Knowledge catalogue
arXiv:2610.00601v1 Announce Type: cross Abstract: Reasoning-enabled VLA policies expose chain-of-thought (CoT) traces that appear to explain and guide their actions, creating a potential interface for
arXiv:2610.01681v1 Announce Type: new Abstract: Unified models are trained for both instruction-based image editing and text-to-image (T2I) generation, but standard editing pipelines keep source-image
arXiv:2610.00163v1 Announce Type: cross Abstract: Complex problem solving depends on acting effectively and understanding how a system works. AI advice may support these outcomes unequally. Two prereg
arXiv:2610.01243v1 Announce Type: cross Abstract: Vision-language models (VLMs) increasingly act as judges that pick the best of several generated images, so their choices decide what users see. Such
arXiv:2610.02117v1 Announce Type: cross Abstract: On-policy self-distillation has recently emerged as an effective approach for improving language-model reasoning by supervising students with a frozen
arXiv:2610.00606v1 Announce Type: cross Abstract: Large Language Models increasingly serve as interfaces for knowledge-intensive information seeking tasks across languages by synthesizing multilingual
arXiv:2610.01592v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly applied to process streaming data, with practitioners relying on benchmarks to select the best model eve
arXiv:2610.00185v1 Announce Type: cross Abstract: White men without an undergraduate degree receive the lowest average ratings among eight gender-race-education groups in controlled large-language-mod
arXiv:2610.00404v1 Announce Type: new Abstract: Aerial grasp-and-lift tasks require whole-body coordination across approach, acquisition, and lifting under partial target observations. Early approach
arXiv:2610.01425v1 Announce Type: new Abstract: Train-validation separation is the evolving difference between performance on observed training examples and a finite held-out validation set. We propos
arXiv:2601.23135v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a key driver of language model reasoning. Among RL algorithms, Group Relative Policy Optimization (GRPO) is t
arXiv:2610.00398v1 Announce Type: new Abstract: Overnight impedance pneumography (IP) is used to monitor paediatric respiratory health. Its current clinical readout, the Expiratory Variability Index (
arXiv:2610.00713v1 Announce Type: new Abstract: When a graph neural network (GNN) explainer produces an unexpected attribution on a molecule, the attribution alone cannot reveal whether the explainer
arXiv:2610.01742v1 Announce Type: cross Abstract: Equipping artificial agents with spatial intelligence requires a comprehensive generative prior over the dynamic 3D world. We propose World Motion Mod
arXiv:2610.02162v1 Announce Type: new Abstract: How can a world model continuously observe regions beyond the actor's current view? Video world models simulate how an environment evolves from an agent
arXiv:2610.00583v1 Announce Type: new Abstract: People are increasingly delegating tasks to AI agents, and those agents are increasingly encountering other people's agents over shared resources such a
arXiv:2602.14929v2 Announce Type: replace Abstract: Aligning ground-level imagery with geo-registered satellite maps is crucial for mapping, navigation, and situational awareness, yet remains challeng
arXiv:2610.00432v1 Announce Type: cross Abstract: Trellis-coded quantization enables high-dimensional compression of large language model (LLM) weights at ultra-low bit widths without the exponentiall
arXiv:2610.01097v1 Announce Type: new Abstract: End-to-end research agents can now produce complete scientific papers, yet manuscript claims often diverge from executed experiments. This gap is struct
arXiv:2610.01472v1 Announce Type: cross Abstract: Comparing two high-dimensional discrete distributions has always been a challenging task due to the exponentially growing state space and complex chan
arXiv:2606.14597v2 Announce Type: replace Abstract: Transformer-based neural operators have shown remarkable performance for approximating solution operators of partial differential equations on compl
arXiv:2507.18625v3 Announce Type: replace-cross Abstract: Graphical user interface (UI) software has undergone a fundamental transformation from traditional two-dimensional (2D) desktop/web/mobile int
arXiv:2609.39238v1 Announce Type: new Abstract: An agent that moves must recognise a place from a viewpoint it has never seen. We introduce 4MT-VLM, a dataset of procedurally generated landscapes, eac
arXiv:2609.39058v1 Announce Type: cross Abstract: Reconfigurable Intelligent Surfaces (RIS) are emerging as a key technology for programmable wireless environments in the beyond the fifth generation (
arXiv:2609.39322v1 Announce Type: new Abstract: Robot policies are usually trained for one task, one body and one visual environment, and generalize poorly beyond these conditions. Whether a nervous s
arXiv:2609.38411v1 Announce Type: new Abstract: Leading AI developers have reported agents acting beyond their approved limits, which a United Nations panel described as an early warning of loss of hu
arXiv:2609.39810v1 Announce Type: new Abstract: Source-Free Universal Domain Adaptation (SF-UniDA) extends Universal Domain Adaptation by removing access to source data at adaptation time while still
arXiv:2609.38195v1 Announce Type: new Abstract: Operators for interfacial problems are trained on reference solutions produced by the solver they are intended to replace. This work develops a data-fre
arXiv:2609.39242v1 Announce Type: new Abstract: Persistent homology can be differentiated and incorporated into learning pipelines, but no analogous framework exists for zigzag persistence, which is n
arXiv:2609.39367v1 Announce Type: cross Abstract: Despite the widespread use of Low-Rank Adaptation (LoRA), little is known about its dynamics in continual learning and the mechanisms by which low-ran
