Knowledge catalogue
arXiv:2607.07962v1 Announce Type: cross Abstract: Inferring latent physical properties from sensory observations is a fundamental challenge in machine perception. Among available sensing modalities, t
arXiv:2607.08555v1 Announce Type: new Abstract: The operational integrity of complex industrial systems relies on precise anomaly detection and diagnosis. The vast majority of existing methods narrowl
arXiv:2402.07407v3 Announce Type: replace-cross Abstract: We propose conformal predictive programming (CPP), a framework to solve chance constrained optimization problems, i.e., optimization problems
arXiv:2607.07721v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) and agentic frameworks have advanced enterprise AI considerably, yet agents remain fundamentally reactive: they wai
arXiv:2407.13632v2 Announce Type: replace Abstract: Deploying deep learning-based imaging tools across various clinical sites poses significant challenges due to inherent domain shifts and regulatory
arXiv:2607.07817v1 Announce Type: cross Abstract: We present DreamCharacter-1, a lightweight post-adaptation framework that calibrates pretrained 3D foundation models toward high-fidelity, production-
arXiv:2607.08092v1 Announce Type: cross Abstract: Privacy-preserving clustering is critical for analyzing sensitive data in healthcare, cybersecurity, and enterprise applications, where maintaining da
arXiv:2607.07773v1 Announce Type: cross Abstract: EEG-based emotion recognition is critical for mental health monitoring and affective brain-computer interfaces, yet existing deep learning approaches
arXiv:2607.08249v1 Announce Type: new Abstract: Slot attention is a powerful framework for object-centric learning, decomposing visual scenes into latent slots through iterative competitive attention.
This post discusses the conceptual distinction between training-scaling and inference-scaling in machine learning models, while acknowledging related frameworks or concepts (possibly referencing Sol,
arXiv:2607.08189v1 Announce Type: cross Abstract: Safe navigation in dynamic environments is challenging when system dynamics are unknown and actuator inputs are limited. Existing methods either rely
arXiv:2607.08374v1 Announce Type: cross Abstract: Personality recognition has traditionally been constrained by theory-dependent formulations, where models are trained to fit predefined psychological
arXiv:2505.19422v2 Announce Type: replace Abstract: We present extbf{LlamaSeg}, a visual autoregressive framework that unifies multiple image segmentation tasks via natural language instructions. By r
arXiv:2607.08012v1 Announce Type: cross Abstract: This paper studies an online variant of the assistance games framework, where an informed agent and an uninformed agent repeatedly interact over T tim
arXiv:2607.08003v1 Announce Type: cross Abstract: Catalysts are essential for sustainable chemical manufacturing, yet discovering novel architectures remains a bottleneck dominated by trial-and-error
arXiv:2607.07895v1 Announce Type: new Abstract: Research on stereotypes in large language models (LLMs) has largely focused on English-speaking contexts, due to the lack of datasets in other languages
arXiv:2607.07735v1 Announce Type: cross Abstract: Sparse precision matrix estimation provides an interpretable and computationally efficient framework for modeling conditional dependencies in high-dim
arXiv:2607.08075v1 Announce Type: new Abstract: Unmanned Aerial Vehicle (UAV) videos are widely used in traffic monitoring, urban management, and emergency rescue. However, existing UAV video percepti
arXiv:2607.06893v1 Announce Type: cross Abstract: The Stochastic-Oracle Turing Machine (SOTM) framework models AI-augmented computation as the interaction of a probabilistic Turing machine with an ora
arXiv:2607.06610v1 Announce Type: cross Abstract: Portfolio optimization under uncertainty is inherently a multi-objective decision problem involving complex interactions among return, risk, market dy
arXiv:2604.02915v2 Announce Type: replace Abstract: We present GP-4DGS, a novel framework that integrates Gaussian Processes (GPs) into 4D Gaussian Splatting (4DGS) for principled probabilistic modeli
arXiv:2607.07034v1 Announce Type: cross Abstract: We introduce Intrinsic Green's Learning (IGL), a framework that models a target function on a manifold as the solution to a linear PDE whose source te
arXiv:2607.07027v1 Announce Type: cross Abstract: While generative models enable encoding of complex neuroimaging data for feature generation and reconstruction, developing optimal architectural frame
arXiv:2607.07136v1 Announce Type: new Abstract: This paper presents a Spatiotemporal Tube (STT)-based control framework for general unknown nonlinear Euler-Lagrange (EL) systems subject to input const
This X thread discusses lore and discussions within the MooTools developer community, likely referencing internal dynamics, historical events, or notable figures in the MooTools JavaScript framework e
arXiv:2601.14271v2 Announce Type: replace Abstract: Shared accountability records are often used by parties who may never agree about causation, responsibility, or normative interpretation. For such r
arXiv:2603.23800v2 Announce Type: replace-cross Abstract: We present a novel LLM-informed model-based planning framework, and a novel prompt selection method, for object search in partially-known envi
arXiv:2505.19033v2 Announce Type: replace-cross Abstract: Conformal prediction (CP) is a widely used frequentist framework to quantify uncertainty by constructing prediction sets with user-specified m
arXiv:2607.07318v1 Announce Type: new Abstract: Rigorous content moderation is crucial for online advertising but leads to millions of daily rejections. This scale renders manual rectification infeasi
arXiv:2511.06667v2 Announce Type: replace-cross Abstract: With the explosive growth of rigid-body simulators, policy learning in simulation has become the de facto standard for most rigid morphologies
