Knowledge catalogue
arXiv:2605.23652v1 Announce Type: new Abstract: On a 300-persona life-simulation benchmark, pcsp achieves compositional zero-shot persona identification up to 17x above chance, Spearman rho approx 0.7
arXiv:2605.23668v1 Announce Type: cross Abstract: Although large language model (LLM) conversational systems process millions of multi-turn dialogues daily, they remain fundamentally reactive: they re
arXiv:2605.23409v1 Announce Type: cross Abstract: In human computer interaction, real-time detection and classification of dynamic hand gestures is challenging as: 1) the system must run in a real-tim
arXiv:2508.14311v2 Announce Type: replace-cross Abstract: There is an increasing need to enforce multiple, often competing, measures of fairness within automated decision systems. The appropriate weig
arXiv:2602.08927v3 Announce Type: replace-cross Abstract: We study the problem of online monotone density estimation, where density estimators must be constructed in a predictable manner from sequenti
arXiv:2512.15436v2 Announce Type: replace-cross Abstract: We introduce an extension of the partitioned local depth (PaLD) algorithm that is adapted to online applications such as semi-supervised predi
Only Restore Britain can save Britain Right. Just so we’re all clear. Farage and Reform tried to put me in prison because I backed the mass deportation of Pakistani child rapists and their foreign wiv
arXiv:2605.23434v1 Announce Type: new Abstract: Approximate inference over inducing variables is the central computational bottleneck of Deep Gaussian Processes (DGPs). Existing methods either fit an
arXiv:2605.23297v1 Announce Type: new Abstract: AI-enabled services deployed in critical digital infrastructure are subject to governance obligations spanning transparency, accountability, fairness, a
arXiv:2605.23037v1 Announce Type: new Abstract: Data-driven modeling is becoming central to multiphase transport, electronics cooling, acoustic diagnostics, and thermal-fluid digital twins, but progre
OpenAI announced a strategic partnership with Grupo Folha and Grupo UOL, major Brazilian media companies, to integrate their content into OpenAI's AI models and products. The partnership enables OpenA
arXiv:2605.23657v1 Announce Type: new Abstract: Skills, i.e., structured workflow instructions distilled for large language models (LLMs), are becoming an increasingly important mechanism for improvin
OpenStudio is a hybrid AI router that combines local model inference with cloud-based model access through OpenRouter, a unified API providing access to hundreds of AI models through a single endpoint
arXiv:2605.23145v1 Announce Type: cross Abstract: Individual fairness, the notion that 'similar individuals should be treated similarly,' provides a strong and flexible fairness guarantee for algorith
arXiv:2512.19184v2 Announce Type: replace-cross Abstract: This paper presents novel generalization bounds for vector-valued neural networks and deep kernel methods, focusing on multi-task learning thr
arXiv:2605.23712v1 Announce Type: cross Abstract: Reconstructing flow fields from sparse measurements is a fundamental problem in fluid mechanics with broad implications for modeling, control, and des
arXiv:2605.23726v1 Announce Type: new Abstract: We prove optimal sampling bounds achieving (1pmarepsilon)-relative error for a broad class of Lipschitz continuous classification loss functions under v
arXiv:2605.23689v1 Announce Type: new Abstract: RaNNDy is a randomized neural network architecture for the data-driven approximation of transfer operators associated with complex dynamical systems. Th
arXiv:2605.23066v1 Announce Type: cross Abstract: In a landscape of high-performance distributed ML systems, JAX has emerged as a framework of choice. However, JAX's modular design philosophy leaves i
arXiv:2604.07796v2 Announce Type: replace-cross Abstract: In this paper, we study the problem of mean estimation under 1-bit communication constraints. We propose a novel adaptive mean estimator based
arXiv:2605.23019v1 Announce Type: new Abstract: Deploying language-model agents in production often requires substantial compute and human effort to tune prompts, parsers, validators, and other compon
arXiv:2605.23219v1 Announce Type: cross Abstract: Time series forecasting plays a central role in many real-world applications and has been extensively studied. Most existing approaches rely on determ
arXiv:2605.23296v1 Announce Type: new Abstract: Long-horizon LLM agents accumulate growing conversation histories that eventually exceed the model's context window. Context compaction via LLM-based su
arXiv:2605.23402v1 Announce Type: cross Abstract: Effectively modeling non-stationary dynamics in probabilistic multivariate time series(MTS) forecasting requires balancing expressiveness with robustn
arXiv:2605.23074v1 Announce Type: new Abstract: The emergence of Large Reasoning Language Models (LRMs) has paved the way for tackling complex reasoning tasks through test-time scaling by generating l
arXiv:2605.23559v1 Announce Type: cross Abstract: Whole-slide image visual question answering (WSI-VQA) frames pathology as an extreme-context search problem: to answer a free-form clinical query, a s
People are often confused that I am against the framing of 'tool AI' This is hands down the best post explaining (some of) the issues with the term. Give it a read! Many in AI safety advocacy argue th
people in glass houses should not throw stones, Zuck Mark Zuckerberg says Apple's lack of innovation since the iPhone will lead to its decline 'They haven't really invented anything great in a while.
