Knowledge catalogue
arXiv:2109.02355v2 Announce Type: replace-cross Abstract: The last decade of progress in machine learning (ML), especially the deep learning era, has raised a number of scientific questions that chall
arXiv:2609.07075v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is commonly evaluated by whether the final answer is correct. That test is insufficient: an answer can match its re
arXiv:2505.23215v2 Announce Type: replace-cross Abstract: We propose a framework for generative modeling of continuous-time processes from irregularly and asynchronously recorded data. It is based on
arXiv:2609.09910v1 Announce Type: new Abstract: The small-sample-size (SSS) problem remains a fundamental challenge in machine learning when labeled data are scarce due to cost, accessibility, or ethi
arXiv:2609.10357v1 Announce Type: new Abstract: Time-series foundation models are evaluated almost exclusively on public archives that predate them, so a strong score cannot be separated from having s
arXiv:2609.08016v1 Announce Type: new Abstract: Multi-agent debate, in which several LLMs exchange arguments before answering, is widely assumed to improve answer quality by surfacing genuine disagree
arXiv:2603.25259v2 Announce Type: replace Abstract: Research on mobile manipulation systems that physically interact with humans has expanded rapidly in recent years, opening the way to tasks which co
arXiv:2609.10529v1 Announce Type: new Abstract: We prove the gap-entropy conjecture for fixed-confidence best-arm identification with independent unit-variance Gaussian arms, means in [0,1], and a uni
arXiv:2609.09796v1 Announce Type: new Abstract: The DIRECT algorithm is a deterministic global optimization method known for its versatility and balanced exploration-exploitation strategy. However, DI
arXiv:2609.07719v1 Announce Type: new Abstract: Medical imaging artificial intelligence (AI) is commonly developed as separate mappings from radiographs to diagnostic outputs or from clinical descript
arXiv:2609.09650v1 Announce Type: new Abstract: Reinforcement learning (RL) has demonstrated considerable potential for autonomous driving decision-making. However, its deployment in urban autonomous
arXiv:2609.09986v1 Announce Type: cross Abstract: Consistent submodular maximization studies the tradeoff between solution quality and stability when elements arrive over time. For a monotone submodul
arXiv:2609.06050v1 Announce Type: cross Abstract: For a compact set KsubsetC, let artheta(K) be the infimum of the planar areas of the unit lemniscates of all monic polynomials with zeros in K, allowi
arXiv:2609.10084v1 Announce Type: cross Abstract: Generalized zero-shot learning (GZSL) has emerged as an important paradigm for visual recognition systems that must generalize to classes that were no
arXiv:2609.09547v1 Announce Type: new Abstract: Sample size determination for machine learning (ML) prediction models is challenging because conventional power analysis typically requires the predicto
arXiv:2609.09211v1 Announce Type: cross Abstract: The Davis-Kahan theorem is a fundamental tool in spectral analysis, providing quantitative control over the distance between the eigenspaces of a symm
arXiv:2609.10099v1 Announce Type: new Abstract: Molecule generation has emerged as a powerful computational tool for de novo drug design, enabling the exploration of chemical space beyond the limits o
arXiv:2609.08592v1 Announce Type: new Abstract: Evaluating tool-augmented LLM agents requires diverse, realistic user inputs yet most evaluation frameworks use flat role descriptions ('you are an angr
arXiv:2609.07586v1 Announce Type: new Abstract: Software repositories contain vast amounts of data on code contributions, bug reports, and project activities, yet this information remains challenging
arXiv:2609.10400v1 Announce Type: new Abstract: The coordination of Automated Guided Vehicles (AGVs) in high-density industrial environments represents a critical challenge within Logistics 4.0, as tr
arXiv:2609.06573v1 Announce Type: new Abstract: Recent studies report that automated red-teaming finds more vulnerabilities, at lower cost, than human red-teaming on standard AI safety benchmarks, and
arXiv:2609.10108v1 Announce Type: new Abstract: Aging clocks quantify biological aging and help characterize individual health status. What protein interactions are important for accurate aging clocks
arXiv:2609.06708v1 Announce Type: cross Abstract: Large language models are transforming many industries with their text generation abilities. However, their outputs can be easily tampered with, creat
arXiv:2609.06579v1 Announce Type: cross Abstract: Machine learning methods, and especially neural networks, are now routinely used for malware detection in network traffic. Though very effective, syst
arXiv:2609.06543v1 Announce Type: new Abstract: Enterprise AI is evolving into an Enterprise Operating System where autonomous AI agents can plan, reason, use memory, invoke tools, execute workflows,
arXiv:2609.09855v1 Announce Type: cross Abstract: Although probabilistic statements are ubiquitous, foundational disagreements persist about their understanding, as exemplified by debates between Baye
arXiv:2609.06914v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities across diverse domains, showing considerable potential in medicine. However, their ap
arXiv:2609.07334v1 Announce Type: new Abstract: The Asset Administration Shell (AAS) is a cornerstone of Industry 4.0 and the Digital Product Passport, providing standardized digital representations o
arXiv:2609.09380v1 Announce Type: new Abstract: Unlocking the potential of tiny aerial robots requires order of magnitude improvements in the performance of embedded edge control. In particular, altho
arXiv:2609.09257v1 Announce Type: new Abstract: Sensor-based AI systems are rarely operated under the conditions under which they were trained: devices, personnel and recording epochs change, and each
