Knowledge catalogue
arXiv:2605.08223v1 Announce Type: new Abstract: Federated techniques such as federated learning and federated analysis have emerged as a powerful paradigm for enabling multi-center research on sensiti
arXiv:2605.06042v2 Announce Type: replace Abstract: Flapping-wing micro aerial vehicles offer quieter and safer operation than rotary-wing drones, yet achieving precise autonomous control of bird-scal
arXiv:2605.10555v1 Announce Type: new Abstract: As AI agents transition from research prototypes to enterprise production systems, the tool interfaces they consume remain rooted in human-oriented CRUD
arXiv:2605.08956v1 Announce Type: new Abstract: A growing body of work pursues AI scientists capable of end-to-end autonomous scientific discovery. This position paper argues that although they alread
arXiv:2605.08764v1 Announce Type: cross Abstract: Deep vision models degrade sharply in low-data regimes, particularly in medical imaging where labeled samples are scarce. We show this arises not mere
arXiv:2605.09190v1 Announce Type: new Abstract: We present AQMP, a novel image codec combining Adaptive Quadtree Refinement with Matching Pursuit. Unlike conventional Matching Pursuit methods that ope
arXiv:2308.13222v3 Announce Type: replace-cross Abstract: We introduce an evidence-driven Bayesian formulation of physics-informed neural networks that enables automatic optimization of loss weights b
arXiv:2605.10822v1 Announce Type: new Abstract: Cyber-physical system (CPS) forecasting models depend on sensor streams with noisy, biased, missing, or temporally misaligned readings, yet standard for
arXiv:2605.08994v1 Announce Type: cross Abstract: The current catalyst discovery and development pipeline for energy-intensive applications like methane conversion remains bottlenecked by expensive tr
arXiv:2605.10586v1 Announce Type: new Abstract: Learning a physical model from video data that can comprehend physical laws and predict the future trajectories of objects is a formidable challenge in
arXiv:2605.10721v1 Announce Type: cross Abstract: Artificial intelligence safety research focuses on aligning individual language models with human values, yet deployed AI systems increasingly operate
arXiv:2505.05707v2 Announce Type: replace Abstract: The integration of AI into daily life has generated considerable attention and excitement, while also raising concerns about automating algorithmic
arXiv:2605.09890v1 Announce Type: cross Abstract: Differentially private stochastic gradient descent (DP-SGD) is a standard approach to privacy-preserving learning based on per-example clipping, subsa
arXiv:2605.08794v1 Announce Type: cross Abstract: Modern generative models can be understood as probability transport from a simple base distribution to a target data distribution. Deterministic trans
arXiv:2602.13759v2 Announce Type: replace Abstract: We study eigendecomposition on SO(n) under streaming observations C_k = C_{sig} + sigma_k^2 I + E_k, where the isotropic background sigma_k^2 I may
arXiv:2605.08104v1 Announce Type: new Abstract: This paper explores the application of the Soft Actor-Critic (SAC) algorithm within a Distributional Reinforcement Learning setting and introduces an im
eBay rejected GameStop's unsolicited 56 billion takeover bid, with eBay's board declaring the offer 'neither credible nor attractive.' The proposal called for purchasing eBay shares at 125 apiece with
arXiv:2604.16838v2 Announce Type: replace-cross Abstract: We present enclawed, a hard-fork hardening framework built on the OpenClaw AI assistant gateway. enclawed targets deployments that need attest
SpaceX's Falcon 9 rocket successfully launched the NROL-172 classified national reconnaissance payload from Space Launch Complex 4E at Vandenberg Space Force Base in California. This mission was condu
arXiv:2605.10302v1 Announce Type: new Abstract: Existing approaches to controllable generation typically rely on fine-tuning, auxiliary networks, or test-time search. We show that flow matching admits
arXiv:2605.09681v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion models adopt a streaming generation framework, enabling long-horizon video generation with real-time responsiveness,
arXiv:2602.16708v3 Announce Type: replace-cross Abstract: Security policy enforcement in contemporary agentic systems predominantly consists of embedding natural-language policies within an agent's sy
arXiv:2605.08712v1 Announce Type: new Abstract: Action-conditioned surgical video generation is a critical yet highly challenging problem for robotic surgery. The core difficulty is that low-dimension
arXiv:2603.04474v2 Announce Type: replace-cross Abstract: Large Language Model-based Multi-Agent Systems (LLM-MAS) are increasingly applied to complex collaborative scenarios. However, their collabora
arXiv:2605.08291v1 Announce Type: cross Abstract: EDA problems are graph-structured, but not all graph-structured problems call for the same GNN computation. We argue that successful GNN-for-EDA metho
arXiv:2605.08143v1 Announce Type: cross Abstract: Large language models encode vast factual knowledge that inevitably becomes outdated or incorrect after deployment, yet retraining is costly prohibiti
arXiv:2602.03677v2 Announce Type: replace Abstract: Modality following is the ability to selectively leverage multimodal contexts based on user instructions. It is fundamental to the safety and reliab
arXiv:2605.10551v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have achieved strong results in molecular property prediction, but polymers present distinct challenges: labeled datasets a
arXiv:2605.09954v1 Announce Type: cross Abstract: Articulated objects used in simulation and embodied AI are typically specified by geometry and kinematic structure, but lack the fine-grained dynamica
arXiv:2605.06394v1 Announce Type: cross Abstract: These lecture notes introduce some topics of classical statistical physics, particularly those that are relevant for neural networks and deep learning
