Knowledge catalogue
arXiv:2607.03754v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) target segmentation remains challenging due to the small size of objects, appearance variations, cluttered backgrounds, an
arXiv:2607.02630v1 Announce Type: cross Abstract: Hardware accelerators now sit on the critical path of online serving. GPUs, FPGAs, and increasingly remote services such as hardware security modules,
arXiv:2607.04315v1 Announce Type: cross Abstract: This paper studies the problem of identifying the treatment that maximizes the expected natural direct potential outcome (NDPO), which captures the po
arXiv:2607.05201v1 Announce Type: new Abstract: In non-stationary streaming environments, simultaneously adapting to complex, non-linear domain shifts via continual learning while mitigating the catas
arXiv:2607.05261v1 Announce Type: new Abstract: We present FlowMark, a video watermarking framework guided by automatically predicted object masks. In contrast to prior region-based approaches that re
arXiv:2607.03661v1 Announce Type: new Abstract: Point cloud-based understanding has become an important enabler for facility operation and maintenance involving indoor building components. However, ex
arXiv:2607.05176v1 Announce Type: new Abstract: Small object detection (SOD) remains a challenging task in real-world applications. Despite recent advances, existing detectors remain limited by rigid
arXiv:2607.03254v1 Announce Type: new Abstract: Integrated sensing and communication (ISAC) enables intelligent wireless infrastructure but raises growing regulatory concern as fine-grained personal t
arXiv:2607.05153v1 Announce Type: cross Abstract: Scientists often seek to draw causal inferences from structured data that is not independently and identically distributed, such as spatial data, netw
arXiv:2607.04714v1 Announce Type: cross Abstract: Learning motion latents for robotic manipulation heavily relies on extracting motion patterns from visual sequences, yet effective action abstractions
arXiv:2511.23191v2 Announce Type: replace Abstract: Previous works that leverage video models for image-to-3D scene generation often suffer from geometric distortions and blurry content. Using video g
arXiv:2508.03750v2 Announce Type: replace-cross Abstract: Early and accurate glaucoma detection is critical to prevent irreversible vision loss, yet existing AI methods often rely on unimodal inputs a
arXiv:2602.21009v2 Announce Type: replace-cross Abstract: Modern recommender systems leverage ultra-long user behavior sequences to capture dynamic preferences, but end-to-end modeling is infeasible i
AWS Finance used Amazon Quick chat agents and Flows to automate two major time-consuming workflows: financial target setting and weekly business reviews. The automation reduced target-setting time fro
arXiv:2607.04554v1 Announce Type: new Abstract: Dexterous grasping across diverse object scales requires contact modes ranging from two-finger pinches to bimanual grasps. Existing dexterous grasp synt
arXiv:2607.04811v1 Announce Type: new Abstract: Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and qualit
I have been playing these world models/games since the first diffusion DOOM, and multiplayer at 20 FPS is pretty neat. 'A dream of rocket league,' indeed. Introducing MIRA. A playable, multiplayer wor
arXiv:2510.24936v3 Announce Type: replace Abstract: Wi-Fi sensing is a leading technology for Human Activity Recognition (HAR), offering a non-intrusive and cost-effective solution for healthcare and
IBM Corp. today announced a massive expansion of its on-premises enterprise infrastructure lineup, with new single-frame and rack-mount versions of its iconic z17 mainframes and more compact LinuxONE
arXiv:2607.04735v1 Announce Type: cross Abstract: When data sources are integrated through a shared interface, a downstream query may or may not be determined by what the interface exposes: two global
arXiv:2607.04146v1 Announce Type: cross Abstract: This work establishes that trigger-word data poisoning of vision language action models is practical, while at the same time the open-source robotics
arXiv:2607.05009v1 Announce Type: cross Abstract: Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly
arXiv:2607.03289v1 Announce Type: new Abstract: When designing robots' nonverbal behaviors, many researchers have turned to arts-based insights, such as Disney's Animation Principles. Yet, while these
arXiv:2607.03217v1 Announce Type: new Abstract: Uncertainty quantification of hydrological predictions is necessary to inform operational decisions. Recent generative machine-learning methods have adv
arXiv:2602.08842v3 Announce Type: replace-cross Abstract: As highly automated driving is transitioning from single-vehicle closed-access testing to commercial deployments of public ride-hailing in sel
arXiv:2607.02609v1 Announce Type: cross Abstract: For decades, data engineering has developed mature architectural principles for integrating, governing, validating, cataloging, and serving organizati
arXiv:2607.04447v1 Announce Type: new Abstract: Local causal discovery is a scalable alternative to global structure learning. However, it can struggle to identify valid adjustment sets in data-scarce
arXiv:2607.02850v1 Announce Type: new Abstract: Meta-learning without labeled data is crucial for real-world applications, where obtaining labeled datasets can be expensive or restricted due to privac
arXiv:2507.08905v2 Announce Type: replace-cross Abstract: We explore the use of Hamiltonian Monte Carlo (HMC) sampling as a probabilistic last layer approach for deep neural networks (DNNs). While HMC
arXiv:2607.03204v1 Announce Type: new Abstract: In this study, we propose a layout-independent control allocator capable of zero-shot deployment across diverse actuator configurations. The proposed me
