Full-text search across 12498 articles. Combine with topic and date filters; results sorted by relevance.
Turing Award winner Yann LeCun, who left Meta last year, has founded AMI Labs in Paris to build world models based on the Joint Embedding Predictive Architecture (JEPA), backed by $1 billion in investment and compute fro…
A METR study finds that AI has dramatically accelerated the rate of reported cyber vulnerabilities in 2026 compared with 2025, contributed modestly to mathematics research with arXiv submissions doubling in some areas, b…
A breakthrough in AI concept representation uses Laguerre Geometry to precisely map concepts as regions rather than points, reshaping interpretability. Researchers have developed Geometric Lens, a method that offers unpr…
New research shows depth is more important than width in neural networks for approximating analytic functions, challenging traditional thinking. The study derived new approximation rates expressed as O(N^{-CL^τ}), where …
Researchers have found that the multimodal language model LLaVA 1.6 can replicate six of seven categories of naming errors seen in stroke-induced aphasia, matching real-world clinical data in 97.8% of configurations, tho…
Google has unveiled the Magic Pointer, a feature powered by its Gemini AI that reads screens in real-time and suggests actions, aiming to redefine user interaction with Googlebook laptops. The system uses natural languag…
NSNQuant, a calibration-free vector quantization method developed by researchers, promises up to 3x throughput gains for language model inference by compressing the key-value cache without relying on calibration datasets…
Git-Assistant, a new tool combining large language models with automated planning, aims to simplify complex git operations by translating natural language commands into precise actions. A systematic evaluation shows the …
A new approach using sparse autoencoders (SAEs) is revolutionizing out-of-distribution (OOD) detection by extracting interpretable features from intermediate neural network layers, achieving record performance on OOD det…
SPARC-Net, a novel neural network architecture, claims to overcome the limitations of Physics-Informed Neural Networks (PINNs) in solving stiff and shock-dominated partial differential equations, achieving error reductio…
A new framework grounded in generalized extrinsic information transfer (GEXIT) functions redefines diffusion model training by defining cross-entropy as an integral of local information-theoretic derivatives along the no…
AI model performance increasingly depends on data quality rather than compute power, as researchers shift focus from scaling model size to refining datasets. This trend affects real-world applications like autonomous veh…
Researchers introduced ReRanking Preference Optimization (RRPO), a method that uses reinforcement learning from LLM feedback to improve reranker relevance for AI-generated answers, outperforming strong baselines like Ran…
Researchers developed a two-stage AI pipeline that estimates wind conditions and uses reinforcement learning to improve drone trajectory tracking by 48% in turbulent winds. The method, tested in simulations, outperforms …
Researchers introduced two CUTLASS-based kernels that accelerate the SwiGLU activation function in large language models by up to 2.47x on NVIDIA H100 GPUs, shifting workloads from memory-bound to compute-bound and achie…
Researchers introduced K9-Bench, a benchmark evaluating AI's ability to understand canine behavior through 5,000 question-answer pairs across 907 videos. Current AI models struggle with subtle animal interactions, highli…
Researchers introduced a Gibbs algorithm that simplifies posterior sampling in Bayesian inversion, offering reliable convergence guarantees and computational efficiency. The method, verified through numerical simulations…
Consumer technology is shifting from reactive healthcare to preventive medicine by using wearable sensors and AI to monitor physiological signals continuously. Devices like smartwatches and smart rings track heart rate, …
Microsoft has open-sourced its ML Video Codec (MLVC), a machine learning-based video compression technology designed to improve efficiency and quality. The release on GitHub includes the codec's source code, models, and …
Yann LeCun presented a talk on world models as the next step in AI, emphasizing their role in enabling machines to learn and reason like humans. The talk highlighted how world models could lead to breakthroughs in roboti…