arXiv:2609.08256v1 Announce Type: cross Abstract: Automated red-team attacks and blue-team defenses for large language models (LLMs) are advancing quickly. However, attackers and defenders are built a
arXiv:2609.10142v1 Announce Type: new Abstract: Large language models remain fragile against malicious fine-tuning, motivating training-time defenses against harmful persona drift. Preventative Steeri
arXiv:2609.09492v1 Announce Type: new Abstract: Reinforcement learning has produced capable controllers across a broad range of legged-robot tasks, but a subset of these tasks fail to converge under s
arXiv:2603.08275v2 Announce Type: replace-cross Abstract: With the global proliferation of Large Language Models (LLMs), cultural safety, defined as the ability to generate respectful and appropriate
arXiv:2609.09511v1 Announce Type: cross Abstract: Physical-layer authentication (PLA) in non-terrestrial networks (NTNs) is challenged by severe Doppler shifts, long delays, and fast channel variation
arXiv:2609.10215v1 Announce Type: new Abstract: This work considers adaptive shared human-robot control for nonlinear control-affine systems, where the assumption of a fully rational human is relaxed
arXiv:2609.10456v1 Announce Type: new Abstract: Nanoscale imaging of mammalian brains is critical for connectomics. X-ray laminography enables high-throughput imaging of extended, plate-like biologica
arXiv:2609.09945v1 Announce Type: new Abstract: Machine learning-based credit scoring is increasingly central to Peer-to-Peer (P2P) lending, yet its resilience to adversarial manipulation, where appli
arXiv:2609.07672v1 Announce Type: new Abstract: Production content-generation systems must integrate a user's immediate task, long-term brand identity, historical evidence, and revision feedback. We p
arXiv:2609.10135v1 Announce Type: cross Abstract: To address insufficient contextualization, weak generalization, and poor scenario adaptation in tourism meteorological services, we propose SmartWeath
arXiv:2609.05837v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed in real-world applications through tool-use APIs, yet training them for specific environments remains fundame
arXiv:2606.16723v2 Announce Type: replace Abstract: Large language model (LLM) agents increasingly take actions (screening applicants, recommending credit, triaging patients), yet fairness for LLMs is
arXiv:2609.08572v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems (MAS) achieve strong performance by employing specialized multiple agents, yet their performance de
arXiv:2609.09503v1 Announce Type: new Abstract: Rapid bespoke commissioning of the Cognitive Digital Twin (CDT) is a major challenge in reconfigurable manufacturing. Traditional digital twin (DT) cons
arXiv:2609.07204v1 Announce Type: new Abstract: The minimum cut problem for an undirected edge-weighted graph asks us to divide its set of nodes into two blocks while minimizing the weighted sum of th
arXiv:2609.05818v1 Announce Type: new Abstract: We introduce ABLE, a benchmark for evaluating LLM agents' ability to use biological AI models (BAIMs), such as ProteinMPNN and AlphaFold3, in dual-use p
arXiv:2606.19795v2 Announce Type: replace-cross Abstract: Electronic design automation (EDA) is multi-stage and handoff-heavy, relying on transfers among humans, design artifacts, and multiple tools.
arXiv:2609.08248v1 Announce Type: new Abstract: Modern industrial ads ranking stacks are increasingly bottlenecked not by model capacity or training compute, but by the throughput of human ML iteratio
arXiv:2609.05995v1 Announce Type: new Abstract: Achieving reliable autonomy in the wild requires agents to sustain continuous operations across long-horizon trajectories. However, as agents navigate t
arXiv:2609.09187v1 Announce Type: cross Abstract: Advertising video generation is not only a video synthesis task, but also a product-conditioned reasoning problem whose success is measured by online
arXiv:2609.07611v1 Announce Type: new Abstract: Scientific ideation is the capacity to formulate novel and testable hypotheses from scientific evidence, and autonomous AI scientists depend on it. Exis
arXiv:2609.07131v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly achieve long-horizon tasks by combining foundation models with explicit skills and implicit procedural
arXiv:2609.05587v1 Announce Type: new Abstract: Existing evaluations of tool-using agents primarily measure whether an agent can successfully complete diverse tasks with tools. These evaluations gener
arXiv:2609.10469v1 Announce Type: new Abstract: Automated plant disease diagnosis is increasingly deployed on farmer-held devices in regions where agronomic expertise is scarce and network connectivit
arXiv:2609.08166v1 Announce Type: cross Abstract: The twenty-first century's transformative technology, artificial intelligence, is increasingly constrained by the twentieth century's transformative t
arXiv:2609.09884v1 Announce Type: new Abstract: Recent advances in Intrinsic Image Decomposition (IID) have increasingly relied on generative models. However, progress remains limited by three key cha
arXiv:2609.06197v1 Announce Type: cross Abstract: We study continuous-time full-order dynamic output-feedback H_infty policy search, a nonconvex and nonsmooth problem. Direct policy search is a centra
arXiv:2609.10428v1 Announce Type: cross Abstract: Algorithmic stability refers to the property of an algorithm being insensitive to perturbations of the input data, where the type of perturbation may
arXiv:2609.09685v1 Announce Type: new Abstract: Real-time hold control is a high-leverage mechanism in large-scale ride-hailing systems: by selectively deferring driver-order pairs, the platform can w
arXiv:2609.05899v1 Announce Type: cross Abstract: Aligning large language models with human preferences remains a challenge, primarily due to the critical role of preference data quality in effective