arXiv:2605.23883v1 Announce Type: cross Abstract: Despite remarkable progress in Multimodal Large Language Models (MLLMs), these models still struggle with fine-grained understanding tasks. In this wo
arXiv:2605.23478v1 Announce Type: cross Abstract: Accurate crop yield prediction is crucial for sustainable agriculture and global food security. While existing methods are predominantly developed for
arXiv:2605.23108v1 Announce Type: cross Abstract: AI-assisted code review tools typically operate as generic 'expert reviewer' agents, producing homogeneous findings regardless of the analysis type ne
arXiv:2605.23771v1 Announce Type: cross Abstract: Virtual photography asks an agent to enter a prepared 3D scene with no preselected camera pose or reference image, infer a suitable shot from scene in
arXiv:2506.20537v3 Announce Type: replace Abstract: Efficient simulation of Laser Powder Bed Fusion (LPBF) is crucial for process prediction due to the lasting issue of high computational cost associa
arXiv:2502.07489v2 Announce Type: replace Abstract: State-of-the-art methods for forecasting irregularly sampled time series with missing values predominantly rely on just four datasets and a few smal
arXiv:2605.23128v1 Announce Type: new Abstract: Currently, Vision-Language-Action (VLA) models have become the most adopted paradigm for robotic manipulation for its great potential for task generaliz
arXiv:2605.23902v1 Announce Type: new Abstract: Most practical high-resolution text-to-image systems, including latent diffusion and autoregressive models, perform generation in a compact latent space
arXiv:2605.22856v1 Announce Type: cross Abstract: Channel foundation models assume access to fully observed channels, an assumption that fails in deployment. We introduce PilotWiMAE, a self-supervised
arXiv:2605.23027v1 Announce Type: new Abstract: Recent research has demonstrated the potential of reinforcement learning in effective multi-robot collaboration, particularly in social dilemmas where r
arXiv:2503.06684v3 Announce Type: replace Abstract: Recent advances in diffusion-based text-to-image generation have demonstrated promising results through visual condition control. However, existing
arXiv:2605.23531v1 Announce Type: new Abstract: Low-light images exhibit severe noise, contrast loss, and semantic ambiguity, making enhancement a joint problem of denoising and detail recovery. We pr
PixlStash 1.3 is a Python-based image management and tagging web app that improves grid loading performance and introduces JoyCaption integration for AI-powered image captioning. The update adds suppo
arXiv:2507.05311v2 Announce Type: replace-cross Abstract: In this paper, we propose PLACE (Prompt Learning for Attributed Community Search), an innovative graph prompt learning framework for ACS. Enli
Plugins can also affect the empty state of the new menu - the latest datasette-agent adds a form for kicking off a new agent conversation - live demo (if you sign in with GitHub) on https://agent.data
arXiv:2605.23856v1 Announce Type: new Abstract: Robot policy learning benefits from world-action models that capture environment dynamics, but pixel-level prediction entangles dynamics with nuisance f
arXiv:2605.22891v1 Announce Type: new Abstract: Evaluation in scientific reconstruction is dominated by pointwise metrics - RMSE, MAE, per-event resolution - under the implicit assumption that lower e
arXiv:2605.23168v1 Announce Type: cross Abstract: When practitioners fine-tune LLMs on unvetted datasets, an adversary can exploit the data supply chain through task-level poisoning: inserting a small
arXiv:2603.21437v2 Announce Type: replace Abstract: Transformer-based embedding models frequently exhibit geometric pathologies, such as anisotropy and length-induced representation collapse, which ca
Pope Leo XIV warned of the risks of AI and unconstrained technological power in his first major papal document released on Monday. Magnifica Humanitas is the pope's manifesto on 'safeguarding the huma
Pope Leo has warned that the artificial intelligence revolution is being driven primarily by profit motives rather than ethical considerations, characterizing this as a form of 'idolatry of profit.' T
Pope Leo XIV today issued an encyclical that contains an extensive discussion of artificial intelligence and its risks. The approximately 43,000-word document is entitled “Magnifica Humanitas,” which
New York Times: Pope Leo XIV presents Magnifica humanitas, his encyclical on AI, calling for AI regulation, protection for children against hypersexualized AI images, and more — The document marks a p
arXiv:2605.23170v1 Announce Type: cross Abstract: Position-controlled evaluation is standard for retrieval tasks such as Needle-in-a-Haystack and RULER, but mainstream reasoning benchmarks do not cont
arXiv:2605.23522v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become an effective way to improve prompt alignment and perceptual quality in diffusion and flow-matching generators.
arXiv:2605.22855v1 Announce Type: cross Abstract: Personalized pricing negotiations are a challenging testbed for LLM agents because successful interaction does not guarantee profitable decision makin
arXiv:2605.23603v1 Announce Type: cross Abstract: We introduce the Preisach Attention Layer (PAL), a novel sequence modelling architecture grounded in the classical Preisach hysteresis operator from m
Product >> Brand 2 years ago: 'Elon destroyed the Tesla brand globally! It'll never recover!' Today: #1 selling EV in California: Tesla Model Y #1 selling EV in the U.S.: Tesla Model Y #1 selling EV i
arXiv:2603.02897v2 Announce Type: replace Abstract: Recent advances in generative image compression (GIC) have delivered remarkable improvements in perceptual quality. However, many GICs rely on large
arXiv:2601.15224v2 Announce Type: replace-cross Abstract: Estimating task progress requires reasoning over long-horizon dynamics rather than recognizing static visual content. While modern Vision-Lang
arXiv:2605.04118v2 Announce Type: replace-cross Abstract: Recent advances in de novo protein binder design have enabled increasing experimental validation, yet reported in silico metrics remain diffic
arXiv:2605.23351v1 Announce Type: new Abstract: We study adversarial multi-armed bandits with and without delayed feedback under a safety-aware goal: achieving minimax-optimal worst-case regret while