arXiv:2605.08949v1 Announce Type: new Abstract: A central challenge in continual learning for large language models (LLMs) is catastrophic forgetting, where adapting to new tasks can substantially deg
arXiv:2603.28254v2 Announce Type: replace Abstract: Orthogonalized-update optimizers such as Muon improve training of matrix-valued parameters, but existing extensions typically either rescale updates
arXiv:2605.05373v2 Announce Type: replace Abstract: A key capability of intelligent agents is operating under partial observability: reasoning and acting effectively despite missing or incomplete stat
arXiv:2605.08192v1 Announce Type: cross Abstract: Frontier AI safety claims - published assertions that a highly capable general-purpose model is below a threshold of concern, adequately mitigated, or
Announced today at SAP Sapphire — where NVIDIA founder and CEO Jensen Huang joined SAP CEO Christian Klein’s keynote by video — SAP and NVIDIA’s expanded collaboration helps enterprises run specialize
Red Hat Enterprise Linux, the platform underpinning much of enterprise IT, has spent 20 years as the quiet foundation of enterprise computing. Now, as AI moves into production at scale, it’s becoming
arXiv:2605.09565v1 Announce Type: new Abstract: We consider the problem of learning an unknown subset N_ext{target} of a domain in an online setting. In each round t, the learner predicts a set of ite
Sam Altman's personal investments faced increased scrutiny from Republican lawmakers following reporting by The Wall Street Journal in April regarding potential conflicts of interest. The controversy
arXiv:2605.10391v1 Announce Type: cross Abstract: We introduce Phoenix-VL 1.5 Medium, a 123B-parameter natively multimodal and multilingual foundation model, adapted to regional languages and the Sing
arXiv:2605.10310v1 Announce Type: new Abstract: Existing alignment research is dominated by concerns about safety and preventing harm: safeguards, controllability, and compliance. This paradigm of ali
arXiv:2605.10761v1 Announce Type: new Abstract: Cancer screening is a reasoning task. A radiologist observes findings, compares them to prior scans, integrates clinical context, and reaches a diagnost
arXiv:2605.08142v1 Announce Type: cross Abstract: Reasoning in large language models is predominantly evaluated through labeled benchmarks, conflating task performance with the quality of internal inf
SAP SE today introduced at Sapphire 2026, the company’s annual conference, what it calls Autonomous Enterprise, a suite of artificial intelligence tools and agents designed to enhance how humans and A
arXiv:2605.09630v1 Announce Type: new Abstract: Tokenizer-free language models eliminate the tokenizer step of the language modeling pipeline by operating directly on bytes; patch-based variants furth
arXiv:2605.09209v1 Announce Type: cross Abstract: We study optimistic bilevel optimization when the lower-level problem has a non-isolated manifold of minimizers. In this setting, the hyper-objective
arXiv:2605.09345v1 Announce Type: new Abstract: We identify a Selection Plateau phenomenon in one-shot neural network pruning: all rank-monotone weight scorers converge to identical accuracy at fixed
arXiv:2605.10395v1 Announce Type: cross Abstract: We study the information-theoretic limits of learning a one-hidden-layer teacher network with hierarchical features from noisy queries, in the context
arXiv:2605.10500v1 Announce Type: new Abstract: Agent skills today are static artifact: authored once -- by human curation or one-shot generation from parametric knowledge -- and then consumed unchang
arXiv:2605.08693v1 Announce Type: new Abstract: Skills provide an effective mechanism for improving LLM agents on complex tasks, yet in existing agent frameworks, their creation, refinement, and selec
arXiv:2605.08230v1 Announce Type: new Abstract: Background: Fentanyl overdose deaths are still increasing across the U.S. We do not fully understand which county-level social and structural conditions
arXiv:2605.09415v1 Announce Type: new Abstract: The growing integration of AI into cybersecurity is reshaping the balance between attackers and defenders. When access to advanced AI-enabled defence to
If anyone, anywhere builds a superhuman artificial intelligence using present methods, the most likely outcome is catastrophe. There have accordingly been widespread calls for an international agreeme
arXiv:2605.10811v1 Announce Type: cross Abstract: This paper develops a joint spectral radius (JSR) framework for analyzing rank-one deflated Q-value iteration (Q-VI) in discounted Markov decision pro
Databricks announced the general availability of Catalog Commits, a feature that integrates open table formats with open catalog systems to enable versioning and tracking of catalog-level changes. Thi
arXiv:2605.10687v1 Announce Type: new Abstract: Turbulent dynamical systems are characterized by nonlinear interactions and stochastic effects that generate coupled statistical quantities, such as non
arXiv:2510.15995v3 Announce Type: replace-cross Abstract: We study overpricing in a repeated game between two representative agents: a market maker, who controls market liquidity, and a market taker,
arXiv:2605.10601v1 Announce Type: new Abstract: AI deployment in sensitive domains such as health care, credit, employment, and criminal justice is often treated as unsafe to authorize until model int
arXiv:2512.18610v3 Announce Type: replace Abstract: Intuitively, a more deterministic time series should be easier to forecast. However, point-wise loss functions (e.g., MSE and MAE), serving as diffe
arXiv:2605.08541v1 Announce Type: new Abstract: Neural scaling laws approximate a language model's loss as a power-law function of parameter count N and token count D. Following Chinchilla-style compu
arXiv:2605.09965v1 Announce Type: new Abstract: The real world unfolds along a single set of physics laws, yet human intelligence demonstrates a remarkable capacity to generalize experiences from this