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Research & Development
Decoding Agent Behavior: A Transformer-Based Approach for Multi-Agent Systems
TLDR: TransAM is a novel transformer-based agent modeling approach for multi-agent systems. It allows a controlled agent to understand and predict the behavior of...
Research & Development
Adaptive AI for Precision Antibody Design: Learning from Nature’s Evolution
TLDR: Researchers have developed a new AI framework for antibody design that mimics how B cells naturally evolve antibodies. This 'Adaptive Multi-Expert Diffusion' system...
Research & Development
SecoustiCodec: Advancing Speech Codecs with Semantic Disentanglement and Real-time Streaming
TLDR: SecoustiCodec is a new speech codec that achieves high-quality, low-bitrate, real-time speech encoding by effectively separating semantic (meaning) and paralinguistic (timbre, emotion) information...
Research & Development
AI-Powered Defense for mmWave Networks Against Beam-Stealing
TLDR: A new framework uses a Deep Reinforcement Learning (DRL) agent with Integrated Sensing and Communications (ISAC) to proactively defend millimeter-wave (mmWave) communication systems...
Research & Development
Satellite Vision: Unpacking the Performance of Transformers and CNNs in Remote Sensing
TLDR: A research paper comprehensively evaluates 11 deep neural networks (5 transformer-based, 6 CNNs) for object detection on three diverse high-resolution satellite imagery datasets...
Research & Development
Advancing Time Series Foundation Models with Synthetic Data Pretraining
TLDR: CAUKER is a new algorithm that generates diverse, causally coherent synthetic time series data for pretraining classification Time Series Foundation Models (TSFMs). It...