Knowledge catalogue
arXiv:2508.19186v2 Announce Type: replace-cross Abstract: Reactive obstacle avoidance methods often cause agents to become trapped in local minima, because they can often only reason one step ahead (i
arXiv:2503.06796v2 Announce Type: replace Abstract: Robot design is a complex and time-consuming process that requires specialized expertise. Gaining a deeper understanding of robot design data can en
arXiv:2607.12954v1 Announce Type: cross Abstract: Engineering use of AI forecasting models requires not only high nominal accuracy but also predictable behavior under uncertain inputs. In photovoltaic
arXiv:2607.11889v1 Announce Type: cross Abstract: Large language models trained on unrestricted internet corpora inevitably embed information from the future, introducing lookahead bias that compromis
arXiv:2607.11975v1 Announce Type: cross Abstract: Current machine unlearning methods predominantly rely on global, coarse-grained intervention strategies. They lack precise pilot signals to guide the
arXiv:2607.12866v1 Announce Type: new Abstract: Reconstruction-based methods are a cornerstone of unsupervised image anomaly detection, but they remain vulnerable to outlier leakage, where standard me
arXiv:2506.21324v3 Announce Type: replace-cross Abstract: Neuromorphic and quantum computing have recently emerged as promising paradigms for advancing artificial intelligence, each offering complemen
arXiv:2607.12161v1 Announce Type: new Abstract: Context-reduction layers for API-based coding agents, including command-output compressors, retrieval rankers, and payload-optimizing proxies, are usual
arXiv:2607.12861v1 Announce Type: cross Abstract: Multi-agent Reinforcement Learning (MARL) holds great potential for robot swarms, but the black-box nature of neural policies complicates strategic an
arXiv:2607.12735v1 Announce Type: new Abstract: Companion work showed the grokking delay is causally the time to form task-structured representations, injectable via a contrastive prior. Here we chara
arXiv:2607.12790v1 Announce Type: new Abstract: Self-evolving agent systems improve by creating, revising, and retiring their own skills, but every such loop rests on a hidden assumption: a reliable e
For years, we’ve built with a clear priority: putting the practical needs of the enterprise first. Long before generative AI dominated the headlines, we were focused on building the global infrastruct
Retail Finance teams are increasingly deploying agentic AI to safeguard omni‑channel margins. These systems automatically monitor sales performance, forecast demand, and adjust pricing or inventory co
Just a reminder that deepseek v3 came out 18 months ago and was considered revolutionary at the time but is basically unusable today There was a fierce debate at the time about vibe coding and the arg
Proactive agents that anticipate user needs and autonomously execute tasks hold great promise as digital assistants, yet the lack of realistic user simulation frameworks hinders their development. Exi
In 2026, the public sector is no longer defending a traditional perimeter. Instead, they are defending a complex web of interconnected trust relationships against adversaries that now operate at machi
How should your security team manage shadow AI? Workloads deployed by developers without formal registration can often evade traditional security scanners, because organizations are reluctant to slow
Grok 4.5 is an AI language model developed by xAI, featuring improvements in reasoning, coding, and multimodal capabilities compared to earlier versions. The model demonstrates enhanced performance ac
Tesla has deployed 10 GWh of industrial energy storage products across Australia, a capacity equivalent to powering approximately 160,000 Tesla Model Y vehicles. This milestone reflects the growing ad
arXiv:2607.07850v1 Announce Type: new Abstract: For seemless control of advanced hand prostheses and augmented reality, accurate and immediate hand gestures recognition is essential. Surface electromy
arXiv:2510.22052v2 Announce Type: replace Abstract: The field of artificial intelligence (AI) has taken a tight hold on broad aspects of society, industry, business, and governance in ways that dictat
arXiv:2607.07761v1 Announce Type: new Abstract: Large language models (LLMs) have emerged as important tools in healthcare, showing growing potential for clinical reasoning and patient care. This surv
arXiv:2607.08297v1 Announce Type: new Abstract: Background and Objective: Quantitative analysis of cell dynamics is central to modern biological research, providing critical insights into immune cell
arXiv:2503.15414v3 Announce Type: replace-cross Abstract: Federated learning seeks to foster collaboration among distributed clients while preserving the privacy of their local data. Traditional feder
arXiv:2607.07962v1 Announce Type: cross Abstract: Inferring latent physical properties from sensory observations is a fundamental challenge in machine perception. Among available sensing modalities, t
arXiv:2504.18235v2 Announce Type: replace Abstract: Event-based cameras are bio-inspired sensors that detect light changes asynchronously for each pixel. They are increasingly used in fields like comp
arXiv:2607.08380v1 Announce Type: new Abstract: An important quantity in the theory of gradient descent (GD) is the sharpness, defined as the largest eigenvalue of the objective Hessian. Classical ana
arXiv:2505.23842v5 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly power search engines and AI assistants that retrieve and summarize content from many sources. By serving a
arXiv:2607.08427v1 Announce Type: cross Abstract: Achieving nanosecond-scale inference latency for deep neural networks (DNNs) has become a primary architectural concern for latency-critical applicati
arXiv:2607.08144v1 Announce Type: cross Abstract: Through-the-wall radar (TWR) human activity recognition (HAR) is important for non-line-of-sight indoor sensing, security monitoring, and emergency re
