Cubit: Token Mixer with Kernel Ridge Regression
arXiv:2605.06501v2 Announce Type: replace-cross Abstract: Since its introduction in 2017, the Transformer has become one of the most widely adopted architectures in modern deep learning. Despite exten
Knowledge catalogue
arXiv:2605.06501v2 Announce Type: replace-cross Abstract: Since its introduction in 2017, the Transformer has become one of the most widely adopted architectures in modern deep learning. Despite exten
Curated AI ecosystems are becoming the defining architecture of enterprise AI. The shift does not announce itself with spectacle. It shows up in procurement decisions, architecture diagrams and the sl
current agent systems coordinate through conversations and workflows. Active Graph explores what happens when agents coordinate through evolving shared state instead this proposal suggests that long-r
arXiv:2605.19484v1 Announce Type: cross Abstract: While GUI agents have made significant progress in web navigation and basic operating system tasks, their capabilities in professional creative workfl
arXiv:2605.19690v1 Announce Type: new Abstract: Navigation Foundation Models (NFMs) trained on large cross-embodied datasets have demonstrated powerful generalizability in various scenarios. Adopting
arXiv:2605.19210v1 Announce Type: new Abstract: Convexity is a fundamental geometric prior that underlies many natural and man-made structures, yet remains challenging to impose effectively in end-to-
arXiv:2605.18810v1 Announce Type: cross Abstract: Speculative decoding accelerates LLM inference by having a small drafter propose tokens that a larger target model verifies in parallel. Recent diffus
arXiv:2605.20036v1 Announce Type: new Abstract: Ride-hailing platforms like DiDi Chuxing operate in highly dynamic environments where balancing driver supply and passenger demand is critical. Although
arXiv:2605.19887v1 Announce Type: cross Abstract: Current Physical AI (PAI) relies heavily on closed-loop visual-servoing pipelines, whose perception and planning stages may become computationally int
arXiv:2605.18868v1 Announce Type: cross Abstract: While vision and multimodal foundation models underpin critical tasks from perception to complex reasoning, they remain highly vulnerable to adversari
Data centers aren’t stealing your water. Even if the total water draw of data centers triples by 2030, they’d require just 8% of the water consumed by American golf courses. @dodgeblake interviewed @A
arXiv:2602.09259v2 Announce Type: replace Abstract: In robot-assisted minimally invasive surgery (RMIS), reduced haptic feedback and depth cues increase reliance on expert visual perception, motivatin
arXiv:2511.13588v2 Announce Type: replace-cross Abstract: Model Predictive Control (MPC) is a powerful framework for optimal control but can be too slow for low-latency applications. We present a data
arXiv:2511.12158v3 Announce Type: replace Abstract: Research in bioacoustics, neuroscience, and linguistics often uses birdsong as a proxy to acquire knowledge across diverse areas. This requires audi
arXiv:2605.18892v1 Announce Type: cross Abstract: Federated learning (FL) enables collaborative learning of computer vision models, where privacy and regulatory constraints prevent centralizing data a
Databricks partnered with the Good and Virtue Foundation to leverage data and technology solutions that connect medical volunteers with critical health services across 72 countries. The collaboration
Bot and agent trust management company DataDome SAS today launched Priority Protect, a virtual waiting room product designed to sort human shoppers, authorized artificial intelligence agents and malic
Release: datasette-agent-charts 0.1a1 More color! Bar and waffle charts without a color column are shaded by magnitude with a sequential color scheme; color columns holding text values use the observa
arXiv:2605.19605v1 Announce Type: new Abstract: Forests worldwide are increasingly threatened by climate change and disturbances such as fire, pests, and pathogens, creating an urgent need for scalabl
arXiv:2605.18773v1 Announce Type: cross Abstract: Traditional facility management often relies on centralized decision-making structures that limit stakeholder participation, leading to misalignment w
arXiv:2605.19737v1 Announce Type: cross Abstract: Digital Twin (DT) technology holds immense potential for surgical planning and personalized medicine. However, generating interactive, patient-specifi
arXiv:2605.19099v1 Announce Type: new Abstract: We introduce DecisionBench, a benchmark substrate for emergent delegation in long-horizon agentic workflows. The substrate fixes a task suite (GAIA, tau
arXiv:2601.12707v2 Announce Type: replace Abstract: Estimating the unknown reward functions driving agents' behaviors is of central interest in inverse reinforcement learning and game theory. To tackl
arXiv:2605.19270v1 Announce Type: new Abstract: Large language models can deceive by subtly manipulating truthful information -- omitting key facts, shifting focus, or obscuring meaning -- making such
arXiv:2603.29382v2 Announce Type: replace-cross Abstract: Lightweight cryptographic primitives are widely deployed in resource-constrained environments, particularly in Internet of Things (IoT) device
arXiv:2105.00933v3 Announce Type: replace-cross Abstract: The task of efficient automatic music classification is of vital importance and forms the basis for various advanced applications of AI in the
arXiv:2605.19021v1 Announce Type: new Abstract: Deep Graph Neural Networks (GNNs) are essential for capturing complex dependencies in graph-structured data. However, scaling GNNs to depth remains chal
arXiv:2605.19892v1 Announce Type: cross Abstract: Dramatic cost reductions driven by private sector innovations have led to a rapid increase in the number of satellites in orbit and a corresponding su
deepagents v0.6 ships w/ support for code interpreters! these are the perfect happy medium between pure tool execution and heavyweight sandboxes they give your agent an environment where it can... → k
