Knowledge catalogue
arXiv:2604.20055v1 Announce Type: new Abstract: Hospital Quality Improvement (QI) plays a critical role in optimizing healthcare delivery by translating high-level hospital goals into actionable solut
arXiv:2604.19884v1 Announce Type: cross Abstract: Post-Training Quantization (PTQ) is critical for the efficient deployment of Large Language Models (LLMs). While 4-bit quantization is widely regarded
arXiv:2604.20046v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has revolutionized novel view synthesis with high-quality rendering through continuous aggregations of millions of 3D Gauss
arXiv:2604.01938v3 Announce Type: replace Abstract: The structure of all the permutations of a sequence can be represented as a permutohedron, a graph where vertices are permutations and two vertices
arXiv:2604.19786v1 Announce Type: new Abstract: Evaluating humor in large language models (LLMs) is an open challenge because existing approaches yield isolated, incomparable metrics rather than unifi
arXiv:2604.20307v1 Announce Type: new Abstract: In this paper, a deep learning framework is proposed for automatic facial emotion based on deep convolutional networks. In order to increase the general
arXiv:2604.19815v1 Announce Type: new Abstract: Drug repurposing is often framed as a candidate identification task, but existing approaches provide limited guidance for distinguishing biologically pl
arXiv:2604.20174v1 Announce Type: new Abstract: Reinforcement learning (RL) policies are typically trained for fixed objectives, making reuse difficult when task requirements change. We study inferenc
arXiv:2604.20650v1 Announce Type: new Abstract: 6D object pose estimation in cluttered scenes remains challenging due to severe occlusion and sensor noise. We propose MAPRPose, a two-stage framework t
arXiv:2604.19902v1 Announce Type: cross Abstract: We present MMCORE, a unified framework designed for multimodal image generation and editing. MMCORE leverages a pre-trained Vision-Language Model (VLM
arXiv:2604.19827v1 Announce Type: cross Abstract: Software engineering faces a fundamental challenge: multi-agent AI systems fail in ways that defy explanation by traditional theories. While individua
arXiv:2506.16658v2 Announce Type: replace-cross Abstract: Multi-armed bandit (MAB) is a widely adopted framework for sequential decision-making under uncertainty. Traditional bandit algorithms rely so
arXiv:2604.20283v1 Announce Type: new Abstract: Multimodal Entity Linking (MEL) is a fundamental task in data management that maps ambiguous mentions with diverse modalities to the multimodal entities
arXiv:2604.20115v1 Announce Type: cross Abstract: Bilevel optimization and bilevel minimax optimization have recently emerged as unifying frameworks for a range of machine-learning tasks, including hy
arXiv:2510.09574v2 Announce Type: replace Abstract: Autonomous navigation in unfamiliar environments requires robots to simultaneously explore, localise, and plan under uncertainty, without relying on
arXiv:2604.19832v1 Announce Type: cross Abstract: In a global derivatives market with notional values in the hundreds of trillions of dollars, the accuracy and efficiency of pricing models are of fund
arXiv:2604.20711v1 Announce Type: new Abstract: Artificial intelligence is increasingly deployed to synthesize large-scale public input in policy consultations and participatory processes. Yet no form
arXiv:2604.20175v1 Announce Type: cross Abstract: Accurate prediction of thermal runaway in lithium-ion batteries is essential for ensuring the safety, efficiency, and reliability of modern energy sto
arXiv:2604.20147v1 Announce Type: cross Abstract: Data-driven decision-making under uncertainty typically presumes the collection of historical data from an unknown target probability distribution. Ho
arXiv:2604.20169v1 Announce Type: new Abstract: We propose Semantic-Fast-SAM (SFS), a semantic segmentation framework that combines the Fast Segment Anything model with a semantic labeling pipeline to
arXiv:2604.20128v1 Announce Type: new Abstract: Fusing a low resolution (LR) mosaiced hyperspectral image (HSI) with a high resolution (HR) panchromatic (PAN) image offers a promising avenue for video
arXiv:2604.19841v1 Announce Type: cross Abstract: Accurate forecasting of electric vehicle (EV) charging demand is critical for grid management and infrastructure planning. Yet the field continues to
arXiv:2604.20022v1 Announce Type: cross Abstract: Large language models are increasingly deployed as autonomous diagnostic agents, yet they conflate two fundamentally different capabilities: natural-l
arXiv:2604.20688v1 Announce Type: cross Abstract: Storm surge forecasting remains a critical challenge in mitigating the impacts of tropical cyclones on coastal regions, particularly given recent tren
arXiv:2604.20188v1 Announce Type: new Abstract: Learning the underlying potential energy of stochastic gradient systems from partial and noisy observations is a fundamental problem arising in physics,
arXiv:2604.20156v1 Announce Type: new Abstract: Mixture-of-Experts models, now popular for scaling capacity at fixed inference speed, switch experts at nearly every token. Once a model outgrows availa
