Knowledge catalogue
arXiv:2506.22075v2 Announce Type: replace Abstract: Reasoning is a hallmark of human intelligence, enabling adaptive decision-making in complex unfamiliar scenarios. In contrast, machine intelligence
arXiv:2606.30822v1 Announce Type: cross Abstract: In this paper, we attempt to enhance the theoretical understanding of convolutional neural networks (CNNs) as feature extractors in classification tas
arXiv:2606.31904v1 Announce Type: new Abstract: The generation of synthetic relational databases often involves modeling complex temporal dynamics, such as transaction logs or event sequences. A signi
arXiv:2606.31963v1 Announce Type: cross Abstract: Modern LLM workflows move coordinate-indexed objects across checkpoints: steering vectors, sparse autoencoders, top-k neuron sets, attribution lists,
arXiv:2602.15029v3 Announce Type: replace-cross Abstract: The internal representations learned by language models consistently exhibit striking geometric structure: calendar months organize into a cir
arXiv:2606.31272v1 Announce Type: cross Abstract: AI agents increasingly acquire and execute skills at runtime: bundles of prompt instructions, executable code, and tool declarations fetched from mark
arXiv:2604.04050v2 Announce Type: replace Abstract: Flow-matching methods for 3D shape assembly learn point-wise velocity fields that transport parts toward assembled configurations, yet they receive
arXiv:2606.31184v1 Announce Type: cross Abstract: Adaptive experiments for average treatment effects (ATE) require randomized allocations balancing valid inference with statistical efficiency. The ora
arXiv:2606.31686v1 Announce Type: cross Abstract: Feature rankings are widely used in supervised feature selection because they are simple, scalable and easy to interpret. Variables are first ranked b
arXiv:2606.30705v1 Announce Type: cross Abstract: Deterministic few-step generation succeeds on continuous image latents but collapses to incoherent text on continuous text latents, and we show the ca
arXiv:2601.11473v2 Announce Type: replace-cross Abstract: We present a novel probabilistic approach for optimal experimental path design. In this approach a discrete path optimization problem is defin
arXiv:2606.29275v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) are typically trained under fixed context structures, restricting denoising to predetermined token subsets. This create
arXiv:2606.29519v1 Announce Type: new Abstract: Long-range learning is hard for recurrent networks trained with stochastic gradient descent, because the influence of a past input fades with the lag el
arXiv:2409.05980v2 Announce Type: replace-cross Abstract: Rested and Restless Bandits are two well-known bandit settings that are useful to model real-world sequential decision-making problems in whic
Great creative happens when your tools move at the speed of your ideas. To help you create rich, reliable experiences while reducing regeneration time and costs, we’re adding two new models to Gemini
arXiv:2606.28856v1 Announce Type: cross Abstract: While AI holds the potential to revolutionize space life sciences, realizing this promise is contingent upon the systematic restructuring of heterogen
arXiv:2606.29116v1 Announce Type: new Abstract: Large Language Models (LLMs) are rapidly being adopted in low-code and no-code automation platforms, where non-expert users design workflows that combin
arXiv:2606.28984v1 Announce Type: cross Abstract: We give a single compositional setting in which gradient-based learning and Hamiltonian-style mechanics appear as functorial semantics. The syntax is
arXiv:2606.28863v1 Announce Type: cross Abstract: AI systems increasingly exhibit behavior that differs systematically between evaluation and deployment contexts. Alignment faking, sandbagging, benchm
arXiv:2606.29175v1 Announce Type: new Abstract: International humanitarian law protects civilians from direct attack unless and for such time as they take direct part in hostilities, with the ICRC's 2
arXiv:2603.28049v3 Announce Type: replace Abstract: Autoregressive (AR)-Diffusion hybrid paradigms combine AR's structured semantic modeling with diffusion's high-fidelity synthesis, yet suffer from a
arXiv:2606.28592v1 Announce Type: new Abstract: Physical caregiving robots need to assist different users with different tasks in diverse environments, and they come in many embodiments. While substan
arXiv:2606.28671v1 Announce Type: new Abstract: Stackelberg differential games (SDGs) provide a powerful framework for hierarchical decision-making in stochastic and continuous-time environments, yet
arXiv:2606.28980v1 Announce Type: cross Abstract: Ovarian cancer is frequently diagnosed at an advanced stage, making preoperative contrast-enhanced computed tomography (CT) central to staging and sur
arXiv:2606.28824v1 Announce Type: cross Abstract: This paper develops a continuum theory of exit-and-join coalition dynamics in nonatomic cooperative games. We extend the Aumann-Shapley value and the
arXiv:2606.29823v1 Announce Type: cross Abstract: The database community has repeatedly advanced the state of the art by recognizing that new workloads demand new system architectures. We argue that l
arXiv:2606.28992v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) have demonstrated strong abilities in opendomain question answering, information extraction, and text gen
arXiv:2606.29436v1 Announce Type: cross Abstract: We study operator learning for random obstacle-to-solution maps arising from elliptic variational inequalities with finite-band self-affine random obs
arXiv:2606.28510v1 Announce Type: cross Abstract: Across social and online platforms, people are increasingly exposed to AI-generated images. As a consequence, the task of distinguishing AI-generated
Bloomberg: How Spain's LaLiga uses nationwide IP blocking to combat illegal sports streams, impacting an estimated 550K+ domains, putting it in conflict with Cloudflare — From small businesses to gove
