Decoding What People See from Where They Look: Predicting Visual Stimuli from Scanpaths. - Moran Cerf; Jonathan Harel; Alex Huth; Wolfgang Einhäuser; Christof Koch (WAPCV, 2008)

Anthropic correction of information estimates and its application to neural coding. - Michael Gastpar; Patrick R. Gill; Alexander G. Huth; Frédéric E. Theunissen (IEEE Trans. Inf. Theory, 2010)

Pycortex: an interactive surface visualizer for fMRI. - James S. Gao; Alexander G. Huth; Mark D. Lescroart; Jack L. Gallant (Frontiers Neuroinformatics, 2015)

Natural speech reveals the semantic maps that tile human cerebral cortex. - Alexander G. Huth; Wendy A. de Heer; Thomas L. Griffiths 001; Frédéric E. Theunissen; Jack L. Gallant (Nat., 2016)

Sparse and low-rank approximations of large symmetric matrices using biharmonic interpolation. - Javier S. Turek; Alexander Huth (CoRR, 2017)

Efficient, Sparse Representation of Manifold Distance Matrices for Classical Scaling. - Javier S. Turek; Alexander G. Huth (CVPR, 2018)

Incorporating Context into Language Encoding Models for fMRI. - Shailee Jain; Alexander Huth (NeurIPS, 2018)

A single-layer RNN can approximate stacked and bidirectional RNNs, and topologies in between. - Javier S. Turek; Shailee Jain; Mihai Capota; Alexander G. Huth; Theodore L. Willke (CoRR, 2019)

Are We Ready for Real-world Neuroscience? - Pawel J. Matusz; Suzanne Dikker; Alexander G. Huth; Catherine Perrodin (J. Cogn. Neurosci., 2019)

Voxelwise encoding models with non-spherical multivariate normal priors. - Anwar Nunez-Elizalde; Alexander G. Huth; Jack L. Gallant (NeuroImage, 2019)

Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network. - Javier Turek; Shailee Jain; Vy A. Vo; Mihai Capota; Alexander Huth; Theodore L. Willke (ICML, 2020)

Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech. - Shailee Jain; Vy A. Vo; Shivangi Mahto; Amanda LeBel; Javier S. Turek; Alexander Huth (NeurIPS, 2020)

Selecting Informative Contexts Improves Language Model Finetuning. - Richard J. Antonello; Javier Turek; Alexander Huth (CoRR, 2020)

Deep Generative Modeling for Scene Synthesis via Hybrid Representations. - Zaiwei Zhang; Zhenpei Yang; Chongyang Ma; Linjie Luo; Alexander Huth; Etienne Vouga; Qixing Huang (ACM Trans. Graph., 2020)

Selecting Informative Contexts Improves Language Model Fine-tuning. - Richard J. Antonello; Nicole Beckage; Javier Turek; Alexander Huth (ACL/IJCNLP (1), 2021)

Multi-timescale Representation Learning in LSTM Language Models. - Shivangi Mahto; Vy Ai Vo; Javier S. Turek; Alexander Huth (ICLR, 2021)

Low-dimensional Structure in the Space of Language Representations is Reflected in Brain Responses. - Richard J. Antonello; Javier S. Turek; Vy Ai Vo; Alexander Huth (NeurIPS, 2021)

Physically Plausible Pose Refinement using Fully Differentiable Forces. - Akarsh Kumar; Aditya R. Vaidya; Alexander G. Huth (CoRR, 2021)

Self-Supervised Models of Audio Effectively Explain Human Cortical Responses to Speech. - Aditya R. Vaidya; Shailee Jain; Alexander Huth (ICML, 2022)

Humans and language models diverge when predicting repeating text. - Aditya R. Vaidya; Javier Turek; Alexander Huth (CoNLL, 2023)

Scaling laws for language encoding models in fMRI. - Richard J. Antonello; Aditya R. Vaidya; Alexander Huth (NeurIPS, 2023)

Brain encoding models based on multimodal transformers can transfer across language and vision. - Jerry Tang; Meng Du; Vy A. Vo; Vasudev Lal; Alexander Huth (NeurIPS, 2023)

Explaining black box text modules in natural language with language models. - Chandan Singh; Aliyah R. Hsu; Richard J. Antonello; Shailee Jain; Alexander G. Huth; Bin Yu 001; Jianfeng Gao 001 (CoRR, 2023)

Crafting Interpretable Embeddings for Language Neuroscience by Asking LLMs Questions. - Vinamra Benara; Chandan Singh; John X. Morris; Richard J. Antonello; Ion Stoica; Alexander Huth; Jianfeng Gao 001 (NeurIPS, 2024)

How Many Bytes Can You Take Out Of Brain-To-Text Decoding? - Richard J. Antonello; Nihita Sarma; Jerry Tang; Jiaru Song; Alexander Huth (CoRR, 2024)

Crafting Interpretable Embeddings by Asking LLMs Questions. - Vinamra Benara; Chandan Singh; John X. Morris; Richard J. Antonello; Ion Stoica; Alexander G. Huth; Jianfeng Gao 001 (CoRR, 2024)

A generative framework to bridge data-driven models and scientific theories in language neuroscience. - Richard J. Antonello; Chandan Singh; Shailee Jain; Aliyah R. Hsu; Jianfeng Gao 001; Bin Yu 001; Alexander Huth (CoRR, 2024)

Assessing Episodic Memory in LLMs with Sequence Order Recall Tasks. - Mathis Pink; Vy A. Vo; Qinyuan Wu; Jianing Mu; Javier S. Turek; Uri Hasson; Kenneth A. Norman; Sebastian Michelmann; Alexander Huth; Mariya Toneva (CoRR, 2024)

Position: Episodic Memory is the Missing Piece for Long-Term LLM Agents. - Mathis Pink; Qinyuan Wu; Vy Ai Vo; Javier Turek; Jianing Mu; Alexander Huth; Mariya Toneva (CoRR, 2025)

BrainWavLM: Fine-tuning Speech Representations with Brain Responses to Language. - Nishitha Vattikonda; Aditya R. Vaidya; Richard J. Antonello; Alexander G. Huth (CoRR, 2025)