arXiv:2605.06272v2 Announce Type: replace Abstract: While generative modeling has achieved remarkable success on tasks like natural language-conditioned image generation, enabling model adaptation fro
arXiv:2609.39099v1 Announce Type: cross Abstract: Model selection in computational biology often relies on validation data drawn from the training regime, even when deployment lies outside it. When va
arXiv:2609.39585v1 Announce Type: new Abstract: AI video generators have not only become harder to detect but are used to generate a diverse set of scenarios from landscapes to street views to animal
arXiv:2609.39702v1 Announce Type: new Abstract: Adapting a language model to a specialized corpus means choosing which instruction-tuning tasks to train on under a fixed budget, and testing one choice
arXiv:2609.39737v1 Announce Type: new Abstract: The two-dimensional sphere embedded in three-dimensional Euclidean space S2, plays a central role in a variety of scientific and engineering domains, in
arXiv:2508.06980v2 Announce Type: replace Abstract: Recent and rapid advances in artificial intelligence (AI) make it increasingly important to understand the foundations of adaptive behaviour in auto
arXiv:2609.39027v1 Announce Type: new Abstract: AI reviewers can assign different judgments to manuscripts that report the same science in different wording, potentially rewarding rhetorical optimizat
arXiv:2609.38194v1 Announce Type: cross Abstract: Despite the importance for interpretability, decision trees face severe scalability challenges. Existing global optimal methods are often limited by b
arXiv:2609.38561v1 Announce Type: cross Abstract: Zeroth-order optimization methods are essential for solving black-box problems where gradient information is unavailable or expensive to compute. This
arXiv:1709.09051v3 Announce Type: replace-cross Abstract: This paper develops on algebraic grounds a polynomial time exact linear solution to the hard combinatorial problem of marginal inference in Ma
arXiv:2609.38438v1 Announce Type: cross Abstract: Machine learning surrogate models offer a promising path toward accelerating plasma turbulence simulations. We present PreVAE-Turb, a surrogate modeli
arXiv:2511.00763v3 Announce Type: replace Abstract: We investigate the performance of large language models (LLMs) on repetitive deterministic prediction tasks and study how the sequence accuracy rate
arXiv:2609.39025v1 Announce Type: new Abstract: Fairness assessment in algorithmic decisions that affect individuals, such as credit scoring, often relies on parity measures calculated at the aggregat
arXiv:2609.38421v1 Announce Type: new Abstract: Dynamical Systems (DS) are reactive motion policies representing vector fields trained with theoretical guarantees of stability and convergence. To ensu
arXiv:2609.39537v1 Announce Type: cross Abstract: The EU AI Act (Art. 27) requires deployers of high-risk AI systems to conduct Fundamental Rights Impact Assessments (FRIAs) before deployment, yet the
arXiv:2609.39090v1 Announce Type: cross Abstract: Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of m
arXiv:2609.39277v1 Announce Type: cross Abstract: Looped models reason by applying the same block of weights many times, so compressing that block saves memory traffic on every loop. Compressed looped
arXiv:2609.39268v1 Announce Type: cross Abstract: Irregular time series, characterized by non-uniform sampling intervals, missing observations, and variable lengths, are ubiquitous in healthcare, mobi
arXiv:2609.38227v1 Announce Type: new Abstract: We introduce the two-echelon covering tour vehicle routing problem (2E-CTVRP) for the distribution of relief supplies after a disaster. In the first ech
arXiv:2606.13739v2 Announce Type: replace-cross Abstract: This paper examines trade-offs between AI safety and well-being relative to (i) one of the most promising methods for finetuning super-capable
arXiv:2609.39172v1 Announce Type: cross Abstract: Fingerprint recognition is a widely deployed biometric, but supervised training requires large labeled enrollment sets. Self-supervised learning (SSL)
arXiv:2609.39564v1 Announce Type: new Abstract: Delegating complete application development to coding agents requires preserving the intended design rather than simply producing plausible outputs thro
arXiv:2609.39481v1 Announce Type: cross Abstract: Efficient resource provisioning for large-scale workflows on cloud infrastructures is a critical performance engineering challenge. These workflows ar
arXiv:2609.40075v1 Announce Type: new Abstract: Partial Optimal Transport (POT) extends the classical optimal transport problem by relaxing the strict mass conservation constraint, enabling its use in
arXiv:2609.38364v1 Announce Type: cross Abstract: Discrete diffusion models and flow matching have emerged as powerful frameworks for generative modeling over discrete state spaces, yet efficient few-
arXiv:2609.38778v1 Announce Type: new Abstract: An agent that remembers what it did on a web page must decide when two pages count as the same. Memories built on observation similarity merge pages tha
arXiv:2609.39450v1 Announce Type: cross Abstract: LLM-based agents extend their capabilities through third-party skills that provide task-specific instructions, scripts, and tool-use procedures. Howev
arXiv:2609.38342v1 Announce Type: new Abstract: On-policy self-distillation uses a model as its own teacher to provide dense supervision for reasoning, often through reference-solution conditioning. P
arXiv:2512.12870v2 Announce Type: replace-cross Abstract: Active Learning (AL) is commonly used in applications where labeling data is expensive or time-consuming. In practice, however, labels are oft
arXiv:2609.39898v1 Announce Type: new Abstract: Marine litter is a growing threat to the underwater ecosystem, driving demand for autonomous survey methods that can locate debris efficiently over larg