Knowledge catalogue
arXiv:2604.21028v1 Announce Type: cross Abstract: The increasing frequency and severity of global flood events highlights the need for the development of rapid and reliable flood prediction tools. Thi
arXiv:2604.21363v1 Announce Type: new Abstract: Bridging the gap between embodied intelligence and embedded deployment remains a key challenge in intelligent robotic systems, where perception, reasoni
arXiv:2601.18672v3 Announce Type: replace Abstract: Kolmogorov-Arnold Networks (KANs) have recently demonstrated promising potential in scientific machine learning, partly due to their capacity for gr
arXiv:2604.21411v1 Announce Type: new Abstract: Standard physics-informed neural networks (PINNs) struggle to simulate highly oscillatory Helmholtz solutions in heterogeneous media because pointwise m
arXiv:2604.21101v1 Announce Type: new Abstract: For autoregressive modeling of chaotic dynamical systems over long time horizons, the stability of both training and inference is a major challenge in b
arXiv:2604.21688v1 Announce Type: cross Abstract: The IC3 algorithm represents the state-of-the-art (SOTA) hardware model checking technique, owing to its robust performance and scalability. A signifi
arXiv:2604.21595v1 Announce Type: cross Abstract: Multivariate conformal prediction requires nonconformity scores that compress residual vectors into scalars while preserving certain implicit geometri
arXiv:2604.21579v1 Announce Type: cross Abstract: LLM-based automated program repair (APR) techniques have shown promising results in reducing debugging costs. However, prior results can be affected b
arXiv:2604.21891v1 Announce Type: cross Abstract: Maintaining instantaneous balance between electricity supply and demand is critical for reliability and grid instability. System operators achieve thi
arXiv:2604.21885v1 Announce Type: cross Abstract: Event extraction is essential for event understanding and analysis. It supports tasks such as document summarization and decision-making in emergency
arXiv:2604.21198v1 Announce Type: new Abstract: Object detection models typically perform well on images captured in controlled environments with stable lighting, water clarity, and viewpoint, but the
arXiv:2510.08814v2 Announce Type: replace-cross Abstract: We present a proof architecture for (P neq NP) based on an upper--lower clash in polytime-capped conditional description length. We construct
arXiv:2604.21377v1 Announce Type: new Abstract: Large language models are increasingly being explored as interfaces between humans and robotic systems, yet there remains limited evidence on how such t
arXiv:2604.21903v1 Announce Type: cross Abstract: Deep-learning video super-resolution has progressed rapidly, but climate applications typically super-resolve (increase resolution) either space or ti
arXiv:2604.21432v1 Announce Type: cross Abstract: In many application domains (e.g., recommender systems, intelligent tutoring systems), the rewards associated to the actions tend to decrease over tim
arXiv:2604.20990v1 Announce Type: new Abstract: Legged robots have demonstrated remarkable agility on rigid, stationary ground, but their locomotion reliability remains limited in non-inertial environ
arXiv:2604.21030v1 Announce Type: cross Abstract: The integration of Model Predictive Control (MPC) and Reinforcement Learning (RL) has emerged as a promising paradigm for constrained decision-making
arXiv:2604.21527v1 Announce Type: new Abstract: Low-cost air quality sensors (LCS) provide a practical alternative to expensive regulatory-grade instruments, making dense urban monitoring networks pos
arXiv:2604.20898v1 Announce Type: new Abstract: Wrist function is essential in performing activities of daily living (ADLs). However, there is limited experimental evidence on the functional impact of
arXiv:2604.21623v1 Announce Type: cross Abstract: The proliferation of Internet of Things (IoT) devices has significantly expanded attack surfaces, making IoT ecosystems particularly susceptible to so
arXiv:2604.20915v1 Announce Type: cross Abstract: Transformers suffer from a high computational cost that grows with sequence length for self-attention, making inference in long streams prohibited by
arXiv:2510.18091v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) partition input images into uniformly sized patches regardless of their content, resulting in long input sequence l
arXiv:2503.04492v3 Announce Type: replace-cross Abstract: In the rapidly advancing field of materials informatics, nonlinear machine learning models have demonstrated exceptional predictive capabiliti
arXiv:2604.20907v1 Announce Type: cross Abstract: We study the community detection problem in the non-uniform hypergraph stochastic block model (HSBM), where hyperedges of varying sizes coexist. This
arXiv:2604.21044v1 Announce Type: new Abstract: In some complex domains, certain problem-specific decompositions can provide advantages over monolithic designs by enabling comprehension and specificat
arXiv:2602.23666v2 Announce Type: replace-cross Abstract: The increasing size and heterogeneity of exoplanet catalogs have made systematic habitability assessment challenging, particularly given the e
arXiv:2604.20932v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) systems are increasingly deployed in sensitive domains such as healthcare and law, where they rely on private, do
arXiv:2604.21159v1 Announce Type: cross Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifyin
arXiv:2603.16797v2 Announce Type: replace-cross Abstract: Guided diffusion sampling relies on approximating often intractable likelihood scores, which introduces significant noise into the sampling dy
arXiv:2407.19664v3 Announce Type: replace Abstract: Previous research on selective protection for neural network components typically exploits only static vulnerability differences. Although these met
