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Found 5 papers, 4 papers with code
WhisBERT: Multimodal Text-Audio Language Modeling on 100M Words
Training on multiple modalities of input can augment the capabilities of a language model.
Quantifying the redundancy between prosody and text
Using a large spoken corpus of English audiobooks, we extract prosodic features aligned to individual words and test how well they can be predicted from LLM embeddings, compared to non-contextual word embeddings.
FABRIC: Personalizing Diffusion Models with Iterative Feedback
In an era where visual content generation is increasingly driven by machine learning, the integration of human feedback into generative models presents significant opportunities for enhancing user experience and output quality.
A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications
Here, we introduce DETRtime, a novel framework for time-series segmentation that creates ocular event detectors that do not require additionally recorded eye-tracking modality and rely solely on EEG data.
EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement Prediction
We present a new dataset and benchmark with the goal of advancing research in the intersection of brain activities and eye movements.
