Knowledge catalogue
arXiv:2607.05420v1 Announce Type: cross Abstract: This study examines how alternative systems of scholarly representation identify and characterize broad public administration (PA) and artificial inte
arXiv:2511.04177v2 Announce Type: replace Abstract: Personal AI agents are increasingly deployed in shared environments, where their actions affect not just the primary user they are assisting, but by
arXiv:2607.06166v1 Announce Type: new Abstract: Prediction markets aggregate dispersed beliefs into prices that act as probabilistic forecasts of uncertain events. Classical theory establishes a clean
arXiv:2607.06155v1 Announce Type: cross Abstract: Modern sequence models are increasingly deployed as agents that interleave token generation with calls to external tools. We give an exact, architectu
arXiv:2606.20023v2 Announce Type: replace-cross Abstract: As LLM agents increasingly select tools autonomously, their choices among tools with different privileges become safety-relevant. However, pri
arXiv:2607.05752v1 Announce Type: cross Abstract: Search-augmented language models can use external evidence to compensate for limitations in parametric knowledge, but search is not uniformly benefici
arXiv:2607.05691v1 Announce Type: new Abstract: Every chemical language model reading SMILES begins with a tokenizer, yet the field has inherited byte-pair encoding (BPE) from natural language with li
arXiv:2607.05574v1 Announce Type: cross Abstract: Artificial intelligence increasingly mediates consequential decisions in healthcare, law, and public services, and the field has responded with an ext
arXiv:2607.05412v1 Announce Type: cross Abstract: STEM education faces challenges in personalization and interdisciplinary integration. AI technology has brought new possibilities, but the mechanisms
arXiv:2607.06023v1 Announce Type: new Abstract: Visual SLAM is a well-established technology utilized in a wide range of real-world applications. However, its performance still degrades under challeng
arXiv:2607.05735v1 Announce Type: cross Abstract: Infinite-width limits are a standard way to reason about neural networks, but it is not automatic that the limiting learner has the same complexity-th
arXiv:2607.06234v1 Announce Type: new Abstract: Generating CT volumes from MRI and CBCT can improve treatment planning in adaptive radiotherapy while avoiding additional radiation exposure. However, d
arXiv:2607.06461v1 Announce Type: cross Abstract: While recent Large Language Model (LLM)-based Text-to-Speech (TTS) systems have achieved remarkable naturalness, they predominantly rely on implicit e
arXiv:2607.06438v1 Announce Type: cross Abstract: Retargeting human object interaction demonstrations to physics based simulation requires reproducing not only body motion but also the object motion a
arXiv:2607.06163v1 Announce Type: cross Abstract: Foundation Models for Electronic Health Records (FEMRs) are pretrained on large-scale structured patient data, enabling them to convert longitudinal p
arXiv:2607.06114v1 Announce Type: cross Abstract: Diffusion and flow matching models generate high-quality samples, but their ODE samplers often need tens to hundreds of neural function evaluations (N
arXiv:2607.06424v1 Announce Type: new Abstract: X-ray fluorescence (XRF) spectroscopy is a key modality for material analysis in cultural heritage. However, automated learning from XRF spectra remains
arXiv:2502.09696v3 Announce Type: replace Abstract: Large Multimodal Models (LMMs) exhibit shortfalls when interpreting images and, by some measures, have poorer spatial cognition than young children
arXiv:2511.03078v3 Announce Type: replace Abstract: Tactile sensing plays a key role in enabling dexterous and reliable robotic manipulation, but realizing this capability requires substantial calibra
arXiv:2607.04898v1 Announce Type: new Abstract: We study 3D point cloud reconstruction from multiple partially observed 2D projections. Given two or more projections of an unknown 3D point cloud, toge
arXiv:2211.15590v2 Announce Type: replace Abstract: Analyzing the behavior of complex interdependent networks requires complete information about the network topology and the interdependent links acro
arXiv:2607.03190v1 Announce Type: cross Abstract: Scenario-based transportation analysis specifies future assumptions through aggregate population targets, whereas generative population synthesis mode
arXiv:2607.04184v1 Announce Type: new Abstract: Market manipulation is the dubious practice of manipulating stock prices in order to make a quick profit, which truly degrades confidence on trading pla
arXiv:2604.06025v2 Announce Type: replace Abstract: The performance of legged robots depends strongly on both mechanical design and control, motivating co-design approaches that jointly optimize these
arXiv:2607.01469v2 Announce Type: replace Abstract: Agentic Video Question Answering (VideoQA) systems invoke tools during inference, but their tool libraries are fixed, so recurring procedures are re
arXiv:2607.03256v1 Announce Type: new Abstract: Few-step distilled diffusion students cut text-to-image inference from ~50 to 1-8 network evaluations, but the quality gap is usually summarised by a si
arXiv:2607.04450v1 Announce Type: cross Abstract: Integral codes like the Accident Source Term Evaluation Code (ASTEC) are powerful tools to study the physics of Severe Accidents (SAs) in nuclear reac
arXiv:2607.03739v1 Announce Type: cross Abstract: We release a benchmark and failure-mode-aware evaluation framework for grounded QA under coordinated retrieval poisoning. The framework partitions rea
arXiv:2607.03659v1 Announce Type: cross Abstract: Relational databases (RDBs) are the primary data infrastructure in many enterprises, yet recent deep learning methods designed for RDBs have been eval
arXiv:2607.04574v1 Announce Type: cross Abstract: For LLM agents, supervised fine-tuning is not only about teacher labels' quality, but also about which interaction contexts those labels condition on.