arXiv:2604.21018v1 Announce Type: new Abstract: While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from
arXiv:2511.04638v5 Announce Type: replace-cross Abstract: A common approach to mechanistic interpretability is to causally manipulate model representations via targeted interventions in order to under
arXiv:2604.21879v1 Announce Type: cross Abstract: The ability of generative AI (GenAI) methods to photorealistically alter camera images has raised awareness about the authenticity of images shared on
arXiv:2604.20846v1 Announce Type: cross Abstract: Next point-of-interest (POI) recommendation requires modeling user mobility as a spatiotemporal sequence, where different behavioral factors may evolv
arXiv:2604.21310v1 Announce Type: cross Abstract: Deep learning has emerged as a powerful approach for malware detection, demonstrating impressive accuracy across various data representations. However
arXiv:2604.21725v1 Announce Type: cross Abstract: LLM agents increasingly operate in open-ended environments spanning hundreds of sequential episodes, yet they remain largely stateless: each task is s
arXiv:2604.20996v1 Announce Type: new Abstract: How can language learning systems be developed for languages that lack sufficient training resources? This challenge is increasingly faced by developers
arXiv:2601.18491v2 Announce Type: replace Abstract: The rise of AI agents introduces complex safety and security challenges arising from autonomous tool use and environmental interactions. Current gua
arXiv:2604.05846v2 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly rely on agentic capabilities-iterative retrieval, tool use, and decision-making-to overcome the limits of
arXiv:2604.21744v1 Announce Type: cross Abstract: The capabilities of AI-assisted coding are progressing at breakneck speed. Chat-based vibe coding has evolved into fully fledged AI-assisted, agentic
arXiv:2604.21154v1 Announce Type: new Abstract: At-home physiotherapy compliance remains critically low due to a lack of personalized supervision and dynamic feedback. Existing digital health solution
arXiv:2604.21590v1 Announce Type: new Abstract: Modern industrial applications increasingly demand language models that act as agents, capable of multi-step reasoning and tool use in real-world settin
arXiv:2604.21129v1 Announce Type: cross Abstract: Current blockchain Layer 2 solutions, including Optimism, Arbitrum, zkSync, and their derivatives, optimize for human-initiated financial transactions
arXiv:2511.23159v2 Announce Type: replace-cross Abstract: Vibe coding, the much-touted use of AI techniques for programming, faces two overwhelming obstacles: the difficulty of specifying goals ('prom
arXiv:2604.21103v1 Announce Type: new Abstract: Governments are increasingly interested in using AI to make administrative decisions cheaper, more scalable, and more consistent. But for probabilistic
arXiv:2604.21446v1 Announce Type: new Abstract: We present AI-Gram, a live platform enabling image-based interactions, to study social dynamics in a fully autonomous multi-agent visual network where a
arXiv:2604.20878v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in Traffic Accident Detection (TAD) and Traffic Accident Understanding (TAU).
arXiv:2507.15753v2 Announce Type: replace-cross Abstract: Generative machine learning models have revolutionized material discovery by capturing complex structure-property relationships, yet extending
arXiv:2604.21209v1 Announce Type: new Abstract: Online reviews have played a pivotal role in consumers' decision-making processes. Existing research has highlighted the significant impact of manageria
arXiv:2604.21827v1 Announce Type: new Abstract: Modern AI assistants are trained to follow instructions, implicitly assuming that users can clearly articulate their goals and the kind of assistance th
arXiv:2604.21798v1 Announce Type: new Abstract: The k-means problem is perhaps the classical clustering problem and often synonymous with Lloyd's algorithm (1957). It has become clear that Hartigan's
arXiv:2604.21311v1 Announce Type: new Abstract: Brain tumors represent one of the most critical neurological conditions, where early and accurate diagnosis is directly correlated with patient survival
arXiv:2602.13211v2 Announce Type: replace-cross Abstract: Compared with IP multicast, Overlay Multicast (OM) offers better compatibility and flexible deployment in heterogeneous, cross-domain networks
arXiv:2502.04416v3 Announce Type: replace-cross Abstract: Scaling large language models (LLMs) improves performance but significantly increases inference costs, with feed-forward networks (FFNs) consu
arXiv:2504.03476v2 Announce Type: replace Abstract: Accurate lumbar spine segmentation is crucial for diagnosing spinal disorders. Existing methods typically use coarse-grained segmentation strategies
arXiv:2502.15793v2 Announce Type: replace Abstract: Anomaly detection in smart power grids is a critical challenge due to the complexity, heterogeneity, and dynamic nature of sensor data streams. Exis
arXiv:2505.09971v3 Announce Type: replace Abstract: Airborne laser scanning (ALS) point cloud semantic segmentation is a fundamental task for large-scale 3D scene understanding. Fixed models deployed
arXiv:2604.20862v1 Announce Type: new Abstract: The automation system for Course of Action (CoA) planning is an essential element in future warfare. As maneuver speeds increase, surveillance ranges ex
arXiv:2604.21529v1 Announce Type: cross Abstract: Applying the concept of controlled self-organization in agent-based Cyber-Physical Energy Systems (CPES) is a promising approach to ensure system robu
arXiv:2604.21199v1 Announce Type: cross Abstract: Time series question-answering (TSQA), in which we ask natural language questions to infer and reason about properties of time series, is a promising