Knowledge catalogue
arXiv:2608.16158v1 Announce Type: cross Abstract: Phishing remains a persistent and evolving cybersecurity threat, with attack volumes reaching record levels. This growth is driven by the industrializ
arXiv:2608.14723v1 Announce Type: new Abstract: Reduced left ventricular ejection fraction (LVEF) is frequently asymptomatic and often detected only after advanced heart failure develops. Electrocardi
arXiv:2608.16319v1 Announce Type: new Abstract: This first release of Prior Labs in relational learning shows our continued commitment to open science. We open-source three pieces of software that we
Amazon Bedrock AgentCore payments is now generally available, enabling AI agents to autonomously transact at scale with built-in spending guardrails, protocol-agnostic payment orchestration, and produ
arXiv:2608.16351v1 Announce Type: new Abstract: Dexterous grasp generation that considers arm-related constraints is crucial in real-world scenarios involving arm environment collision avoidance, work
arXiv:2608.15949v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have enabled their use as conversational recommender systems (CRS), demonstrating strong recommendatio
arXiv:2608.16118v1 Announce Type: new Abstract: How should we assess whether large language models can perform mathematical invention? I argue that this question is currently underspecified: mathemati
arXiv:2608.16336v1 Announce Type: cross Abstract: Modern LLM serving deployments must simultaneously satisfy heterogeneous service-level objectives (SLOs) across a diverse population of user tiers, ra
arXiv:2608.14800v1 Announce Type: cross Abstract: With the growth of digital document exchange, protecting image integrity against attacks such as Vector Quantization (VQ) and collage has become criti
arXiv:2608.16855v1 Announce Type: new Abstract: Background Lung cancer remains the deadliest cancer worldwide because it is often diagnosed too late. Effective treatment depends on detection at an ear
arXiv:2608.14950v1 Announce Type: new Abstract: Generative AI systems are increasingly producing real-world artifacts, however their efficacy and validity are often evaluated via context-free LLM-scor
arXiv:2608.15780v1 Announce Type: cross Abstract: Stale recommendations are a pervasive challenge and a leading source of user complaints on large-scale content platforms. Items lose relevance through
arXiv:2608.16612v1 Announce Type: cross Abstract: An accurate estimation of the state of health (SOH) underpins a safe and optimized use of the battery system. Although compelling, data-driven SOH est
arXiv:2608.14974v1 Announce Type: new Abstract: This paper presents a demand-driven framework for on-demand Urban Air Mobility (UAM) network design that links vertiport siting, fleet simulation, and d
arXiv:2510.00358v2 Announce Type: replace-cross Abstract: Soft snake robots offer remarkable flexibility and adaptability in complex environments, yet their control remains challenging due to highly n
arXiv:2608.14916v1 Announce Type: cross Abstract: AI-generated music detectors are commonly evaluated against original songs, but real-world uploads are often remixed, re-encoded, pitch-shifted, or ot
arXiv:2608.15630v1 Announce Type: cross Abstract: The rapid development and growing deployment of large language models (LLMs) have made it increasingly important to understand their capabilities. A c
arXiv:2608.16161v1 Announce Type: cross Abstract: General-purpose text embedding models are designed to capture semantic similarity but are not optimised for distinguishing entity records that represe
arXiv:2608.16640v1 Announce Type: new Abstract: Vision-based Unmanned Aerial Vehicles (UAVs) often suffer from navigation failures in dead ends due to limited sensing accuracy and range. To address th
arXiv:2608.16270v1 Announce Type: new Abstract: Coreset selection reduces the cost of model training by replacing a large training set with a small representative subset. Existing gradient-approximati
arXiv:2608.15060v1 Announce Type: new Abstract: Touch is fundamental to dexterous manipulation, yet most egocentric human data increasingly used for robot learning lacks tactile information. Directly
arXiv:2608.16101v1 Announce Type: cross Abstract: Coresets distill large datasets into small, representative subsets for efficient downstream learning. Yet Optimal Transport (OT)-based selection typic
arXiv:2508.18037v2 Announce Type: replace Abstract: Leveraging information from public data has become increasingly crucial in enhancing the utility of differentially private (DP) methods. Traditional
arXiv:2603.02830v2 Announce Type: replace-cross Abstract: Predicting future student responses to questions is particularly valuable for educational learning platforms where it enables effective interv
arXiv:2510.04927v2 Announce Type: replace-cross Abstract: Automatic modulation classification (AMC) is a core enabler of cognitive wireless systems, providing spectrum awareness and supporting adaptiv
arXiv:2507.15502v1 Announce Type: cross Abstract: Postoperative follow-up plays a crucial role in monitoring recovery and identifying complications. However, traditional approaches, typically involvin
arXiv:2603.15427v2 Announce Type: replace-cross Abstract: Robots are increasingly deployed across diverse domains and designed for multi-purpose operation. As robotic systems grow in complexity and op
arXiv:2608.15707v1 Announce Type: new Abstract: Correcting robot manipulation policies through human intervention holds great promise for real-world deployment, yet human operators are inherently impe
arXiv:2501.18898v4 Announce Type: replace Abstract: Generating full-body human gestures based on speech signals remains challenges on quality and speed. Existing approaches model different body region
arXiv:2608.16073v1 Announce Type: cross Abstract: Sequential recommenders often struggle with sparse and noisy histories, limiting generalization to unseen interactions. Knowledge distillation mitigat
