Knowledge catalogue
arXiv:2608.01867v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly extended into deep search agents that solve complex questions through multi-step interaction with external
arXiv:2608.00566v1 Announce Type: new Abstract: Post-hoc model explainers such as LIME, SHAP, and Integrated Gradients are widely deployed to audit models in high-stakes sensitive domains, including f
arXiv:2608.02472v1 Announce Type: new Abstract: Trust is fundamental in modern regulatory ecosystems, and compliance checking plays a critical role in fostering that trust. Regulatory compliance verif
arXiv:2607.11510v2 Announce Type: replace Abstract: Causal discovery from observational tabular data remains fundamentally challenging, primarily due to the heterogeneity of underlying causal mechanis
arXiv:2608.00835v1 Announce Type: cross Abstract: Fragile X Syndrome (FXS) is a neurodevelopmental disorder caused by reduced expression of fragile X mental retardation protein (FMRP), leading to disr
arXiv:2506.02976v4 Announce Type: replace Abstract: The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) thro
arXiv:2608.02092v1 Announce Type: new Abstract: Deep multimodal fusion for object detection has demonstrated good performance through mining modal characteristics. However, existing feature-level fusi
arXiv:2608.00432v1 Announce Type: new Abstract: Deep research agents are often trained on expensive, environment-grounded tool-use trajectories that require repeated retrieval, document inspection, an
arXiv:2511.13749v2 Announce Type: replace Abstract: Deep neural networks are known to be vulnerable to adversarial perturbations, which are small, carefully crafted inputs that lead to incorrect predi
arXiv:2607.15807v2 Announce Type: replace Abstract: Ultra-Wideband (UWB) ranging has become a viable option for industrial Autonomous Mobile Robot (AMR) localization due to improved accuracy and low c
arXiv:2608.01343v1 Announce Type: new Abstract: The emergence of transformer-based deep learning models has brought unprecedented performance across various domains, particularly in natural language p
arXiv:2508.08831v2 Announce Type: replace-cross Abstract: Generating synthetic images that closely mimic those from real cameras is instrumental in training visual models and enabling end-to-end visuo
arXiv:2608.01985v1 Announce Type: new Abstract: Visual token pruning reduces the computational cost of Vision-Language Models (VLMs) by removing redundant visual tokens. The key is to learn a score th
arXiv:2608.00089v1 Announce Type: new Abstract: With rapid growth in the fields of empirical and computational aesthetics we have seen a vast increase in large image datasets annotated for aesthetics.
arXiv:2608.02396v1 Announce Type: new Abstract: Most evidence on the effectiveness of explainable artificial intelligence (XAI) attribution methods has been established on convolutional neural network
arXiv:2608.01559v1 Announce Type: cross Abstract: Adversarial self-play is an appealing recipe for legal reasoning: have a student model draft an argument, have an adversary attack it, and reward the
arXiv:2608.02235v1 Announce Type: new Abstract: Recent advances in neural text-to-speech (TTS) systems have substantially improved speech naturalness and intelligibility across many languages. However
arXiv:2603.00919v3 Announce Type: replace Abstract: Large language models (LLMs) have shown great promise for autonomous driving. However, discretizing numbers into tokens limits precise numerical rea
arXiv:2608.00086v1 Announce Type: new Abstract: Brain tumor diagnosis is a time-sensitive process in which patients may wait weeks for a finalized pathology report. This problem motivates automated sy
arXiv:2608.01452v1 Announce Type: cross Abstract: Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that a
arXiv:2607.17244v2 Announce Type: replace Abstract: Longitudinal T cell receptor repertoires contain signals of clonal expansion, contraction, disappearance, and reappearance after immune perturbation
arXiv:2608.02474v1 Announce Type: new Abstract: Audio-driven video generation (A2V) has achieved promising progress in synthesizing temporally coherent and audio-visually aligned videos, yet its infer
arXiv:2608.02168v1 Announce Type: new Abstract: Credit risk detection, particularly mitigating individual fraud, is crucial for maintaining the stability of digital financial ecosystems. Accurately id
arXiv:2510.01925v3 Announce Type: replace Abstract: Reward models (RMs) play a critical role in enhancing the reasoning performance of LLMs. For example, they can provide training signals to finetune
arXiv:2509.11924v2 Announce Type: cross Abstract: Multimodal learning has attracted much attention in recent years due to its ability to effectively utilize data features from a variety of different m
arXiv:2608.00346v1 Announce Type: new Abstract: Data imbalance poses a major challenge in supervised classification, where the majority-class bias contributes to false negatives and overestimates clas
arXiv:2608.02284v1 Announce Type: new Abstract: Open-vocabulary segmentation identifies and segments objects from arbitrary textual descriptions. SAM 3 supports noun-phrase-guided segmentation and ach
arXiv:2608.02289v1 Announce Type: new Abstract: Realistic and diverse trajectory generation is central to enabling higher levels of vehicle automation. While rule-based and classical learning-based me
arXiv:2608.01091v1 Announce Type: new Abstract: AdaBoost.MH reduces multi-class classification to a collection of binary subproblems and enjoys the classical boosting-type convergence guarantee under
arXiv:2608.01661v1 Announce Type: new Abstract: The challenge of fair deepfake detection (FDD) has attracted increasing attention. Existing fairness-enhanced detectors often suffer from suboptimal gen
