Knowledge catalogue
arXiv:2608.05976v1 Announce Type: new Abstract: Recently, diffusion models have made great progress in video generation. However, most existing video diffusion models are trained with short videos, an
arXiv:2608.06110v1 Announce Type: new Abstract: This paper presents ECHO (Enhanced Care & Health Observer), a locally-deployable conversational health assistant for long-term chronic care management.
arXiv:2608.06208v1 Announce Type: new Abstract: Contact-centric tasks on surfaces, ranging from inspection and cleaning to sanding and polishing, require robots to systematically cover the surface whi
arXiv:2608.06332v1 Announce Type: new Abstract: Generalist robot policies exhibit strong capabilities, but their robustness in complex and unseen environments remains limited. Scaling robot learning a
arXiv:2608.05422v1 Announce Type: new Abstract: While many algorithms blend reinforcement learning (RL) with counterfactual regret (CFR) methods to leverage tradeoffs in computational speed and perfor
arXiv:2608.06122v1 Announce Type: cross Abstract: Inspired by recent evidence that transformer architectures benefit from Self-PreTraining (SPT) on long-context benchmarks, we investigate whether simi
arXiv:2608.05798v1 Announce Type: new Abstract: Latent diffusion modeling (LDM), a prominent paradigm, utilizes tokenizers to map input signal to compressed representation. This dependency positions t
arXiv:2608.06253v1 Announce Type: new Abstract: Metabolomics knowledge is distributed across heterogeneous resources and remains difficult to translate into predictive representations. We developed Me
arXiv:2608.05430v1 Announce Type: cross Abstract: The remarkable instruction-following ability of modern LLMs has enabled their practical use as the minds of agents that can autonomously complete incr
arXiv:2507.03631v4 Announce Type: replace Abstract: Extracting interpretable mathematical models from complex dynamical systems is difficult, especially for chaotic dynamics observed with noisy experi
arXiv:2608.05439v1 Announce Type: new Abstract: Translating natural language instructions into machine-interpretable formal specifications enables robots and autonomous systems to plan, reason, and fo
arXiv:2608.06346v1 Announce Type: new Abstract: LLM-based agentic systems have shown remarkable capabilities in complex domains, while suffering from cascading errors and difficulty in debugging. Crit
arXiv:2504.13621v2 Announce Type: replace Abstract: Visual grounding associates textual descriptions with objects in an image. Conventional methods target third-person image inputs and named object qu
arXiv:2608.05215v1 Announce Type: cross Abstract: Learning manipulation skills from human videos is promising for scalable robot learning. However, the embodiment mismatch between humans and robots ma
arXiv:2608.04945v1 Announce Type: cross Abstract: The emergence of the ISO standard GQL introduces a powerful query language extending first-order logic with controlled recursion, raising the question
arXiv:2608.04305v1 Announce Type: new Abstract: Risk-aware Q-learning (RaQL) provides a model-free, two-timescale estimator for dynamic risk objectives, but its finite-budget behavior remains fragile:
The intersection of medicine and AI has led to remarkable innovations. However, developers now face the thorny challenge of building robust medical AI tools that have been tested and evaluated on dive
arXiv:2608.04753v1 Announce Type: new Abstract: Attention layers are the backbone of today's most powerful and impactful models. Models with multi-million and billion parameters rely on contextual kno
arXiv:2607.16868v2 Announce Type: replace Abstract: Large Language Models often produce confidently stated yet unreliable outputs, posing critical challenges for deployment in safety-sensitive applica
arXiv:2601.12401v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has emerged as a powerful paradigm for fine-tuning large-scale generative models, such as diffusion and flow model
arXiv:2608.05042v1 Announce Type: new Abstract: Leveraging pre-trained vision-language models (VLMs) to construct vision-language-action (VLA) models has emerged as a promising paradigm for 3D robot m
arXiv:2608.04865v1 Announce Type: new Abstract: Event cameras, also known as neuromorphic cameras, have gained significant attention in recent years due to their high temporal resolution, high dynamic
arXiv:2608.04655v1 Announce Type: cross Abstract: Curvilinear structure analysis is an important and fundamental task in multimedia. However, the controllable generation of images with precise curvili
arXiv:2602.07453v2 Announce Type: replace Abstract: Decision tree ensembles are widely used in critical domains, making robustness and sensitivity analysis essential to their trustworthiness. We study
arXiv:2601.20985v2 Announce Type: replace Abstract: Optimal control of complex environments with robotic systems faces two complementary and intertwined challenges: efficient organization of sensory s
arXiv:2604.05087v3 Announce Type: replace Abstract: Document expansion is a classical technique for improving retrieval quality, and is attractive since it shifts computation offline, avoiding additio
DXC Technology Co. today announced a partnership with security startup Primary that makes the information technology services company the exclusive managed services partner for Primary’s zero-trust pl
arXiv:2608.04472v1 Announce Type: cross Abstract: The development of foundation models (FMs) is crucial for advancing endoscopic image analysis. However, existing endoscopy FMs mainly rely on self-sup
A regulated customer needed all Claude Code inference processed in a single AWS Region (London), not just in-geography. This post shows two ways to pin Claude Code on Amazon Bedrock to one Region: an