arXiv:2608.15382v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed for healthcare decision support, but their evaluations still reward single-answer accuracy rather
arXiv:2608.15446v1 Announce Type: new Abstract: This paper presents an evaluation of a goal-free probabilistic framework for human intent inference during robotic manipulation. We deploy the Global Us
arXiv:2608.14820v1 Announce Type: cross Abstract: Handover (HO) management in vehicular networks requires fast and reliable decision-making under highly dynamic conditions. While machine learning (ML)
arXiv:2608.16447v1 Announce Type: new Abstract: Long-horizon embodied tasks require LLM agents to iteratively decompose high-level goals, revise plans in response to environmental feedback, and ground
In this post, we describe how AIDA works at a high level and how it helps address these challenges — grounding users in the right contracts, under the right legal context, and within the right access
arXiv:2506.02917v2 Announce Type: replace Abstract: We propose a training-free, Vision-Language Model (VLM)-guided approach for efficiently generating trajectories to facilitate target inspection plan
arXiv:2608.14657v1 Announce Type: cross Abstract: Early identification of lung cancer risk is critical for timely intervention, yet existing prediction models are limited by their reliance on single d
arXiv:2407.00890v5 Announce Type: replace-cross Abstract: This paper presents a comparative analysis evaluating the accuracy of Large Language Models (LLMs) against traditional macro time series forec
arXiv:2608.15465v1 Announce Type: cross Abstract: Identification of IoT device types from passive traffic is increasingly used for security management in enterprise and ISP networks. However, the perf
arXiv:2603.17216v2 Announce Type: replace Abstract: With the advent of AI agents, automated scientific discovery is becoming an increasingly plausible goal. However, training agents to autonomously ex
arXiv:2410.19504v3 Announce Type: replace-cross Abstract: Dimensionality reduction (DR) plays a crucial role in various fields, including data engineering and visualization, by simplifying complex dat
The rise of neoclouds — AI-first cloud providers — is transforming enterprise infrastructure. The unique requirements of AI models and agents have paved the way for new collaborations between hardware
arXiv:2509.24900v2 Announce Type: replace-cross Abstract: The performance of unified multimodal models for image generation and editing is fundamentally constrained by the quality and comprehensivenes
arXiv:2608.14742v1 Announce Type: cross Abstract: Pandas has emerged as the de facto library for data processing and machine learning, widely used for tasks, such as data loading, transformation, and
arXiv:2608.16225v1 Announce Type: new Abstract: Standard Transformers have proven effective in point cloud object classification, but their performance in dense prediction tasks within complex scenes
arXiv:2608.15504v1 Announce Type: new Abstract: Encrypted traffic classification is vital for network security, yet real-world deployments are inherently sensitive to rare but high-loss errors such as
arXiv:2505.23863v3 Announce Type: replace-cross Abstract: Understanding chaotic dynamics is a fundamental problem across scientific disciplines, including climate science, neuroscience, and fluid dyna
arXiv:2608.14606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic survey respondents, but existing evaluations ask whether answers look plausible at the
arXiv:2608.16276v1 Announce Type: cross Abstract: Debate is a structured form of persuasive communication that trains argument construction, rebuttal, oral delivery, and audience awareness. These skil
arXiv:2608.15810v1 Announce Type: new Abstract: Runtime compression of serving state trades quality for capacity with no priced guarantee: systems adapt precision on load signals with no soundness sta
arXiv:2509.10691v3 Announce Type: replace-cross Abstract: Decentralized federated learning enables collaborative model training without a central server, but shared model updates can still leak sensit
arXiv:2608.15857v1 Announce Type: new Abstract: Ethereum is now integral to mission-critical sectors, including finance, healthcare, and supply chain management. Execution fees, commonly referred to a
arXiv:2608.14865v1 Announce Type: new Abstract: An actuator health estimation algorithm for a soft swimming robot that can perform anguilliform swimming is developed. Due to harsh operational environm
arXiv:2608.15938v1 Announce Type: new Abstract: Action chunking --- the practice of predicting a sequence of actions and executing a prefix open-loop --- has emerged as a key enabler of recent progres
arXiv:2608.15217v1 Announce Type: new Abstract: Existing blind image quality assessment (BIQA) methods typically rely on synthetic distortions and subjective annotations, limiting generalization in re
arXiv:2608.16741v1 Announce Type: new Abstract: Long-term manipulation planning requires robots to reason not only about immediate task success but also about how current decisions affect future inter
arXiv:2608.16409v1 Announce Type: new Abstract: Today, a neural system is almost always used in two phases -- trained, then deployed -- and in that regime it freezes twice: training ends, and the topo
arXiv:2608.14697v1 Announce Type: new Abstract: Steganography in large language models offers a way to embed hidden messages within natural-sounding text. Existing token and logit-level methods typica
arXiv:2608.14675v1 Announce Type: cross Abstract: While Self-Supervised Learning (SSL) effectively extracts general representations from noisy, unconstrained physiological signals such as photoplethys
arXiv:2608.15270v1 Announce Type: new Abstract: Miss a filing deadline by one day and the claim is barred, however strong the case. Computing that deadline is rarely simple: the period runs from a tri