Knowledge catalogue
arXiv:2608.14826v1 Announce Type: cross Abstract: The wireless networks have historically faced significant security vulnerabilities, necessitating advanced anomaly detection mechanisms, especially as
arXiv:2510.17088v3 Announce Type: replace-cross Abstract: Financial anomalies arise from heterogeneous mechanisms - price shocks, liquidity freezes, contagion cascades, and momentum reversals - yet ex
arXiv:2608.14620v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has been extensively used in autonomous and self-* systems, but RL policies, especially deep RL ones relying on neural net
arXiv:2608.16476v1 Announce Type: new Abstract: Learning embodied urban navigation policies from real-world data is constrained by the cost of task-specific data collection and the limited coverage of
arXiv:2608.14603v1 Announce Type: cross Abstract: Cooperative perception enables vehicles and infrastructure to exchange sensor data via Vehicle-to-Everything (V2X) communication, extending sensing co
arXiv:2608.16697v1 Announce Type: new Abstract: Vision-Language-Action models (VLAs) integrate visual perception, language instruction, and action generation into end-to-end policies across heterogene
arXiv:2608.15408v1 Announce Type: new Abstract: Deep operator networks can become statistically unstable when partial differential equation inputs are observed at thousands of strongly correlated sens
arXiv:2608.15113v1 Announce Type: cross Abstract: Learned image compression (LIC) has demonstrated remarkable rate-distortion (RD) performance in benign settings. However, the high representational ca
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:2608.15867v1 Announce Type: cross Abstract: Synthetic populations are critical inputs for activity-based travel demand models, yet generating realistic populations from limited survey data remai
arXiv:2608.16148v1 Announce Type: new Abstract: Multi-view multi-label feature selection aims to identify a compact and informative feature subset from heterogeneous views while preserving discriminat
arXiv:2608.15310v1 Announce Type: cross Abstract: Multimodal data collected by heterogeneous devices are used for collaborative training, where federated learning (FL) serves as a key paradigm for eff
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:2608.14654v1 Announce Type: cross Abstract: Federated Learning (FL) is a collaborative paradigm that enables multiple devices to train a global model while preserving local data privacy. A major
arXiv:2608.15381v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) enables efficient federated fine-tuning of large language models, but its factorized parameterization creates a tension betwe
arXiv:2608.15343v1 Announce Type: new Abstract: Reconstructing three-dimensional computed tomography (CT) from severely constrained projections is highly ill-posed. Sparse angular sampling, restricted
arXiv:2608.16385v1 Announce Type: new Abstract: Early time-series classification (ETSC) aims to make accurate predictions from partially observed time series as early as possible. Although various sto
arXiv:2608.15976v1 Announce Type: new Abstract: A learning system can occupy execution states that are indistinguishable under every declared present-behavior readout yet respond differently to future
arXiv:2608.15177v1 Announce Type: cross Abstract: The increasing complexity of digital financial systems has reshaped financial fraud detection from isolated transaction classification into relational
Mozilla Corp. rolled out updates today to its popular Firefox browser, updating an artificial intelligence assistant called Smart Window, currently in beta, that lets users check answers, summarize op
arXiv:2608.15727v1 Announce Type: cross Abstract: Diffusion models have recently shown strong potential for multivariate time-series anomaly detection by learning the distribution of normal data throu
arXiv:2608.16523v1 Announce Type: new Abstract: Event cameras generate asynchronous, high-frequency data streams offering spatially sparse information at lower latency than traditional cameras.In prin
arXiv:2602.13185v2 Announce Type: replace Abstract: Effective and generalizable control in video generation remains a significant challenge. While many methods rely on ambiguous or task-specific signa
arXiv:2608.16853v1 Announce Type: new Abstract: Multi-segment suction-based soft robots are promising for inspection and maintenance in confined or fragile environments, but existing approaches still
arXiv:2608.15410v1 Announce Type: cross Abstract: Reasoning segmentation enables vision-language models (VLMs) to translate mission-relevant language requests into pixel-level visual grounding, offeri
arXiv:2608.14550v1 Announce Type: new Abstract: AI efficiency has recently taken the spotlight in both academy and industry due to massive model scales, high energy demands, and environmental costs. W
arXiv:2608.15818v1 Announce Type: new Abstract: Music-driven dance video synthesis aims to animate a reference person according to a given music clip. The task is challenging because it requires a mod
arXiv:2608.15602v1 Announce Type: cross Abstract: While binary quantization theoretically promises extreme compression and acceleration for Large Language Models (LLMs), existing research often overlo
arXiv:2608.15296v1 Announce Type: new Abstract: Audio-driven 3D facial animation is essential for advancing immersion and interactivity in virtual experiences. Although recent advances have shown prom
arXiv:2509.06461v3 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have demonstrated remarkable success across diverse visual tasks, yet their performance degrades in complex visu
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:2608.15009v1 Announce Type: cross Abstract: Embodied intelligent ultrasound scanning enables the automation and standardization of the ultrasound examination process by integrating perception, d
arXiv:2608.16273v1 Announce Type: cross Abstract: Foresight-England (Foresight-E) is the first national-scale generative foundation model of electronic health records (EHRs), developed as a research p
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
Fortinet Inc. announced its intent to acquire Virtue AI Inc. Monday, and though the financial aspects are interesting, what’s more significant is how this will help businesses with their next big secu
arXiv:2608.14563v1 Announce Type: cross Abstract: Forward-Pass-Only MLP training (FPO) adapts large language models without a backward pass through the model body, achieving 2.7--3.2x the throughput o
arXiv:2608.14636v1 Announce Type: cross Abstract: Fractional optimization methods and fractal activation functions are two independent directions for improving neural network training. Fractional opti
arXiv:2604.02765v2 Announce Type: replace Abstract: Class-incremental learning (CIL) is commonly evaluated under predefined schedules with fixed or nearly equal class increments, leaving irregular cla
arXiv:2608.15054v1 Announce Type: new Abstract: Remote sensing image semantic segmentation (RSISS) has attracted significant attention due to the growing demand for fine-grained land cover information
arXiv:2603.17555v2 Announce Type: replace-cross Abstract: Diffusion-based image-to-video (I2V) models are increasingly effective, yet they struggle to scale to ultra-high-resolution inputs (e.g., 4K).
