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Beyond bigger models: How efficient multimodal AI is redefining the future of intelligence

Multimodal large language models have shown powerful abilities to understand and reason across text and images, but their ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...

Bolmo’s architecture unlocks efficient byte‑level LM training without sacrificing quality

Ai2 releases Bolmo, a new byte-level language model the company hopes would encourage more enterprises to use byte level architecture.
IEEE

Two-Stream Spatial-Temporal Auto-Encoder With Adversarial Training for Video Anomaly Detection

Abstract: Auto-encoder has been widely used in video anomaly detection which aims to detect abnormal segments in video surveillance. However, the previous auto-encoder methods preferred to reconstruct ...
EurekAlert!

Exploring a novel approach for improving generative AI models

The developed model modified Schrödinger bridge-type diffusion models to add noise to real data through the encoder and reconstructed samples through the decoder. It uses two objective functions, the ...
Scientific Research Publishing

Clark, K., Luong, M.T., Le, Q.V., et al. (2020) ELECTRA: Pre-Training Text Encoders as Discriminators Rather Than Generators. arXiv: 2003.10555.

ABSTRACT: In the field of equipment support, the method of generating equipment support sentence vectors based on word vectors is simple and effective, but it ignores the order and dependency ...