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ORCIDAlexander G. Huth
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- affiliation: University of Texas at Austin, TY, USA
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2020 – today
- 2024
[i15]Richard Antonello, Nihita Sarma, Jerry Tang, Jiaru Song, Alexander Huth:
How Many Bytes Can You Take Out Of Brain-To-Text Decoding? CoRR abs/2405.14055 (2024)- [i14]Vinamra Benara, Chandan Singh, John X. Morris, Richard Antonello, Ion Stoica, Alexander G. Huth, Jianfeng Gao:
Crafting Interpretable Embeddings by Asking LLMs Questions. CoRR abs/2405.16714 (2024) - [i13]Richard Antonello, Chandan Singh, Shailee Jain, Aliyah R. Hsu, Jianfeng Gao, Bin Yu, Alexander Huth:
A generative framework to bridge data-driven models and scientific theories in language neuroscience. CoRR abs/2410.00812 (2024) - 2023
- [c12]Aditya R. Vaidya, Javier Turek, Alexander Huth:
Humans and language models diverge when predicting repeating text. CoNLL 2023: 58-69 - [c11]Richard Antonello, Aditya R. Vaidya, Alexander Huth:
Scaling laws for language encoding models in fMRI. NeurIPS 2023 - [c10]Jerry Tang, Meng Du, Vy A. Vo, Vasudev Lal, Alexander Huth:
Brain encoding models based on multimodal transformers can transfer across language and vision. NeurIPS 2023 - [i12]Chandan Singh, Aliyah R. Hsu, Richard Antonello, Shailee Jain, Alexander G. Huth, Bin Yu, Jianfeng Gao:
Explaining black box text modules in natural language with language models. CoRR abs/2305.09863 (2023) - [i11]Richard Antonello, Aditya R. Vaidya, Alexander G. Huth:
Scaling laws for language encoding models in fMRI. CoRR abs/2305.11863 (2023) - [i10]Jerry Tang, Meng Du, Vy A. Vo, Vasudev Lal, Alexander G. Huth:
Brain encoding models based on multimodal transformers can transfer across language and vision. CoRR abs/2305.12248 (2023) - [i9]Aditya R. Vaidya, Javier Turek
, Alexander G. Huth:
Humans and language models diverge when predicting repeating text. CoRR abs/2310.06408 (2023) - 2022
- [c9]Aditya R. Vaidya, Shailee Jain, Alexander Huth:
Self-Supervised Models of Audio Effectively Explain Human Cortical Responses to Speech. ICML 2022: 21927-21944 - [i8]Aditya R. Vaidya, Shailee Jain, Alexander G. Huth:
Self-supervised models of audio effectively explain human cortical responses to speech. CoRR abs/2205.14252 (2022) - 2021
- [c8]Richard Antonello, Nicole Beckage, Javier Turek, Alexander Huth:
Selecting Informative Contexts Improves Language Model Fine-tuning. ACL/IJCNLP (1) 2021: 1072-1085 - [c7]Shivangi Mahto, Vy Ai Vo, Javier S. Turek, Alexander Huth:
Multi-timescale Representation Learning in LSTM Language Models. ICLR 2021 - [c6]Richard Antonello, Javier S. Turek, Vy Ai Vo, Alexander Huth:
Low-dimensional Structure in the Space of Language Representations is Reflected in Brain Responses. NeurIPS 2021: 8332-8344 - [i7]Akarsh Kumar, Aditya R. Vaidya, Alexander G. Huth:
Physically Plausible Pose Refinement using Fully Differentiable Forces. CoRR abs/2105.08196 (2021) - [i6]Richard Antonello, Javier Turek, Vy A. Vo, Alexander Huth:
Low-Dimensional Structure in the Space of Language Representations is Reflected in Brain Responses. CoRR abs/2106.05426 (2021) - 2020
- [j6]Zaiwei Zhang, Zhenpei Yang, Chongyang Ma, Linjie Luo, Alexander Huth, Etienne Vouga, Qixing Huang:
Deep Generative Modeling for Scene Synthesis via Hybrid Representations. ACM Trans. Graph. 39(2): 17:1-17:21 (2020) - [c5]Javier Turek, Shailee Jain, Vy A. Vo, Mihai Capota, Alexander Huth, Theodore L. Willke:
Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network. ICML 2020: 9648-9658 - [c4]Shailee Jain, Vy A. Vo, Shivangi Mahto, Amanda LeBel, Javier S. Turek, Alexander Huth:
Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech. NeurIPS 2020 - [i5]Richard Antonello, Javier Turek, Alexander Huth:
Selecting Informative Contexts Improves Language Model Finetuning. CoRR abs/2005.00175 (2020) - [i4]Shivangi Mahto, Vy A. Vo, Javier S. Turek, Alexander G. Huth:
Multi-timescale representation learning in LSTM Language Models. CoRR abs/2009.12727 (2020)
2010 – 2019
- 2019
- [j5]Pawel J. Matusz, Suzanne Dikker, Alexander G. Huth, Catherine Perrodin:
Are We Ready for Real-world Neuroscience? J. Cogn. Neurosci. 31(3) (2019) - [j4]Anwar Nunez-Elizalde, Alexander G. Huth, Jack L. Gallant:
Voxelwise encoding models with non-spherical multivariate normal priors. NeuroImage 197: 482-492 (2019) - [i3]Javier S. Turek, Shailee Jain, Mihai Capota, Alexander G. Huth, Theodore L. Willke:
A single-layer RNN can approximate stacked and bidirectional RNNs, and topologies in between. CoRR abs/1909.00021 (2019) - 2018
- [c3]Javier S. Turek, Alexander G. Huth:
Efficient, Sparse Representation of Manifold Distance Matrices for Classical Scaling. CVPR 2018: 2850-2858 - [c2]Shailee Jain, Alexander Huth:
Incorporating Context into Language Encoding Models for fMRI. NeurIPS 2018: 6629-6638 - [i2]Zaiwei Zhang, Zhenpei Yang, Chongyang Ma, Linjie Luo, Alexander Huth, Etienne Vouga, Qixing Huang:
Deep Generative Modeling for Scene Synthesis via Hybrid Representations. CoRR abs/1808.02084 (2018) - 2017
- [i1]Javier S. Turek, Alexander Huth:
Sparse and low-rank approximations of large symmetric matrices using biharmonic interpolation. CoRR abs/1705.10887 (2017) - 2016
- [j3]Alexander G. Huth, Wendy A. de Heer, Thomas L. Griffiths, Frédéric E. Theunissen, Jack L. Gallant:
Natural speech reveals the semantic maps that tile human cerebral cortex. Nat. 532(7600): 453-458 (2016) - 2015
- [j2]James S. Gao, Alexander G. Huth, Mark D. Lescroart, Jack L. Gallant:
Pycortex: an interactive surface visualizer for fMRI. Frontiers Neuroinformatics 9: 23 (2015) - 2010
- [j1]Michael Gastpar, Patrick R. Gill, Alexander G. Huth, Frédéric E. Theunissen:
Anthropic correction of information estimates and its application to neural coding. IEEE Trans. Inf. Theory 56(2): 890-900 (2010)
2000 – 2009
- 2008
- [c1]Moran Cerf, Jonathan Harel, Alex Huth, Wolfgang Einhäuser, Christof Koch:
Decoding What People See from Where They Look: Predicting Visual Stimuli from Scanpaths. WAPCV 2008: 15-26
Coauthor Index
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