IEEE

Multimodal Entity Linking With Dynamic Modality Selection and Interactive Prompt Learning

Abstract: Recent advances in Multimodal Entity Linking leverage multimodal information to link target mentions to corresponding entities. However, existing methods uniformly adopt a “one-size-fits-all ...
eLife

Modality-agnostic decoding of vision and language from fMRI

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
IEEE

Modality-Mix Learning: Promoting Multimodal Learning Through Multilabel Objective

Abstract: Multimodal fusion provides a comprehensive way to understand the world by integrating data from different sources. However, some studies believe that due to the optimization imbalance, ...
GitHub

Enhancing Multimodal Model Robustness under Missing Modalities via Memory-Driven Prompt Learning

Existing multimodal models typically assume the availability of all modalities, leading to significant performance degradation when certain modalities are missing. Recent methods have introduced ...
ischool.berkeley.edu

Learning Stylistic Meaning Across Modalities

Naitian Zhou is a Ph.D. stu­dent at the UC Berkeley School of Information, where he is ad­vised by David Bamman and sup­ported by the NSF grad­u­ate re­search fel­low­ship. Naitian’s re­search ...
Frontiers

Evaluating haptic experience using EEG and deep learning across multiple modalities: linking stimulus and self-reports

Conventionally, evaluations of haptic interfaces have relied on self-reported assessments, which offer limited objectivity and can disrupt the user experience, making it challenging to design ...
Forbes

Voice Modality: The Next Frontier In AI And Workflow

We still live in a keyboard world, but every signal says we shouldn’t. Stanford researchers found that speech recognition can be about three times faster than ...
Forbes

The 6 Education Trends That Will Shape Learning And Skills In 2026

As we head towards 2026, AI has become a powerful aid for both learners and teachers, enabling personalized study and creating new ways to teach and engage students. At the same time, industry is ...
ahajournals.org

Abstract 393: Generalizability of Deep Learning Models for Aneurysm Detection: A Systematic Review of Cross‐Center and Cross‐Modality Validation Performance

Deep learning (DL) has demonstrated high diagnostic accuracy in detecting intracranial aneurysms (IAs) on CT angiography (CTA) and digital subtraction angiography (DSA). However, most studies rely on ...
Scientific Research Publishing

Mahmood, T., Li, J., Pei, Y., Akhtar, F., Imran, A. and Rehman, K.U. (2020) A Brief Survey on Breast Cancer Diagnostic with Deep Learning Schemes Using Multi-Image Modalities ...

ABSTRACT: Breast cancer is the most common cancer among women worldwide, posing significant diagnostic challenges. Traditional diagnostic techniques, while foundational, often lack precision and fail ...
ascopubs.org

Bayesian Counterfactual Machine Learning Individualizes Radiation Modality Selection to Mitigate Immunosuppression

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...