arXiv:2504.21296v2 Announce Type: replace Abstract: Graph learning has evolved into Augmented Graph Learning (AGL) by integrating specialized machine learning (ML) techniques. Examples include federat
arXiv:2608.02213v1 Announce Type: cross Abstract: Inclusion dependency is a relation between attributes of tables that indicates possible Primary Key-Foreign Key references. Automatic discovery of inc
arXiv:2608.01950v1 Announce Type: new Abstract: Autonomous 3D reconstruction with depth sensors is strongly affected by reflective surfaces, which cause missing or unreliable measurements and reduce t
arXiv:2507.21449v2 Announce Type: replace-cross Abstract: Degeneracy is an inherent feature of the loss landscape of neural networks, but it is not well understood how stochastic gradient MCMC (SGMCMC
arXiv:2603.28067v2 Announce Type: replace Abstract: Digital testing has emerged as a key paradigm for the development and verification of autonomous maritime navigation systems, yet the availability o
arXiv:2608.01202v1 Announce Type: new Abstract: Fruit ripeness prediction (FRP) is a classification-based agricultural computer vision task that has attracted much attention, thanks to its wide-rangin
arXiv:2608.00932v1 Announce Type: new Abstract: The integration of artificial intelligence into medical question-answering systems has advanced rapidly; however, research remains predominantly focused
arXiv:2608.01552v1 Announce Type: cross Abstract: Quadratic Gradient (QG) is a Newton-type optimization framework that bridges first-order gradient descent and second-order optimization by incorporati
arXiv:2608.01677v1 Announce Type: new Abstract: Myocardial strain analysis of cardiac magnetic resonance (CMR) images provides an important tool for evaluating cardiac function. However, current techn
arXiv:2608.00156v1 Announce Type: cross Abstract: The push for broader coverage in future cellular networks depends on reliable service, yet this is increasingly harder to do as we encounter more inst
arXiv:2608.01528v1 Announce Type: new Abstract: Vector symbolic architectures (VSA) are widely used for reasoning in neuro-symbolic (NeSy) AI, yet high-dimensional codebooks often create severe memory
arXiv:2506.03270v3 Announce Type: replace Abstract: While recent advances in vision-language models have accelerated language-guided robot planning, their black-box nature lacks the safety guarantees
arXiv:2608.00577v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models have become a dominant architecture for large-scale AI services, yet deploying them over geo-distributed heterogeneous
arXiv:2608.00537v1 Announce Type: new Abstract: Latent Flow Models have revolutionized compressed-space image synthesis, yet their application to high-fidelity inverse problems remains bottlenecked. I
arXiv:2608.00588v1 Announce Type: new Abstract: Layout-to-image diffusion models have achieved impressive semantic controllability by conditioning generation on category-level segmentation maps. Howev
arXiv:2606.13485v3 Announce Type: replace-cross Abstract: Safe rehabilitation is an interaction-dynamics problem: the controller must regulate a prescribed motion while absorbing involuntary spasm, vo
arXiv:2512.10739v3 Announce Type: replace Abstract: Large Reasoning Models (LRMs) have expanded the mathematical reasoning frontier through Chain-of-Thought (CoT) techniques and Reinforcement Learning
arXiv:2608.01599v1 Announce Type: new Abstract: Volatility forecasts are commonly evaluated with aggregate accuracy metrics such as RMSE and MAE, but these metrics can hide conditional failures that m
arXiv:2511.12723v2 Announce Type: replace Abstract: Deep neural networks typically rely on the representation produced by their final hidden layer to make predictions, implicitly assuming that this si
arXiv:2608.01562v1 Announce Type: new Abstract: Optimal trajectory generation for rigid-body motions on Lie groups can be formulated as a variational problem that minimizes energy functionals defined
arXiv:2608.02432v1 Announce Type: new Abstract: Autoregressive models have emerged as an effective paradigm for point cloud generation. However, most existing approaches rely on heuristic tokenization
arXiv:2608.01614v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face a critical computational bottleneck when processing high-resolution imagery due to the O(N^2) memory complexity of So
arXiv:2608.00406v1 Announce Type: cross Abstract: Accurate indoor localization is essential for emerging applications in robotic navigation and search and rescue. While classical methods typically foc
arXiv:2608.02404v1 Announce Type: new Abstract: The Loggia dei Lanzi in the Piazza della Signoria is one of Florence's most prominent structures visited by millions every year. Its construction histor
arXiv:2608.01074v1 Announce Type: cross Abstract: Tabular data is used extensively in many real-world use cases. Deep learning models have been developed to deal with tabular data, but generally perfo
arXiv:2608.00096v1 Announce Type: new Abstract: Current deep learning-based character vision studies, e.g., text recognition, character image denoising, and historical text completion, are offering ne
arXiv:2608.01128v1 Announce Type: cross Abstract: In post-disaster scenarios, unmanned aerial vehicles (UAVs) are critical for establishing emergency communication networks. For time-critical rescue m
arXiv:2608.00893v1 Announce Type: new Abstract: Robust to intensity inhomogeneity, the local Chan--Vese (LCV) model extends the classical Chan--Vese (CV) image segmentation method by incorporating loc
arXiv:2608.00257v1 Announce Type: new Abstract: Automated visual monitoring of urban environments is a growing Computer Vision research area, but municipal solid waste detection remains under-represen
arXiv:2608.00206v1 Announce Type: new Abstract: Navigating doorways is a fundamental capability for mobile manipulators operating in human environments, requiring coordinated motion between the mobile