Knowledge catalogue
arXiv:2609.36289v1 Announce Type: cross Abstract: Prompts are the primary mechanism for directing the behavior of large language models (LLMs). Yet the internal structure and causal hierarchy of promp
arXiv:2609.38173v1 Announce Type: new Abstract: We study robotic in-context learning (ICL), an emerging paradigm that enables robots to infer and execute tasks from visual demonstrations. Despite its
arXiv:2609.37603v1 Announce Type: cross Abstract: A common safeguard for a data pipeline is redundant computation: derive each published number by two routes built on different technology and refuse t
arXiv:2609.36707v1 Announce Type: new Abstract: Legal contracts contain ambiguities that expose enterprises to financial and legal risks. Some ambiguities allow flexible interpretation without trigger
arXiv:2609.36144v1 Announce Type: new Abstract: Electronic health records provide irregular observations of latent patient states that evolve continuously over time. Recent autoregressive models condi
arXiv:2609.37684v1 Announce Type: new Abstract: Adaptive Cruise Control (ACC) systems are typically calibrated for an average driver, often resulting in a mismatch between vehicle behavior and individ
arXiv:2603.25869v2 Announce Type: replace-cross Abstract: Self-supervised image denoising methods have traditionally relied on architectural constraints, pseudo-pair constructions, or specialized loss
arXiv:2609.36577v1 Announce Type: cross Abstract: Audio large language models (ALLMs) can reason about the content of audio recordings to perform complex tasks. However, these capabilities usually col
arXiv:2609.36001v1 Announce Type: cross Abstract: Federated learning (FL) in healthcare remains challenging, as the overhead of rebuilding governance guarantees for every collaboration stops most proj
arXiv:2508.13009v5 Announce Type: replace Abstract: Recent advances in interactive video generations have demonstrated diffusion model's potential as world models by capturing complex physical dynamic
arXiv:2609.36810v1 Announce Type: new Abstract: Video world models aim to predict future content from an observed scene while following prescribed camera motion. Real-world scene evolution is determin
arXiv:2609.37374v1 Announce Type: new Abstract: Reinforcement learning (RL) has recently delivered substantial gains in multimodal reasoning, opening a promising route for fine-grained visual percepti
arXiv:2609.37750v1 Announce Type: cross Abstract: Pulmonary embolism (PE) is a leading cause of cardiovascular mortality, yet the real-world performance of FDA-cleared AI detection models remains inco
arXiv:2609.36903v1 Announce Type: cross Abstract: End-to-end full-duplex speech models have brought open-source machine conversation closer to human-like interaction, yet existing systems remain limit
arXiv:2609.38089v1 Announce Type: cross Abstract: Ship structural vibrations contribute to noise, fatigue, and equipment damage, while dynamic-compliance topology optimization can produce pathological
arXiv:2506.03911v2 Announce Type: replace Abstract: Points-based rewards programs are a prevalent way to incentivize customer loyalty. In theory, the effective design of these programs is shaped by tw
arXiv:2609.36442v1 Announce Type: cross Abstract: Continual learning enables vision systems to adapt to ever-changing data distributions. Despite significant advances, existing approaches fail to capt
arXiv:2602.03915v2 Announce Type: replace-cross Abstract: Tokens are discrete representations that allow modern deep learning to scale by transforming high-dimensional data into sequences that can be
arXiv:2609.37809v1 Announce Type: cross Abstract: Predicting canopy height from medium-resolution satellite imagery is a common and scalable approach for assessing the condition of the world's forests
arXiv:2609.36607v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) offers a promising non-contact solution for heart rate monitoring, yet its real-world robustness is fundamentally lim
arXiv:2609.36969v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) is a state-of-the-art technique for 3D scene rendering, offering high efficiency and excellent visual quality. However, bec
arXiv:2609.37681v1 Announce Type: new Abstract: Long-horizon robotic tasks are vulnerable to unexpected environmental changes that can render planned actions ineffective or unsafe. To address this, ro
arXiv:2507.21135v2 Announce Type: replace Abstract: We demonstrate how Quantum Cognition Machine Learning (QCML) encodes data as quantum geometry. In QCML, features of the data are represented by lear
arXiv:2501.03598v2 Announce Type: replace-cross Abstract: Knowledge graphs have proven successful in integrating heterogeneous data across various domains. However, there remains a noticeable dearth o
arXiv:2609.36850v1 Announce Type: new Abstract: Generative content is increasingly entering the production and dissemination of news, transforming fake news from manually fabricated or simply manipula
arXiv:2609.37560v1 Announce Type: new Abstract: Grinding and sanding are fundamental processes in industrial robotic surface finishing. However, physical trials are expensive and consume workpieces, m
arXiv:2609.37361v1 Announce Type: new Abstract: Operations research supports decision-making in domains such as energy, economics, and healthcare. Solving operations research problems typically begins
arXiv:2609.36929v1 Announce Type: new Abstract: Recent event-based depth estimation methods successfully transfer geometric priors from vision foundation models via cross-modal distillation. However,
arXiv:2609.36417v1 Announce Type: new Abstract: Relational in-context learning (ICL) uses labeled support examples and their linked relational context to predict labels for new queries. This creates a
arXiv:2609.37139v1 Announce Type: new Abstract: 3D content generation technology has significantly advanced the work of designers, as well as the 3D printing and gaming industries. However, it remains
