Large language models are increasingly embedded into academic writing workflows, yet existing assistants remain external to the editor, preventing deep interact...
Paper presents and evaluates various mechanisms for remote access to memory in distributed systems based on two distinct HPC clusters. We are comparing solution...
Eye-based emotion recognition enables eyewear devices to perceive users' emotional states and support emotion-aware interaction, yet deploying such functionalit...
Recent advances in general-purpose AI systems with attention-based transformers offer a potential window into how the neocortex and cerebellum, despite their re...
In this paper, we present a new neural network model based on attribute-specific representations (e.g., color, shape, size), a classic example of associative me...
Memory disaggregation is promising to scale memory capacity and improves utilization in HPC systems. However, the performance overhead of accessing remote memor...
Vector similarity search has become a critical component in AI-driven applications such as large language models (LLMs). To achieve high recall and low latency,...
Metric graphs are structures obtained by associating edges in a standard graph with segments of the real line and gluing these segments at the vertices of the g...
Abusive speech on social media poses a persistent and evolving challenge, driven by the continuous emergence of novel slang and obfuscated terms designed to cir...
Generative modeling has recently shown remarkable promise for visuomotor policy learning, enabling flexible and expressive control across diverse embodied AI ta...
Diffusion models have achieved remarkable success in data-driven learning and in sampling from complex, unnormalized target distributions. Building on this prog...
Self-driving laboratories offer a promising path toward reducing the labor-intensive, time-consuming, and often irreproducible workflows in the biological scien...
