Knowledge catalogue
arXiv:2608.19199v1 Announce Type: cross Abstract: We describe the evolution of a virtual assistant, called ATHENA, designed to support the capture, retrieval, and dissemination of knowledge for member
arXiv:2608.19487v1 Announce Type: cross Abstract: Python is widely used in scientific research because it enables rapid development and provides rich ecosystems for data analysis, artificial intellige
arXiv:2608.19836v1 Announce Type: cross Abstract: Probabilistic shielding is a technique for safe reinforcement learning (RL). Typically, a static observer -- called the shield -- constrains the learn
arXiv:2608.20038v1 Announce Type: cross Abstract: Artificial intelligence can support cultural heritage and digital humanities through large-scale retrieval and analysis of digitized collections. Howe
arXiv:2608.19437v1 Announce Type: cross Abstract: Many benchmarks track Large Language Model (LLM) performance on tasks with verifiable answers, but less is known about how LLM performance is evolving
arXiv:2608.20122v1 Announce Type: new Abstract: Large multimodal models (LMMs) have demonstrated strong OCR recognition capabilities, yet remain vulnerable to adversarial visual text that is readable
arXiv:2608.19567v1 Announce Type: new Abstract: While text-to-3D generation has advanced rapidly, achieving high geometric fidelity at low inference cost remains challenging. Existing text-to-3D metho
arXiv:2608.20305v1 Announce Type: new Abstract: Myocardial scar segmentation from single-stack late gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging has been a longstanding and clinica
arXiv:2608.20271v1 Announce Type: new Abstract: The rapid proliferation of memecoins on blockchain platforms has increased the risk of fraudulent activities, particularly rug pulls. While previous stu
arXiv:2608.20019v1 Announce Type: new Abstract: Incomplete multimodal sentiment analysis has garnered significant attention in recent years. Existing approaches typically assume that data is missing a
arXiv:2608.19783v1 Announce Type: new Abstract: Existing optimal transport (OT) models primarily seek an OT map or plan between distributions by minimizing a prescribed transport cost or distortion. H
arXiv:2608.19366v1 Announce Type: cross Abstract: Mission-critical intelligent systems often operate under time-varying limitations that reduce control authority and change the admissible safe operati
arXiv:2608.19653v1 Announce Type: cross Abstract: Autonomous agents for machine learning experimentation must navigate heterogeneous repositories, repair training pipelines, and evaluate candidate imp
arXiv:2510.01192v2 Announce Type: replace-cross Abstract: Emulating empathy in human-robot interaction is a key component for achieving satisfying social, trustworthy, and ethical robot interaction wi
arXiv:2506.18779v2 Announce Type: replace Abstract: Deformable object manipulation is a key capability in many robotic applications. A promising paradigm for this problem is shape servoing, which aims
arXiv:2603.21875v2 Announce Type: replace-cross Abstract: Speech deepfake source verification systems aims to determine whether two synthetic speech utterances originate from the same source generator
arXiv:2608.19579v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in high-stakes applications, yet their tendency to generate toxic, harmful, or policy-violating c
arXiv:2608.19490v1 Announce Type: cross Abstract: State-of-the-art vision-language-action (VLA) models such as pi_{0.5} exhibit strong semantic understanding, instruction following and task behavior.
FireRedAudio: A General-Purpose Audio Language Model with Decoupled Continuous Representations for Understanding and Generation HuggingFace : https://huggingface.co/FireRedTeam/FireRedAudio GitHub : h
arXiv:2608.19758v1 Announce Type: new Abstract: Long-context modeling is a pivotal capability for Large Language Models, yet the quadratic complexity of attention remains a critical bottleneck, partic
arXiv:2608.19535v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves language-model responses by grounding generation in external passages, which comes with overhead: retrieve
arXiv:2608.20056v1 Announce Type: new Abstract: Inertial measurement units (IMUs) are now standard in most consumer devices, such as smartphones, drones, and extended reality (XR) headsets. By fusing
arXiv:2608.19206v1 Announce Type: cross Abstract: Contemporary Large Language Models (LLMs) are increasingly aligned to suppress hallucinations, prioritizing factual retrieval over combinatorial creat
arXiv:2608.19407v1 Announce Type: cross Abstract: Deep Learning models can include billions of parameters or more, making it difficult to explain their internal transformations and outputs. However, e
In any organizational behavior class, students will learn that effective delegation is among the most important skills for a seasoned leader. Getting meaningful work done involves careful coordination
arXiv:2608.19443v1 Announce Type: new Abstract: Thanks to its parallelizability and flexibility, sampling-based Model Predictive Control (MPC) has become widely popular for controlling real-world robo
arXiv:2608.19514v1 Announce Type: cross Abstract: Persistent intelligent systems require the ability to learn continually, but current machine learning approaches face significant challenges in this a
arXiv:2603.18853v3 Announce Type: replace-cross Abstract: Autonomous aerial vehicles (AAVs) enable data collection for sixth-generation Internet-of-Things networks, but their trajectories couple nonli
arXiv:2505.05203v3 Announce Type: replace-cross Abstract: With the increasing penetration of renewable energy and inverter-based resources, traditional physics-based power-system operation faces growi
arXiv:2608.19953v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) is a fundamental problem class in operations research and combinatorial optimization, with broad applications to