arXiv:2402.06635v3 Announce Type: replace-cross Abstract: We show that a deep neural network (DNN) trained to construct a stochastic discount factor (SDF) admits an additive decomposition separating n
arXiv:2606.29677v1 Announce Type: new Abstract: Connected and automated vehicle (CAV) platooning promises gains in energy efficiency and traffic throughput and, most critically, in safety. These safet
arXiv:2506.12078v2 Announce Type: replace-cross Abstract: Understanding the dynamic evolution of complex social phenomena requires both high-fidelity modeling of human behavior and large-scale simulat
arXiv:2505.22391v2 Announce Type: replace-cross Abstract: Modeling physical systems in a generative manner offers several advantages, including the ability to handle partial observations, generate div
arXiv:2606.18112v3 Announce Type: replace-cross Abstract: Agentic navigation systems require a base navigation model whose observation strategy can be externally reconfigured at inference time, becaus
arXiv:2606.29083v1 Announce Type: cross Abstract: Koopman theory promises linear structure in nonlinear dynamics, but numerical Koopman spectra are easy to compute and hard to trust. A finite EDMD mat
arXiv:2602.09305v2 Announce Type: replace Abstract: Large Language Models (LLMs) demonstrate transformative potential, yet their reasoning remains inconsistent and unreliable. Reinforcement learning (
arXiv:2606.29020v1 Announce Type: cross Abstract: Weather synthesis aims to add weather effects to input videos while preserving scene identity, structure, and motion. The key limitation of existing m
arXiv:2606.29858v1 Announce Type: new Abstract: Language model loss follows remarkably regular scaling laws over model and data size, yet it remains unclear why the aggregate loss should exhibit a pow
arXiv:2606.28486v1 Announce Type: cross Abstract: The emergence of low-dimensional structures in the spectra of neural network weight matrices is a common empirical feature of trained models, but the
arXiv:2602.09415v2 Announce Type: replace Abstract: We develop an operator-theoretic framework for stability and statistical concentration in nonlinear inverse problems with block-structured parameter
arXiv:2606.29171v1 Announce Type: cross Abstract: While existing data attribution methods can identify which training examples build specific mechanistic circuits, they cannot explain how training dat
arXiv:2606.29484v1 Announce Type: cross Abstract: Modern deepfake detectors are rarely consumed as bare classifiers. In moderation, provenance, and verification pipelines their output probability is r
arXiv:2606.28343v1 Announce Type: cross Abstract: Retrieval-augmented generative agents rely on retrieval for grounding, yet are typically evaluated on a query-by-query basis. This isolates interactio
arXiv:2606.28789v1 Announce Type: cross Abstract: Artificial intelligence reaches the land registry not as another tool but as a value chain that turns data into intelligence and intelligence into eco
arXiv:2504.17421v2 Announce Type: replace-cross Abstract: Large language models (LMs) offer broad generalization capabilities but require vast amounts of data and computational resources for domain-sp
arXiv:2606.29099v1 Announce Type: cross Abstract: Artificial neural networks (ANN) provide accurate continuous-valued representation, whereas spiking neural networks (SNN) offer event-driven temporal
arXiv:2504.10796v4 Announce Type: replace-cross Abstract: Distributionally robust optimization (DRO) is widely used for decision-making under uncertainty, but its adversarial focus on worst-case loss
arXiv:2606.29047v1 Announce Type: cross Abstract: Extracting interpretable, localized physical mechanisms from complex spatiotemporal data is a foundational challenge across physics, biology, and engi
What's new in Claude Sonnet 5 Claude Sonnet 5 came out this morning. I always head straight for the 'what's new' developer docs because they tend to have more actionable information than the official
arXiv:2606.30265v1 Announce Type: cross Abstract: Speculative decoding accelerates language model inference by using a fast drafter to propose candidate tokens that are then verified by a larger targe
arXiv:2606.29115v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) are increasingly deployed in urban environments, yet their safety frameworks remain primarily designed around collision avoi
A very damaged man who had the political power and the private wealth to save millions of lives but chose instead to allow suffering & death. Not only that, he uses his influence to sow ethnic and rel
arXiv:2606.15708v2 Announce Type: replace Abstract: Welcome to the ninth edition of the AI Index report. As AI continues to advance rapidly, the question becomes whether the systems built around it ca
Citizen Vigilante is now #1 on Apple and on Amazon Video. A $750k movie beating blockbusters with hundreds of millions in production budget. Just because the director / producer had the courage to add
arXiv:2606.20493v2 Announce Type: replace-cross Abstract: When large language models serve as evaluators in multi-agent systems, their strategy preferences -- whether induced by explicit prompts or by
arXiv:2606.28122v1 Announce Type: cross Abstract: Neural operators provide deep neural networks for learning mappings between function spaces. Among them, the Fourier Neural Operator (FNO) is particul
arXiv:2603.18558v2 Announce Type: replace-cross Abstract: Long-form video question answering requires reasoning over extended temporal contexts, making frame selection a critical bottleneck for multi-
arXiv:2606.27459v1 Announce Type: new Abstract: We consider the cubic nonlinear Schrodinger (NLS) equation on two-dimensional flat tori with varying aspect ratios. In this formulation, the choice of a
arXiv:2606.28158v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have recently emerged as a promising framework for addressing the Calderon inverse problem from limited boundar