arXiv:2412.07259v5 Announce Type: replace Abstract: DatalogMTL is a powerful rule-based language for temporal reasoning. Due to its high expressive power and flexible modeling capabilities, it is suit
This post highlights a practical AI agent that operates intuitively without requiring explanation of its underlying mechanics, suggesting it has achieved a user-friendly interface or autonomous functi
arXiv:2607.07972v1 Announce Type: new Abstract: Recent advances in actuation, control and learning have rapidly pushed humanoid robots from a distant vision towards near-term real-world deployment. He
François Chollet observes that agentic coding systems have made dramatic progress over a six-month period, representing a significant shift in the landscape of AI-assisted development. The post reflec
arXiv:2410.06329v4 Announce Type: replace-cross Abstract: Obtaining a reliable estimate of the joint probability mass function (PMF) of a set of random variables from observed data is a significant ob
arXiv:2607.08392v1 Announce Type: cross Abstract: Amortized neural inverse design typically remains closed-world: component choices are fixed vocabulary tokens, coordinate grids are frozen at training
arXiv:2607.08303v1 Announce Type: new Abstract: The problem of learning constant-depth circuits holds profound implications for computational learning theory. In a seminal result, by introducing the l
arXiv:2607.08004v1 Announce Type: new Abstract: Object detection in geospatial scenes, such as satellite and aerial imagery, poses significant challenges due to the varying orientations and densities
arXiv:2512.13997v2 Announce Type: replace-cross Abstract: Existing two-sample testing techniques, particularly those based on choosing a kernel for the Maximum Mean Discrepancy (MMD), often assume equ
arXiv:2607.07857v1 Announce Type: cross Abstract: We build a team of specialized large language-model agents and present an agent-driven workflow for research-level formalization in theoretical physic
arXiv:2607.07907v1 Announce Type: cross Abstract: With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or
arXiv:2512.16558v3 Announce Type: replace Abstract: Clustering is a cornerstone of modern data analysis. Detecting clusters in exploratory data analyses (EDA) requires algorithms that make few assumpt
arXiv:2607.08025v1 Announce Type: new Abstract: While neural PDE solvers have demonstrated significant potential for accelerating engineering simulations, existing architectures remain constrained by
arXiv:2505.16456v3 Announce Type: replace Abstract: Recent advances in 3D content generation have amplified demand for dynamic models that are both visually realistic and physically consistent. Howeve
arXiv:2607.08725v1 Announce Type: cross Abstract: Recent progress in 3D human pose estimation has made markerless recovery of skeletal motion increasingly accurate and scalable. However, most pose est
arXiv:2607.08072v1 Announce Type: new Abstract: End-to-end models that map multimodal inputs directly to future trajectories/maneuvers have emerged as an increasingly prominent research paradigm in au
arXiv:2607.08691v1 Announce Type: cross Abstract: Repository-level code generation requires implementing target functions while accounting for complex cross-file dependencies and project-specific conv
arXiv:2607.08115v1 Announce Type: new Abstract: While global localization using spinning radar has gained attention for its robustness to adverse weather and challenging environments, many studies hav
arXiv:2607.08056v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) have recently achieved substantial progress in natural language generation tasks. Recent research demonstrates that a
arXiv:2601.09071v2 Announce Type: replace Abstract: The existence of multiple, equally accurate models for a given predictive task leads to predictive multiplicity, where a Rashomon set of models achi
arXiv:2603.01119v2 Announce Type: replace-cross Abstract: A fundamental challenge in causal inference with observational data is correct specification of a causal model. When there is model uncertaint
arXiv:2607.08373v1 Announce Type: cross Abstract: Connected vehicles are autonomous cyber-physical systems whose behavior must be continuously monitored during operation to detect deviations from norm
arXiv:2601.02871v3 Announce Type: replace Abstract: Task-oriented proactive dialogue agents play a pivotal role in recruitment, particularly for steering conversations towards specific business outcom
arXiv:2607.08340v1 Announce Type: cross Abstract: Q-learning is a fundamental algorithm in reinforcement learning (RL) for solving discounted Markov decision processes (MDPs) when the transition kerne
arXiv:2607.08161v1 Announce Type: new Abstract: Text-to-SQL is a fundamental task in natural language processing that enables users to interact with structured databases using natural language. While
arXiv:2312.15341v1 Announce Type: cross Abstract: We provide an overview of recent progress in statistical inverse problems with random experimental design, covering both linear and nonlinear inverse
arXiv:2607.08238v1 Announce Type: new Abstract: Recent algorithmic advances have made directed acyclic graph (DAG) structure learning scalable for causal discovery. Yet, the currently available techni
arXiv:2607.08402v1 Announce Type: cross Abstract: Large-scale and diverse datasets are needed to train AI models to take real-time decisions for autonomous vehicles (AVs), an intelligent transportatio
arXiv:2601.01406v2 Announce Type: replace-cross Abstract: Face super-resolution aims to recover high-quality facial images from severely degraded low-resolution inputs, but remains challenging due to
arXiv:2607.07735v1 Announce Type: cross Abstract: Sparse precision matrix estimation provides an interpretable and computationally efficient framework for modeling conditional dependencies in high-dim