arXiv:2512.17648v2 Announce Type: replace Abstract: Streaming Speech-to-Text Translation (StreamST) requires producing translations concurrently with incoming speech under strict latency constraints,
arXiv:2607.06915v1 Announce Type: new Abstract: Scaling down the resolution of input images can greatly reduce the computational overhead of convolutional neural networks (CNNs), which is promising fo
arXiv:2607.07468v1 Announce Type: cross Abstract: We study the recovery of sparse functions from finite, noisy, and indirect observations in the framework of statistical inverse learning. The unknown
NVIDIA's NeMo framework addresses the challenge of limited, imbalanced financial NLP data by generating synthetic financial news headlines to fill gaps for trading research, risk modeling, and surveil
arXiv:2607.07169v1 Announce Type: new Abstract: The precise pixel-level localization of 2D material flakes is crucial for high-throughput screening. However, traditional fully supervised methods rely
arXiv:2607.06841v1 Announce Type: cross Abstract: Diffusion models offer a powerful framework for sampling from complex probability densities by learning to reverse a noising process. A common approac
arXiv:2603.27742v2 Announce Type: replace Abstract: Vision-language agents that orchestrate specialized tools for image restoration (IR) have emerged as a promising method, yet most existing framework
arXiv:2607.07438v1 Announce Type: new Abstract: Action Quality Assessment (AQA) aims to evaluate how well a person performs a movement, which is essential in applications such as sports scoring, skill
arXiv:2601.17257v2 Announce Type: replace Abstract: We introduce a constrained optimization framework for training transformers that behave like optimization descent algorithms. Specifically, we enfor
arXiv:2607.06291v1 Announce Type: new Abstract: Game worlds have traditionally been built through labor-intensive production pipelines, making them costly to develop, difficult to customization, and e
arXiv:2607.06413v1 Announce Type: cross Abstract: Large language model coding agents increasingly perform open-ended data modeling and analysis. These agents are stochastic and adaptive, and therefore
arXiv:2607.05625v1 Announce Type: new Abstract: Wound monitoring is a critical yet underserved clinical challenge, where timely identification of severe adverse events (SAEs) such as infection, tissue
arXiv:2511.06229v3 Announce Type: replace Abstract: This paper focuses on dynamic origin-destination matrix estimation (DODE), a crucial calibration process necessary for the effective application of
arXiv:2607.05665v1 Announce Type: new Abstract: This study proposes a neural network-based transfer learning framework for modeling the dynamics of soft, fin-actuated underwater robots. We focus on mo
arXiv:2607.06150v1 Announce Type: new Abstract: Reliable seam segmentation is essential for autonomous robotic welding in construction, where harsh illumination, specular reflections, and thin weld ge
arXiv:2509.07162v2 Announce Type: replace Abstract: Autonomous multi-finger grasping is a fundamental capability in robotic manipulation. Optimization-based approaches show strong performance, but ten
arXiv:2607.05758v1 Announce Type: cross Abstract: Automated experimentation is moving from closed-loop optimization toward open decision-making, where human or AI planners must forecast the consequenc
arXiv:2607.05563v1 Announce Type: new Abstract: Interpretable explanation methods in Artificial Intelligence aim to uncover the underlying causes and their effects, enabling a deeper understanding of
In the agentic era, AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in this next phase of AI need computing infrastructure that’s designed and optimi
Google updated Android Bench in July 2026 by adopting the Harbor framework and adding eight new models including Claude Fable 5, Claude Sonnet 5, and others to its LLM leaderboard for Android developm
arXiv:2607.05585v1 Announce Type: cross Abstract: FaceMesh2HPO is a framework for classifying facial phenotypic descriptors aligned with the Human Phenotype Ontology (HPO) to support clinical diagnosi
Harrison Chase and Jensen Huang discuss LangChain's latest announcements, including strategic blueprints for agent systems, the company's direction toward open-source agent frameworks, and initiatives
arXiv:2607.06501v1 Announce Type: new Abstract: We consider an open-world planning setting in which service robots must operate in unknown environments with incomplete knowledge of objects and actions
Mistral AI has developed a unified robotic control system or framework that operates across multiple robot morphologies—including wheeled, legged, and flying variants—while generalizing across differe
arXiv:2607.05903v1 Announce Type: cross Abstract: We present K-ABENA (K-Adaptive Backpropagation with Error-based N-exclusion Algorithm), a selective gradient computation framework that reduces per-it
arXiv:2607.06287v1 Announce Type: cross Abstract: We study kernel-based operator learning in a two-stage sampling framework, where an offline kernel regression operator learns a discretized representa
arXiv:2607.06529v1 Announce Type: new Abstract: Fine-scale socioeconomic information is often unavailable across rapidly ur-banizing regions of the developing world, like India, limiting the ability t
This X post shares a link to a ComfyUI workflow hosted on comfy.org, likely demonstrating a specific node setup or process for image generation or manipulation using the ComfyUI framework. The workflo
NVIDIA has integrated Isaac Teleop, LeRobot v0.6.0, and NVIDIA Isaac GR00T N1.7 to enable advanced robotic teleoperation and control capabilities. This integration combines NVIDIA's robotics framework
arXiv:2607.06348v1 Announce Type: new Abstract: We introduce a physics-informed framework for learning finite-dimensional embeddings of solution families of partial differential equations. The method