arXiv:2609.36968v1 Announce Type: new Abstract: Unsupervised tabular anomaly detection (TAD) aims to identify anomalous rows in tabular data using normal training samples. While conventional methods r
arXiv:2609.36209v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as knowledge bases (KBs) due to the vast amount of knowledge they acquire during pre-training. While
arXiv:2609.36230v1 Announce Type: new Abstract: We study the dynamical behavior of tokens in transformers from a control-theoretic perspective. Our model includes the feed-forward layer present after
arXiv:2609.37772v1 Announce Type: new Abstract: Diffusion and flow-matching Vision-Language-Action (VLA) policies generate action chunks through iterative denoising, incurring substantial inference la
arXiv:2609.37360v1 Announce Type: new Abstract: Defect detection systems for industrial condition monitoring can only be relied upon if they are validated, yet defective samples are rare and, for a sp
arXiv:2609.37078v1 Announce Type: new Abstract: Time series modeling increasingly demands high-quality supervision, yet target observations remain scarce - exogenous inputs are broadly available, but
Getting artificial intelligence into production has become the real test for enterprises. As the proof-of-concept phase ends, harder questions about cost, data and control are taking its place. That s
arXiv:2506.17316v2 Announce Type: replace-cross Abstract: This paper proposes a family of graph metrics for measuring distances between graphs of different sizes. The proposed metric family defines a
arXiv:2510.26184v2 Announce Type: replace Abstract: Public resource allocation involves distributing resources, including urban infrastructure, energy, and transportation, which are typically limited
arXiv:2510.05382v2 Announce Type: replace Abstract: Tactile sensing is critical for enhancing manipulation precision and versatility, but its adoption in robotic hands remains limited due to high sens
arXiv:2609.31759v1 Announce Type: cross Abstract: Domain Generalization (DG) aims to develop models that remain robust to conditions unseen during training. While DG has been systematically studied in
arXiv:2609.34982v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown great promise for robotic manipulation by mapping multi-modal semantics to physical actions. However, thi
arXiv:2609.32530v1 Announce Type: new Abstract: Difference-in-means steering requires activations recorded while a model shows the desired behavior, which a sandbagging model withholds by deliberately
arXiv:2609.32099v1 Announce Type: new Abstract: The craft of weaving, where different materials are interlaced, has tremendous potential for creating active and functional systems for use in soft robo
arXiv:2603.12057v3 Announce Type: replace Abstract: Coarse-guided visual generation, which synthesizes fine visual samples from degraded or low-fidelity coarse references, is essential for various rea
arXiv:2609.34594v1 Announce Type: new Abstract: Accurate capture of non-cooperative targets is critical. In an attempt to tackle this intractable challenge, an aerial gripper system integrated with a
arXiv:2609.32106v1 Announce Type: new Abstract: The global transition to a cashless economy has placed credit cards as the key element of digital transactions, acclaimed for their easy use, speed, and
arXiv:2609.33748v1 Announce Type: new Abstract: World-action models (WAMs) couple predictive visual modeling with action generation, typically relying on iterative denoising with a fixed denoising ste
As least year's DevDay, this is what OpenAI said agents would look like. This is before OpenClaw & self-organizing swarms, so this entire approach was scraped soon after: 1) AI is evolving quite quick
arXiv:2506.08140v2 Announce Type: replace Abstract: Despite long-standing efforts in accelerating scientific discovery with AI, building AI co-scientists remains challenging due to limited high-qualit
arXiv:2609.34270v1 Announce Type: new Abstract: Interactive robot planning requires robots to infer and execute human intentions from natural language instructions that are often ambiguous, incomplete
BREAKING: Elon Musk was sitting next to President Trump at the White House Super Intelligence luncheon. Here is President Trump’s full address: • Praised the technology leaders as some of the world’s
arXiv:2609.32167v1 Announce Type: new Abstract: Counterfactual prediction estimates an individual's outcome under an alternative intervention given their factual observations. Such outcomes are genera
arXiv:2609.31754v1 Announce Type: new Abstract: Vision-based tactile sensors are a popular solution for capturing rich contact surface geometry. However, to obtain high-detail contact surface normals
Data connectivity and integration firm CData Software Inc. today introduced Connect AI Gateway, a platform designed to control how artificial intelligence agents choose models, use tools and access co
arXiv:2609.32026v1 Announce Type: cross Abstract: Physical systems evolve continuously in time, yet their states are typically observed only at discrete times. Generating trajectories consistent with
arXiv:2609.32436v1 Announce Type: cross Abstract: Mechanisms for generating GNN explanations are crucial for building trust and mitigating biases in Graph Neural Networks (GNNs), especially in high-st
arXiv:2609.31786v1 Announce Type: cross Abstract: Maximum likelihood estimation of Markov deterioration hazard models for infrastructure asset management is sensitive to the numerical conditioning of
arXiv:2602.16917v2 Announce Type: replace Abstract: Modern vision models increasingly rely on rich semantic representations that extend beyond class labels to include descriptive concepts, attributes,
arXiv:2609.32513v1 Announce Type: new Abstract: Handwritten mathematical expression recognition (HMER) refers to the task of recognizing and converting handwritten mathematics into a parsable markup l