activity
20182026
most citedThe Temporal Structure of Language Processing in the Human Brain Corresponds to The Layered Hierarchy of Deep Language Models

22 citations · 37 across the 9 of their papers we have counts for

collaborators

10 papers

cs.LG2026

Multi-Subject Pretraining Enables Short-Calibration Personalization for Closed-Corpus Surface EMG Speech Decoding

Chenqian Le, Beatrice Fumagalli, Yasamin Esmaeili +5

Surface electromyography (sEMG)-based silent speech interfaces are limited by cross-user variability and calibration burden. We study a limited-data setting in which each of 27 spe…

cs.SD2026

Comparison of sEMG Encoding Accuracy Across Speech Modes Using Articulatory and Phoneme Features

Chenqian Le, Ruisi Li, Beatrice Fumagalli +6

We test whether Speech Articulatory Coding (SPARC) features can linearly predict surface electromyography (sEMG) envelopes across aloud, mimed, and subvocal speech in twenty-four s…

cs.SD2026

AVMeme Exam: A Multimodal Multilingual Multicultural Benchmark for LLMs' Contextual and Cultural Knowledge and Thinking

Xilin Jiang, Qiaolin Wang, Junkai Wu +30

Internet audio-visual clips convey meaning through time-varying sound and motion, which extend beyond what text alone can represent. To examine whether AI models can understand suc…

cs.LG2025

Machine Learning-Based Prediction of Speech Arrest During Direct Cortical Stimulation Mapping

Nikasadat Emami, Amirhossein Khalilian-Gourtani, Jianghao Qian +4

Identifying cortical regions critical for speech is essential for safe brain surgery in or near language areas. While Electrical Stimulation Mapping (ESM) remains the clinical gold…

cs.CL2025

A Scalable Pipeline for Estimating Verb Frame Frequencies Using Large Language Models

Adam M. Morgan, Adeen Flinker

We present an automated pipeline for estimating Verb Frame Frequencies (VFFs), the frequency with which a verb appears in particular syntactic frames. VFFs provide a powerful windo…

cs.SD2025★ 1 cited

AAD-LLM: Neural Attention-Driven Auditory Scene Understanding

Xilin Jiang, Sukru Samet Dindar, Vishal Choudhari +6

Auditory foundation models, including auditory large language models (LLMs), process all sound inputs equally, independent of listener perception. However, human auditory perceptio…

eess.IV2024★ 10 cited

GroupCDL: Interpretable Denoising and Compressed Sensing MRI via Learned Group-Sparsity and Circulant Attention

Nikola Janjusevic, Amirhossein Khalilian-Gourtani, Adeen Flinker +2

Nonlocal self-similarity within images has become an increasingly popular prior in deep-learning models. Despite their successful image restoration performance, such models remain…

cs.CL2023★ 22 cited

The Temporal Structure of Language Processing in the Human Brain Corresponds to The Layered Hierarchy of Deep Language Models

Ariel Goldstein, Eric Ham, Mariano Schain +17

Deep Language Models (DLMs) provide a novel computational paradigm for understanding the mechanisms of natural language processing in the human brain. Unlike traditional psycholing…

eess.IV2023★ 3 cited

Fast and Interpretable Nonlocal Neural Networks for Image Denoising via Group-Sparse Convolutional Dictionary Learning

Nikola Janjušević, Amirhossein Khalilian-Gourtani, Adeen Flinker +1

Nonlocal self-similarity within natural images has become an increasingly popular prior in deep-learning models. Despite their successful image restoration performance, such models…

cs.SD2018★ 1 cited

Reconstructing Speech Stimuli From Human Auditory Cortex Activity Using a WaveNet Approach

Ran Wang, Yao Wang, Adeen Flinker

The superior temporal gyrus (STG) region of cortex critically contributes to speech recognition. In this work, we show that a proposed WaveNet, with limited available data, is able…