arXiv:2608.04885v1 Announce Type: cross Abstract: Standard accuracy metrics for VLMs often mask significant reliability failures in sensitive domains. In this work, we utilize a histopathology-validat
arXiv:2507.03897v3 Announce Type: replace Abstract: We introduce GenAI-Powered Inference (GPI), a statistical framework for both causal and predictive inference using unstructured data, including text
arXiv:2503.06396v2 Announce Type: replace Abstract: The minimum vertex cover (MVC) problem seeks to identify the smallest set of vertices that cover all edges in an undirected graph. As a fundamental
Huge congratulations to @JeffDean and the legendary founding team on the launch! 🚀 I share a deep conviction in this mission. Automating the scientific method will profoundly alter the trajectory of A
arXiv:2603.12408v3 Announce Type: replace-cross Abstract: Motion imitation learning (IL) is increasingly used in robotics and human gait modeling, yet its ability to recover biomechanically consistent
arXiv:2604.01730v2 Announce Type: replace Abstract: This paper investigates Koopman operator-based approaches for multivariable control of a two-spool turbofan engine. A physics-based component-level
arXiv:2608.05054v1 Announce Type: cross Abstract: We investigate the transferability of Earth weather foundation models to planetary atmospheres by adapting the GraphCast graph neural weather forecast
arXiv:2608.04624v1 Announce Type: cross Abstract: Current neural networks for beat tracking generate invalid outputs, such as consecutive downbeats and erratic tempo changes, even when these are not p
arXiv:2608.04205v1 Announce Type: new Abstract: Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract aw
arXiv:2510.21084v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown strong potential for clinical decision support through their advanced language understanding and reaso
arXiv:2509.08604v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-traini
arXiv:2608.04407v1 Announce Type: cross Abstract: Memory-efficient matrix optimizers such as Sinkhorn gradient descent remove most AdamW optimizer state for dense Transformer matrices, but direct appl
arXiv:2506.02260v4 Announce Type: replace-cross Abstract: Wearable devices enable continuous multi-modal physiological and behavioral monitoring, yet analysis of these data streams faces fundamental c
arXiv:2608.04054v1 Announce Type: cross Abstract: Multimodal intent recognition requires understanding not only what textual, acoustic, and visual signals share, but also how they disagree. Such disag
arXiv:2608.04144v1 Announce Type: cross Abstract: Biomedical entity linking grounds mentions in clinical and scientific text to entities in a curated knowledge base (KB) with ontological structure, wh
arXiv:2608.04397v1 Announce Type: new Abstract: We introduce NOLLI, a procedurally generated English-Korean puzzle benchmark designed to diagnose where Korean performance gaps arise. It comprises 15 p
arXiv:2608.04860v1 Announce Type: cross Abstract: This paper develops procedures for nonparametric goodness-of-fit testing under covariate shift, where labelled data are drawn from a source population
arXiv:2608.04776v1 Announce Type: new Abstract: The ability to accurately assess and anticipate risks in safety-critical scenarios is crucial for autonomous driving systems. While existing research ha
arXiv:2608.04030v1 Announce Type: cross Abstract: Generative artificial intelligence (AI) has transformed text-to-image synthesis, yet its ability to represent specialized engineering domains remains
NVIDIA Nemotron Parse 2.0 transforms document images into structured, machine-readable representations with text, layout classes, bounding boxes, and reading-order information. Given a Red, Green, Blu
arXiv:2505.19840v3 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) have achieved widespread success yet remain prone to adversarial attacks. Typically, such attacks either involve f
arXiv:2608.01791v2 Announce Type: replace-cross Abstract: The rapid development of photonic integrated circuits (PICs) is shifting the design flow from traditional graphical user interface (GUI)-based
arXiv:2608.04995v1 Announce Type: new Abstract: Animal pose estimation and tracking is important for wildlife monitoring and conservation research, and with limited expert time for labelling automated
arXiv:2608.05110v1 Announce Type: cross Abstract: Near-term quantum hardware limits circuit depth and often imposes geometrically local connectivity for quantum generative models, restricting the outp
arXiv:2608.04442v1 Announce Type: cross Abstract: Robustness to natural corruptions remains a fundamental challenge for deep neural networks. In this paper, we identify a robustness fading phenomenon
arXiv:2507.05173v2 Announce Type: replace Abstract: Generating intermediate video content of varying lengths based on given first and last frames, along with text prompt information, offers significan
arXiv:2608.04075v1 Announce Type: cross Abstract: Accurate traffic forecasting is essential for proactive resource management in edge computing, where service demand evolves dynamically across both sp
arXiv:2608.04676v1 Announce Type: new Abstract: Surgical procedures unfold as structured and recurring clinical events, whose real-time understanding via intraoperative surgical videos is critical for
arXiv:2608.05138v1 Announce Type: cross Abstract: Modern Greek is absent from NVIDIA's Nemotron retrieval models and from major multilingual retrieval benchmarks, despite being important for retrieval
arXiv:2503.15560v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly vulnerable to sophisticated multi-turn manipulation attacks, where adversaries strategically build conte
arXiv:2608.04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statis