arXiv:2607.03871v1 Announce Type: new Abstract: Minimum maximum mean discrepancy (MMD) estimation has emerged as a robust and likelihood-free alternative to maximum likelihood estimation for parameter
arXiv:2607.02670v1 Announce Type: new Abstract: Electroencephalography (EEG) offers a noninvasive approach for examining neurophysiological correlates of dimensional psychopathology, yet systematic ev
arXiv:2504.11907v3 Announce Type: replace Abstract: Autonomous exploration of cluttered environments requires efficient exploration strategies that guarantee safety against potential collisions with u
arXiv:2607.03298v1 Announce Type: cross Abstract: Foundation models for Earth systems have so far been trained primarily on physical climate and weather data, with limited representation of the human
arXiv:2607.03385v1 Announce Type: cross Abstract: Policy learning has received substantial attention with the goal of learning policies from observational data for decision-making. A majority of work
arXiv:2607.03945v1 Announce Type: new Abstract: Remote sensing imagery plays a crucial role in evaluating regional transportation capacity. However, existing segmentation datasets often lack diversity
arXiv:2607.03131v1 Announce Type: cross Abstract: Modern video surveillance systems generate far more video streams than human operators can effectively monitor, making automated analysis essential fo
arXiv:2607.05222v1 Announce Type: new Abstract: Charts and images appear together throughout scientific publications, yet most computational work does not characterize their coherence. We argue that a
arXiv:2607.03503v1 Announce Type: new Abstract: Graph-based semi-supervised learning (SSL) propagates a few labels over a similarity graph by minimizing a Dirichlet-type energy. The standard quadratic
arXiv:2607.04518v1 Announce Type: new Abstract: Gait is a distinctive behavioral characteristic that enables non-invasive individual identification without requiring physical interaction with an anima
arXiv:2607.04367v1 Announce Type: new Abstract: In the development of cooking robots, mastering the task of cutting is crucial. A significant challenge lies in the diverse properties of food, which ne
arXiv:2607.04680v1 Announce Type: new Abstract: Grain growth is governed by the reduction in grain boundary energy and exhibits well-established statistical scaling laws. Developing data-driven surrog
arXiv:2607.04056v1 Announce Type: cross Abstract: Modern supply chains span diverse operational environments, ranging from e-commerce distribution networks to customized production-to-order manufactur
arXiv:2607.02944v1 Announce Type: cross Abstract: We propose PRECEDE, a precedent-guided co-scientist for side-effect-aware drug redesign that revises a parent compound to mitigate a specified side ef
arXiv:2607.02782v1 Announce Type: cross Abstract: Predictions by machine learning (ML) and artificial intelligence (AI) models are often received skeptically unless they are paired with intelligible e
arXiv:2511.07109v2 Announce Type: replace-cross Abstract: Nonnegative matrix factorization (NMF) is a linear dimensionality reduction technique for nonnegative data, with applications such as hyperspe
arXiv:2602.02908v2 Announce Type: replace-cross Abstract: Diffusion models trained on different, non-overlapping subsets of a dataset often produce strikingly similar outputs when given the same noise
arXiv:2607.04689v1 Announce Type: cross Abstract: Safe operation of autonomous vehicles in dense urban traffic depends on perception and planning that remain reliable when onboard sensing is degraded.
arXiv:2607.04436v1 Announce Type: cross Abstract: Natural language requirements (NLRs) are essential for bridging communication gaps among diverse stakeholders in software development. However, the in
arXiv:2603.00819v2 Announce Type: replace-cross Abstract: This paper surveys recent developments at the intersection of operator learning, statistical learning theory, and approximation theory. First,
arXiv:2607.03815v1 Announce Type: cross Abstract: For compact convex sets L,K subset R^n, denote by lambda_K(L) the smallest size of a homothet of K that contains L. We define a measure of symmetry ba
arXiv:2408.05124v2 Announce Type: replace-cross Abstract: Image sensors are fundamental to many intelligent systems, allowing visual perception and AI-driven decision-making. However, their integrity
arXiv:2607.02941v1 Announce Type: new Abstract: Multi-product kitting delivery imposes significant challenges for real-time scheduling in hybrid manufacturing systems that integrate processing and ass
arXiv:2607.02753v1 Announce Type: cross Abstract: Neuromorphic controllers for size, weight, and power-constrained systems require neural architectures that are both energy-efficient and interpretable
arXiv:2607.03600v1 Announce Type: cross Abstract: Adversarial robustness in Unsupervised Domain Adaptation (UDA) remains a significant challenge due to noisy pseudo labels and inherent distributional
arXiv:2607.03664v1 Announce Type: new Abstract: The Gaussian Error Linear Unit is usually motivated as the expected output of an input-dependent stochastic Bernoulli gate. This work gives a complement
arXiv:2503.23650v2 Announce Type: replace Abstract: Reinforcement learning (RL), with its ability to explore and optimize policies in complex, dynamic decision-making tasks, has emerged as a promising
arXiv:2509.08269v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly integrated with evolutionary computation to support optimization tasks. This survey primarily fo
arXiv:2507.04136v2 Announce Type: replace Abstract: This survey offers a comprehensive foundation on the integration of RL with language models, highlighting prominent algorithms such as Proximal Poli
arXiv:2204.02803v2 Announce Type: replace-cross Abstract: Sign language recognition from monocular video or 2D pose sequences is challenging, both because 3D information must be inferred from 2D obser