We propose a novel computational framework for analyzing electroencephalography (EEG) time series using methods from stringology, the study of efficient algorit...
We are open‑sourcing SkyDiscover, a modular framework for AI‑driven algorithm discovery. Framework Overview SkyDiscover decomposes the discovery loop into four...
!OpenAI logohttps://9to5google.com/wp-content/uploads/sites/4/2023/03/openai-logo-2.jpg?quality=82&strip=all&w=1600 OpenAI announced that it’s rolling out an up...
We dream of a future where point clouds from all domains can come together to shape a single model that benefits them all. Toward this goal, we present Utonia, ...
Embodied Conversational Agents (ECAs) aim to emulate human face-to-face interaction through speech, gestures, and facial expressions. Current large language mod...
Classifier-Free Guidance (CFG) has emerged as a central approach for enhancing semantic alignment in flow-based diffusion models. In this paper, we explore a un...
Many essential manipulation tasks - such as food preparation, surgery, and craftsmanship - remain intractable for autonomous robots. These tasks are characteriz...
Achieving autonomous and versatile whole-body loco-manipulation remains a central barrier to making humanoids practically useful. Yet existing approaches are fu...
The ability to conduct and learn from interaction and experience is a central challenge in robotics, offering a scalable alternative to labor-intensive human de...
The visual world offers a critical axis for advancing foundation models beyond language. Despite growing interest in this direction, the design space for native...
Human mobility trajectories are widely studied in public health and social science, where different demographic groups exhibit significantly different mobility ...
Mobile devices are frequent targets of eCrime threat actors through SMS spearphishing (smishing) links that leverage Domain Generation Algorithms (DGA) to rotat...
Feedforward geometric foundation models achieve strong short-window reconstruction, yet scaling them to minutes-long videos is bottlenecked by quadratic attenti...
We present DuoMo, a generative method that recovers human motion in world-space coordinates from unconstrained videos with noisy or incomplete observations. Rec...
The numerical simulation of convection-dominated transient transport phenomena poses significant computational challenges due to sharp gradients and propagating...
The accelerating adoption of language models (LMs) as agents for deployment in long-context tasks motivates a thorough understanding of goal drift: agents' tend...
AI algorithms for imperfect-information games are typically compared using performance metrics on individual games, making it difficult to assess robustness acr...
Autoregressive decoding is bottlenecked by its sequential nature. Speculative decoding has become a standard way to accelerate inference by using a fast draft m...
Generative artificial intelligence (AI) offers scalable support for formative feedback, yet most AI-generated feedback relies on task-specific rubrics authored ...
Language models deployed in online communities must adapt to norms that vary across social, cultural, and domain-specific contexts. Prior alignment approaches r...
Unified multimodal models have recently demonstrated strong generative capabilities, yet whether and when generation improves understanding remains unclear. Exi...
We investigate geometric regularization strategies for learned latent representations in encoder--decoder reduced-order models. In a fixed experimental setting ...
Selecting the number of clusters remains a fundamental challenge in unsupervised learning. Existing criteria typically target a single ``optimal'' partition, of...
While deep neural networks (DNNs) have achieved remarkable performance in tasks such as image recognition, they often struggle with generalization, learning fro...
Large Language Models (LLMs) demonstrate potentials for automating scientific code generation but face challenges in reliability, error propagation in multi-age...
The electric vehicle routing problem with time windows (EVRPTW) extends the classical VRPTW by introducing battery capacity constraints and charging station dec...
!https://9to5mac.com/wp-content/uploads/sites/6/2026/02/chatgpt-app-icon-light.jpg?quality=82&strip=all&w=1600 OpenAI has released an update to ChatGPT that it...
Physics-Informed Neural Networks (PINNs) have been recognized as a mesh-free alternative to solve partial differential equations where physics information is in...
Real-time proactive agentic system, capable of modeling Human State of Mind, using foundation EXG model and text embeddings model, running fully offline on the ...
Contrastive steering has been shown as a simple and effective method to adjust the generative behavior of LLMs at inference time. It uses examples of prompt res...
Agentic language models operate in a fundamentally different safety regime than chat models: they must plan, call tools, and execute long-horizon actions where ...
Today, we’re releasing an update to ChatGPT’s most‑used model that makes everyday conversations more consistently helpful and fluid. GPT‑5.3 Instant delivers mo...
CDD, or Contamination Detection via output Distribution, identifies data contamination by measuring the peakedness of a model's sampled outputs. We study the co...
As large language models (LLMs) advance their mathematical capabilities toward the IMO level, the scarcity of challenging, high-quality problems for training an...
Reasoning is the ability to integrate internal states and external inputs in a meaningful and semantically consistent flow. Contemporary machine learning (ML) s...
Reasoning is the ability to integrate internal states and external inputs in a meaningful and semantically consistent flow. Contemporary machine learning (ML) s...
Universal embodied intelligence demands robust generalization across heterogeneous embodiments, such as autonomous driving, robotics, and unmanned aerial vehicl...
Current benchmarks for code agents primarily assess narrow, repository-specific fixes, overlooking critical real-world challenges such as cross-repository reaso...
Omni-modal large language models (omni LLMs) have recently achieved strong performance across audiovisual understanding tasks, yet they remain highly susceptibl...
Automated industrial optimization modeling requires reliable translation of natural-language requirements into solver-executable code. However, large language m...
The mycelial network of prompt engineering is an invisible, underground flow of proprietary techniques between companies, through employee movement, shared tool...
The way we build software is changing fast. AI is no longer a “someday” tool. It’s reshaping how we plan, write, review, and ship code right now. As products ev...
Join us on March 11 for “Debugging the Future: Strategies for Validating World Models and Action‑Conditioned Video” workshop with Nick Lotz from Voxel51 – regis...
If you've ever had to do a systematic literature review — the kind where you manually search databases, download dozens of PDFs, read each one, and paste findin...
The Honesty Gap in LLM Benchmarks In the relentless race toward artificial general intelligence, the industry has become obsessed with a dangerous proxy for in...
Enterprise engineering organizations produce high-volume, heterogeneous telemetry from version control systems, CI/CD pipelines, issue trackers, and observabili...
Local class imbalance and data heterogeneity across clients often trap prototype-based federated contrastive learning in a prototype bias loop: biased local pro...
Endor Labs Launches AURI Endor Labs, the application‑security startup backed by more than $208 million in venture funding, today launched AURI, a platform that...