arXiv:2607.04643v1 Announce Type: new Abstract: Video quality assessment (VQA) plays a critical role in optimizing video delivery systems. While numerous objective metrics have been proposed to approx
arXiv:2602.09530v2 Announce Type: replace-cross Abstract: We introduce AutoSpec, a neural network framework for discovering iterative spectral algorithms for large-scale numerical linear algebra and n
arXiv:2607.03350v1 Announce Type: cross Abstract: Malicious Python packages have become a major threat to software supply chain ecosystems due to the widespread adoption of open-source repositories su
arXiv:2607.03072v1 Announce Type: cross Abstract: Simulation is essential for maritime robotics, supporting operator training, mission rehearsal, and human-vehicle interaction in environments where re
arXiv:2607.04648v1 Announce Type: cross Abstract: Depression screening from large-scale behavioral data is challenged by fragmented circadian indicators, limited interpretability, and the lack of inte
arXiv:2607.03875v1 Announce Type: new Abstract: Close-up rendering, zooming into a scene well beyond any training camera, is important for virtual production and interactive 3D content, yet remains an
arXiv:2607.04133v1 Announce Type: new Abstract: Causal discovery with nonlinear mechanisms and latent confounders remains challenging. Existing methods often rely on either linear assumptions or causa
arXiv:2503.17577v2 Announce Type: replace-cross Abstract: Deepfakes have emerged as a widespread and rapidly escalating concern in generative AI, spanning images, audio, and videos. Among these, audio
arXiv:2510.22298v2 Announce Type: replace-cross Abstract: Uncovering the causal mechanisms of complex real-world systems remains a significant challenge, as these systems often entail high data collec
arXiv:2601.22054v2 Announce Type: replace-cross Abstract: Scaling has powered recent advances in vision foundation models, yet extending this paradigm to metric depth estimation remains challenging du
arXiv:2607.05069v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) improves factuality by grounding LLMs in external evidence, but real-world retrieval is often polluted: semanticall
arXiv:2504.16738v3 Announce Type: replace-cross Abstract: Planning long-horizon manipulation motions using a set of predefined skills is a central challenge in robotics; solving it efficiently could e
arXiv:2607.04972v1 Announce Type: cross Abstract: Deploying robot teams in the real world requires simultaneous adaptation to unseen environments, unknown partners, and varying team sizes, yet existin
Nomos Ai Inc., a company building a platform to embed legal operations into artificial intelligence agents, today announced it has raised 120 million in new funding, bringing the company’s valuation t
Guinevere Grant / Bloomberg: Norm, which runs an AI law firm that provides AI-powered legal services to clients alongside human lawyers, raised 120M led by Khosla at a 1.2B valuation — Norm Ai has rai
arXiv:2607.03758v1 Announce Type: new Abstract: Adversarial attacks on motion planning are crucial for evaluating and quantifying the intrinsic robustness of robotic manipulation. However, existing ap
arXiv:2607.04339v1 Announce Type: cross Abstract: Large generative models across text-to-text, text-to-image, and image-to-text modalities have been shown to pose significant privacy risks. One fundam
Wall Street Journal: OpenAI, Anthropic, and other top AI labs are offering startups token credits and special promotions, as the AI labs seek lasting streams of enterprise revenue — Pitched battle for
arXiv:2607.03200v1 Announce Type: new Abstract: Origin-destination (OD) flow prediction is central to urban analytics, yet deep models trained on raw counts remain vulnerable to distribution shift. Th
arXiv:2508.07033v2 Announce Type: replace Abstract: Embodied agents have shown promising generalization capabilities across diverse physical environments, making them essential for a wide range of rea
arXiv:2607.03349v1 Announce Type: cross Abstract: The accuracy of consumer-grade inertial navigation is bottlenecked by the stochastic noise of Micro-Electro-Mechanical Systems (MEMS). Traditional det
arXiv:2607.03581v1 Announce Type: cross Abstract: The widespread adoption of facial masks, accelerated by COVID-19 and mandated in security-sensitive settings, has exposed limitations of conventional
arXiv:2607.03372v1 Announce Type: new Abstract: A frozen vision-language-action model (VLA) receives recent observations at every decision step, yet prior work has focused on adding memory rather than
arXiv:2607.02632v1 Announce Type: cross Abstract: Time-series forecasting supports decisions in finance, en-ergy, transportation, public health, and industrial monitoring. Recent foundation models imp
arXiv:2607.03004v1 Announce Type: new Abstract: Open-World Object Detection (OWOD) requires detectors to identify previously unseen objects as unknown and incrementally incorporate them into the set o
arXiv:2607.03515v1 Announce Type: cross Abstract: In many machine learning applications, the most relevant items for a query should be efficiently retrieved. The relevance function is usually an expen
arXiv:2601.06542v2 Announce Type: replace-cross Abstract: In this paper, we investigate the Resource-Constrained Project Scheduling Problem (RCPSP) with Time-of-Use (TOU) energy tariffs and machine st
arXiv:2508.03177v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) recently achieve significant breakthroughs in understanding complex visual-textual contexts. However, hallucina
arXiv:2607.02628v1 Announce Type: new Abstract: While diffusion models have revolutionized image synthesis, their application to real-world inverse problems is often hampered by the need for massive d
arXiv:2507.06637v2 Announce Type: replace-cross Abstract: We propose Path Signatures Logistic Regression (PSLR), a semi-parametric framework for classifying vector-valued functional data with scalar c