2 citations · 2 across the 2 of their papers we have counts for
11 papers
B[FM]: Brain Foundation Model via Flow Matching with SplitUNet
Jaedong Hwang, Kathleen Zhang, Wei Dai +5
EEG foundation models can learn generalizable representations from large-scale EEG corpora to enable single-backbone transfer across diverse clinical and brain-computer interface t…
OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization
Keane Ong, Sabri Boughorbel, Luwei Xiao +9
Socially intelligent AI systems must reason across diverse human behavioral tasks and generalize to new social contexts. However, behavioral data is inherently heterogeneous, compr…
Information-theoretic Multimodal Representation Learning for Electrocardiogram Signals
Phu X. Nguyen, Konstantinos Kontras, Wei Dai +5
Electrocardiograms (ECGs) are widely used non-invasive measurements of cardiac activity and play a central role in clinical diagnosis. Recent multimodal approaches align ECG signal…
NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces
Konstantinos Kontras, Trui Osselaer, Stylianos G. Mouslech +12
Foundation models (FMs) promise to extract unified representations that generalize across downstream tasks. They have emerged across fields, including electroencephalography (EEG),…
On the Invariance and Generality of Neural Scaling Laws
Xing Han, Ziyin Liu, Suchi Saria +1
Neural scaling laws establish a predictable relationship between model performance and data or compute, offering crucial guidance for resource allocation in new domains and tasks.…
PuzzleWorld: A Benchmark for Multimodal, Open-Ended Reasoning in Puzzlehunts
Hengzhi Li, Justin Zhang, Brendon Jiang +9
Puzzlehunts are a genre of complex, multi-step puzzles lacking well-defined problem definitions. In contrast to conventional reasoning benchmarks consisting of tasks with clear ins…