All Articles
19232 articles total
From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces
A new framework for Bayesian Optimization in high-dimensional permutation spaces using the 'Merge Kernel' derived from merge sort to improve computational efficiency.
Fusion of Pervasive RF Data with Spatial Images via Vision Transformers for Enhanced Mapping in Smart Cities
A deep learning approach combining DINOv2 and RF data to improve building mapping accuracy in smart cities.
Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning
The GNARL framework reframes neural algorithmic reasoning as a reinforcement learning problem to solve combinatorial NP-hard graph problems without needing expert algorithms.
Q-Net: Queue Length Estimation via Kalman-based Neural Networks
Q-Net is an AI-augmented Kalman filter framework for real-time queue length estimation at intersections using privacy-preserving vehicle counts and speed data.
Shift-Invariant Attribute Scoring for Kolmogorov-Arnold Networks via Shapley Value
ShapKAN is a pruning framework for Kolmogorov-Arnold Networks (KANs) that uses Shapley value attribution to achieve shift-invariant node importance ranking for better compression.
Microsoft turns to AWS as GitHub faces AI capacity crunch
Microsoft is utilizing AWS infrastructure to supplement its AI capacity needs as GitHub faces a shortage of compute resources.
Inside the fight over Claude Mythos 5
Anthropic is facing a legal battle with the US government over export control directives that restrict access to its Mythos 5 and Fable 5 AI models.
MirrorCheck: Efficient Adversarial Defense for Vision-Language Models
MirrorCheck is a new model-agnostic detection framework designed to protect Vision-Language Models from adversarial attacks using semantic consistency checks.
Vanishing Depth: Training Generalized Depth Adapters with Sinusoidal Depth Preprocessing for Pretrained RGB Encoders
Researchers propose a self-supervised depth adapter with sinusoidal preprocessing to improve metric depth understanding in pretrained RGB encoders for robotics.
Revisiting Outage for Edge Inference Systems
A new theoretical framework introduces 'inference outage' (InfOut) to optimize the tradeoff between communication overhead and reliability for 6G edge inference systems.
FPGA-Based Neural Network Accelerators for Space Applications: A Survey
A comprehensive survey on using FPGA-based neural network accelerators to enhance onboard computing systems for space missions.
UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities
UniversalRAG is an any-to-any Retrieval-Augmented Generation framework that integrates knowledge from heterogeneous sources across diverse modalities and granularities.
The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandates
An analysis of how platform API restrictions on social media hinder algorithmic transparency and compliance with the EU Digital Services Act.
Fractured Chain-of-Thought Reasoning
Fractured Sampling is introduced as a way to reduce token costs in Chain-of-Thought reasoning by truncating reasoning traces without significant loss in accuracy.
MASLab: A Unified and Comprehensive Codebase for LLM-based Multi-Agent Systems
MASLab is a unified codebase that integrates over 20 LLM-based multi-agent system methods to provide a standardized environment for research and evaluation.
Amazon Announces Multibillion-Dollar Data Center in Missouri
Amazon is building a multibillion-dollar data center in Missouri.
Cohere's First Model for Developers
Cohere releases its first AI model specifically tailored for developers.
Reviews have become expensive, rewrites have become cheap
An exploration of the shifting cost dynamics between reviewing existing code versus rewriting it, especially in the context of AI.
Humanity isn't ready for the coming intelligence explosion
A speculative discussion on humanity's readiness for a potential intelligence explosion.
The 90-year-old idea behind JEPA models: Canonical Correlation Analysis
An analysis of the role of Canonical Correlation Analysis in the development of JEPA models.