arXiv:2608.15536v1 Announce Type: new Abstract: In value-based argumentation, an audience's ordering of values decides which attacks succeed as defeats. In many settings the deciding factor is not the
arXiv:2608.14937v1 Announce Type: new Abstract: The increasing dynamic demands of modern robotic joints require current controllers to achieve high bandwidth over wide operating ranges of speed, accel
arXiv:2608.14740v1 Announce Type: new Abstract: Unified image and video creation requires a model to follow diverse instructions while preserving identity, geometry, and temporal structure from visual
arXiv:2608.14567v1 Announce Type: new Abstract: This paper presents a targeted narrative review establishing the historical and theoretical foundations for computational belief change implementation.
arXiv:2608.14771v1 Announce Type: new Abstract: Making language models solve constraint problems reliably often means having them translate the problem into a formal specification and delegating the s
arXiv:2608.15580v1 Announce Type: new Abstract: Reliable endoscopic polyp reporting requires integrating quantitative lesion sizing, standardized Paris classification, and clinically meaningful morpho
arXiv:2608.15812v1 Announce Type: new Abstract: This paper documents a frozen engineering project on personalized Chinese handwriting. The project started from approximately 200 real handwriting image
arXiv:2608.15127v1 Announce Type: cross Abstract: Agentic applications are shifting AI serving from isolated model inference to long-running workloads in which LLMs coordinate tools, environments, and
arXiv:2209.01432v4 Announce Type: replace-cross Abstract: In this paper we study probabilistic and neural network approximations for solutions to Poisson equation subject to Holder data in general bou
arXiv:2608.14787v1 Announce Type: cross Abstract: Speculative decoding is a leading technique to reduce the cost of autoregressive generation by using a small drafter to propose several tokens, which
arXiv:2506.16697v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are entering psychological research both as tools and as objects of inquiry. Yet many studies apply human instrum
arXiv:2608.14574v1 Announce Type: cross Abstract: The operational model for cloud network infrastructure has undergone a fundamental transformation over the past decade. What began as manual, human-dr
arXiv:2608.16002v1 Announce Type: cross Abstract: Reliable uncertainty quantification (UQ) is essential for deploying large language model (LLM) agents in complex interactive environments. Existing UQ
arXiv:2604.05635v2 Announce Type: replace Abstract: Numerical preprocessing remains a critical component of tabular deep learning, as the representation of continuous features can strongly affect down
arXiv:2608.15163v1 Announce Type: new Abstract: Visual brain decoding reconstructs visual content perceived by a person from neural measurements such as fMRI, providing a computational approach to stu
arXiv:2608.14903v1 Announce Type: new Abstract: Quantitative forecasts of frontier artificial intelligence often connect dated targets to trends in benchmark scores, training compute, release time, or
arXiv:2608.16303v1 Announce Type: new Abstract: Long-term emotional-support agents require memory mechanisms for personalized understanding across sessions. However, emotional-support dialogue is ofte
arXiv:2410.15921v3 Announce Type: replace Abstract: Existing source-seeking algorithms for robot swarms typically require either direct gradient measurements or rigid geometric formations, limiting th
arXiv:2608.15952v1 Announce Type: cross Abstract: Differences between high-energy event generators can arise at several stages of the collision simulation, from the hard scattering through parton show
arXiv:2608.15065v1 Announce Type: new Abstract: Large Reasoning Models produce diverse, sometimes inconsistent answers across repeated queries on the same problem, so multi-sample inference is a prere