüter, Hamid Eghbal-zadeh, and Gerhard Widmer. 2021 · 2022
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Emergent world representations: Exploring a sequence model trained on a synthetic task
Kenneth Li, Aspen K Hopkins, David Bau, Fernanda Viégas, Hanspeter Pfister, and Martin Wattenberg. 2022 · 2022
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Linearly mapping from image to text space
Jack Merullo, Louis Castricato, Carsten Eickhoff, and Ellie Pavlick. 2022 · 2022
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Meaning without reference in large language models
Steven T Piantadosi and Felix Hill. 2022 · 2022
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Yuan Gong, Yu-An Chung, and James Glass. 2021 · 2021
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Implicit representations of meaning in neural language models
Belinda Z. Li, Maxwell Nye, and Jacob Andreas. 2021 · 2021
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Do language models know the way to rome?
Bastien Liétard, Mostafa Abdou, and Anders Søgaard. 2021 · 2021
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Provable limitations of acquiring meaning from ungrounded form: What will future language models understand?
William Merrill, Yoav Goldberg, Roy Schwartz, and Noah A. Smith. 2021 · 2021
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Mapping language models to grounded conceptual spaces
Roma Patel and Ellie Pavlick. 2021 · 2021
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Learning chess blindfolded: Evaluating language models on state tracking
Shubham Toshniwal, Sam Wiseman, Karen Livescu, and Kevin Gimpel. 2021 · 2021
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Probing classifiers: Promises, shortcomings, and advances
Yonatan Belinkov. 2022 · 2022
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More than correlation: Do large language models learn causal representations of space?
Yida Chen, Yixian Gan, Sijia Li, Li Yao, and Xiaohan Zhao. 2023 · 2023
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Geographic and geopolitical biases of language models
Fahim Faisal and Antonios Anastasopoulos. 2023 · 2023
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Language models represent space and time
Wes Gurnee and Max Tegmark. 2023 · 2023
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Evidence of meaning in language models trained on programs
Charles Jin and Martin Rinard. 2023 · 2023
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Implications of the Convergence of Language and Vision Model Geometries
Jiaang Li, Yova Kementchedjhieva, and Anders Søgaard. 2023 · 2023
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Symbols and grounding in large language models
Ellie Pavlick. 2023 · 2023
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Grounding the vector space of an octopus: Word meaning from raw text
Anders Søgaard. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
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Emergence of abstract state representations in embodied sequence modeling
Tian Yun, Zilai Zeng, Kunal Handa, Ashish V Thapliyal, Bo Pang, Ellie Pavlick, and Chen Sun. 2023 · 2023
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