arXiv:2605.19294v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies are typically deployed with asynchronous inference: the robot executes a previously predicted action chunk while
arXiv:2605.18855v1 Announce Type: cross Abstract: Attention Residuals replace standard additive residual connections with learned softmax attention over previous layer outputs, enabling selective cros
arXiv:2605.19557v1 Announce Type: cross Abstract: We study post-hoc Learning to Defer (L2D) through the lens of ideal distributions: divergence-regularized reweightings of the data distribution under
arXiv:2602.00545v2 Announce Type: replace Abstract: The eigenvalue distribution of the Hessian matrix plays a crucial role in understanding the optimization landscape of deep neural networks. Prior wo
arXiv:2605.19797v1 Announce Type: new Abstract: Monocular depth estimation has improved significantly in recent years, driven by increasingly powerful models and large-scale training data. Predicted d
arXiv:2605.19231v1 Announce Type: new Abstract: We introduce DeRegiME -- Deep Regime Mixture of Experts -- a direct multi-horizon probabilistic forecaster that separates latent uncertainty regimes fro
arXiv:2605.18909v1 Announce Type: new Abstract: Any system that models the world under finite representational capacity must compress; any compression entails a prior; and the prior is the system's bi
arXiv:2605.19966v1 Announce Type: cross Abstract: Optimization-based adversarial suffixes can jailbreak aligned large language models (LLMs) while remaining fluent, weakening static and windowed perpl
arXiv:2605.19228v1 Announce Type: cross Abstract: Large Language Models have achieved strong performance on reasoning tasks with objective answers by generating step-by-step solutions, but diagnosing
Did we ever learn what model won gold at the IMO from OpenAI? It was a year ago and it was called an unreleased internal general purpose model back then. Has GPT-5.5 Pro Extended caught up with whatev
arXiv:2509.21196v3 Announce Type: replace-cross Abstract: Accurately forecasting the long-term evolution of turbulence represents a grand challenge in scientific computing and is crucial for applicati
arXiv:2511.01526v2 Announce Type: replace Abstract: Multiple-choice cloze questions are commonly used to assess linguistic proficiency and comprehension. However, generating high-quality distractors r
arXiv:2509.19707v2 Announce Type: replace-cross Abstract: Copulas are a fundamental tool for modelling multivariate dependencies in data, forming the method of choice in diverse fields and application
arXiv:2605.19621v1 Announce Type: cross Abstract: Deep generative models have emerged as state-of-the-art for solving inverse problems, but applying them to inverse problems for PDEs, like electrical
arXiv:2509.12288v2 Announce Type: replace-cross Abstract: Domestic Violence (DV) is a pervasive public health problem characterized by patterns of coercive and abusive behavior within intimate relatio
arXiv:2605.18793v1 Announce Type: cross Abstract: Accurate spatiotemporal pattern analysis is critical in fields such as urban traffic, meteorology, and public health monitoring. However, existing met
arXiv:2506.12218v2 Announce Type: replace-cross Abstract: Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architec
arXiv:2605.19186v1 Announce Type: new Abstract: Two decades ago, the Semantic Web Services community was asked how agents with different ontological commitments could discover, compose, and invoke web
arXiv:2601.16823v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit remarkable capabilities, yet it remains unclear to what extent these reflect sophisticated recall or genu
arXiv:2605.18999v1 Announce Type: new Abstract: Muon and related normalized optimizers decouple the choice of update direction from the choice of step scale, but their practical performance remains se
arXiv:2605.18993v1 Announce Type: cross Abstract: Task vector composition has emerged as a promising paradigm for editing pre-trained models, enabling model merging through addition and unlearning thr
arXiv:2605.19779v1 Announce Type: new Abstract: We adapt split conformal prediction and adaptive conformal inference (ACI) to continuous AI agent evaluation, providing distribution-free coverage guara
arXiv:2605.19256v1 Announce Type: new Abstract: Distribution Matching Distillation (DMD) provides an effective distribution-level correction for few-step generation, while relying on an auxiliary fake
arXiv:2512.16856v2 Announce Type: replace Abstract: AI safety and alignment research has predominantly been focused on methods for safeguarding individual AI systems, resting on the assumption of an e
arXiv:2605.18871v1 Announce Type: cross Abstract: When Large Language Models produce structured outputs such as travel plans, code solutions, or multi-step proofs, individual reasoning steps may appea
arXiv:2605.19029v1 Announce Type: new Abstract: Reliable robotic manipulation requires control policies that can accurately represent and adapt to uncertainty arising from contact-rich interactions. M
arXiv:2602.03139v2 Announce Type: replace Abstract: Distribution matching distillation (DMD) facilitates few-step image generation by aligning a distilled student with a reference multi-step teacher.
arXiv:2602.23622v2 Announce Type: replace-cross Abstract: Significant progress has been made in the field of Instruction-based Image Editing Models (IIEMs). However, while these models demonstrate pla
arXiv:2605.18915v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are vulnerable to jailbreak attacks, which can elicit harmful responses from MLLMs. Many MLLMs support multi-
arXiv:2605.19278v1 Announce Type: cross Abstract: This paper tests whether graph neural networks improve realized volatility forecasts and whether those forecasts improve portfolio performance. Using
arXiv:2605.19688v1 Announce Type: new Abstract: Document manipulation localization models achieve strong performance on public benchmarks yet fail to generalize to operational document workflows. We i