arXiv:2608.20061v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures significantly expand model capacity without a proportional increase in computational cost. However, optimizing
arXiv:2608.19522v1 Announce Type: cross Abstract: Scan-to-map LiDAR odometry drifts unboundedly along the unobservable axes of geometrically degenerate environments like tunnels and corridors, and exi
arXiv:2608.19800v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) is a prominent fine-tuning method for large models, achieving competitive performance with reduced memory overhead. However
arXiv:2608.19278v1 Announce Type: cross Abstract: The most capable general-purpose AI (GPAI) models are mostly built in two jurisdictions, the United States and China, but the risks they carry land gl
arXiv:2512.06754v2 Announce Type: replace Abstract: Continuum manipulators offer intrinsic dexterity and safe geometric compliance for navigation within confined and obstacle-rich environments. Howeve
NEW from me in the Guardian -- I agree with the AI company employees who wrote, in their 'Pacing the Frontier' letter, that the government should be stepping in. But companies could also be doing more
arXiv:2608.19741v1 Announce Type: new Abstract: Recent agent benchmarks increasingly ground evaluation in executable environments, from code repair to web navigation, app APIs, and function calling. Y
arXiv:2608.19646v1 Announce Type: new Abstract: Visual understanding in sports has emerged as a hot topic in computer vision in recent years. Most existing basketball video datasets adopt single actio
arXiv:2608.20240v1 Announce Type: new Abstract: X-band SAR satellites (8-12 GHz) play a critical role in disaster response, environmental monitoring, and military intelligence. Yet, they lack robust p
arXiv:2608.19890v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) methods aim to bridge the domain gap between the source and target domains. However, traditional TTA methods become ineffecti
arXiv:2510.07758v3 Announce Type: replace Abstract: Sharpness (of the loss minima) is widely believed to be a good indicator of generalization of neural networks. Unfortunately, the correlation betwee
arXiv:2608.19693v1 Announce Type: new Abstract: Sparse keypoint extraction and matching underpin core tasks in geometric computer vision, including structure-from-motion, visual SLAM, augmented realit
arXiv:2608.19214v1 Announce Type: new Abstract: The berth allocation and quay crane assignment problem (BACAP) is a representative port-terminal scheduling problem in maritime transportation and freig
arXiv:2608.19669v1 Announce Type: new Abstract: Latent reasoning has advanced multimodal reasoning through a two-stage training paradigm: (1) a helper image is encoded into latent tokens to teach visu
arXiv:2608.19298v1 Announce Type: new Abstract: Map matching is a key technology connecting positioning data with high precision road networks, but it faces challenges in noise robustness, cross regio
arXiv:2608.19838v1 Announce Type: new Abstract: Spec Driven Development SDD has consolidated the idea that the specification rather than the code should be the primary artefact governing AI assisted w
arXiv:2608.20104v1 Announce Type: cross Abstract: Artificial immune networks (AINs) are naturally memory-forming systems, but conventional visual AINs often rely on flattened vector affinity that igno
arXiv:2601.18305v2 Announce Type: replace Abstract: Despite numerous Graphical User Interface (GUI) agents claiming to automate user interaction tasks, to date, few achieve satisfactory interaction ca
arXiv:2403.15509v3 Announce Type: replace-cross Abstract: Knowledge distillation (KD) has been widely used to improve lightweight AI models by transferring soft-label knowledge from a large teacher mo
The sense of touch is the most criminally under-explored modality in robotics. Imagine doing sleight of hand wearing thick oven mitts. That's exactly how a robot feels today if it were alive. A magnet
arXiv:2608.20201v1 Announce Type: new Abstract: Software form has undergone two paradigm shifts since its inception: Software 1.0, in which instructions determine behavior, and Software 2.0, in which
arXiv:2608.19218v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are increasingly being explored for domain-specific maintenance and prognostics tasks, raising the
arXiv:2511.20973v2 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) deliver strong performance across speech and audio tasks, but their audio encoders generate high-rate toke
arXiv:2608.19794v1 Announce Type: new Abstract: The convergence of large language models (LLMs), structured knowledge bases (KBs), and reasoning ability (RA) presents a promising trajectory toward gen
arXiv:2608.19234v1 Announce Type: new Abstract: Decision-making in complex systems often involves dealing with imprecise or uncertain information, frequently represented using fuzzy sets, particularly
arXiv:2608.20212v1 Announce Type: new Abstract: High-fidelity removal of eyeglasses from video is a major challenge in facial attribute editing, as the underlying facial geometry is often obscured by
arXiv:2608.18572v1 Announce Type: cross Abstract: Tactile Internet services couple cyber events directly to physical actuation, so security decisions must improve risk discrimination without perturbin
arXiv:2608.19644v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) incur high memory traffic and energy costs because sampling repeatedly evaluates large denoisers dominated by linear opera
arXiv:2608.19208v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are frequently exposed to auxiliary textual context, the impact of which on visually grounded tasks remains und
arXiv:2509.04222v2 Announce Type: replace Abstract: Dimensionality Reduction (DR) is widely used for visualizing high-dimensional data, often with the goal of revealing expected cluster structure. How