arXiv:2604.19803v1 Announce Type: new Abstract: Agentic AI is rapidly transforming the way research is conducted, from prototyping ideas to reproducing results found in the literature. In this paper,
arXiv:2604.20231v1 Announce Type: new Abstract: Connected autonomous vehicles (CAVs), which represent a significant advancement in autonomous driving technology, have the potential to greatly increase
arXiv:2604.19923v1 Announce Type: new Abstract: We introduce UniCon3R (Unified Contact-aware 3D Reconstruction), a unified feed-forward framework for online human-scene 4D reconstruction from monocula
arXiv:2604.20755v1 Announce Type: new Abstract: We introduce V-tableR1, a process-supervised reinforcement learning framework that elicits rigorous, verifiable reasoning from multimodal large language
arXiv:2604.20712v1 Announce Type: new Abstract: Peg-in-hole (PiH) assembly is a fundamental yet challenging robotic manipulation task. While reinforcement learning (RL) has shown promise in tackling s
arXiv:2604.20564v1 Announce Type: new Abstract: While LLMs demonstrate impressive reasoning capabilities, they remain fragile in multi-step logical deduction, where a single transition error can propa
arXiv:2603.22885v4 Announce Type: replace Abstract: BACKGROUND: General aviation fleet expansion demands intelligent health monitoring under computational constraints. Real-world aircraft health diagn
arXiv:2604.18889v1 Announce Type: new Abstract: We present AC-SINDy, a compositional extension of the Sparse Identification of Nonlinear Dynamics (SINDy) framework that replaces explicit feature libra
arXiv:2510.14630v2 Announce Type: replace Abstract: We introduce Representation Tokenizer (RepTok), a generative modeling framework that represents an image using a single continuous latent token obta
arXiv:2604.18576v2 Announce Type: replace Abstract: We present BLF (Bayesian Linguistic Forecaster), an agentic system for binary forecasting that achieves state-of-the-art performance on the Forecast
arXiv:2604.19238v1 Announce Type: new Abstract: Real-world image super-resolution (Real-SR) has been revolutionized by leveraging the powerful generative priors of large-scale diffusion and flow-based
arXiv:2604.19618v1 Announce Type: new Abstract: Reliable pipeline inspection is critical to safe energy transportation, but is constrained by long distances, complex terrain, and risks to human inspec
arXiv:2604.18781v1 Announce Type: new Abstract: Large-scale automated morphometric analysis of brain MRI is limited by the thick-slice, anisotropic acquisitions prevalent in routine clinical practice.
arXiv:2604.19431v1 Announce Type: cross Abstract: Generative AI systems are known to amplify biases present in their training data. While several inference-time mitigation strategies have been propose
arXiv:2602.18571v2 Announce Type: replace-cross Abstract: While significant progress has been made in automating various aspects of software development through coding agents, there is still significa
arXiv:2604.19432v1 Announce Type: new Abstract: Vision foundation models have shown great promise for open-set 3D object retrieval (3DOR) through efficient adaptation to multi-view images. Leveraging
arXiv:2504.01733v4 Announce Type: replace Abstract: This paper presents a class of epistemic logics that captures the dynamics of acquiring knowledge and descending into oblivion, while incorporating
arXiv:2603.15956v2 Announce Type: replace-cross Abstract: Learning generalizable and robust behavior cloning policies requires large volumes of high-quality robotics data. While human demonstrations (
arXiv:2604.19259v1 Announce Type: new Abstract: Multi-class defect detection constitutes a critical yet challenging task in industrial quality inspection, where existing approaches typically suffer fr
arXiv:2404.10769v4 Announce Type: replace-cross Abstract: This paper develops a functional-analytic framework for approximating the push-forward induced by an analytic map from finitely many samples.
arXiv:2604.19457v1 Announce Type: new Abstract: Long-horizon enterprise agents make high-stakes decisions (loan underwriting, claims adjudication, clinical review, prior authorization) under lossy mem
arXiv:2604.19516v1 Announce Type: new Abstract: Generative engines (GEs) are reshaping information access by replacing ranked links with citation-grounded answers, yet current Generative Engine Optimi
arXiv:2604.19345v1 Announce Type: new Abstract: This paper investigates the intrinsic geometrical features of highly similar objects and introduces a general self-supervised framework called the Geome
arXiv:2505.22811v5 Announce Type: replace-cross Abstract: Weight binarization has emerged as a promising strategy to reduce the complexity of large language models (LLMs). Existing approaches fall int
The post discusses the lack of AI models that work seamlessly across different agent frameworks and harnesses, suggesting this represents a significant opportunity for open-weight model development. T
arXiv:2604.19191v1 Announce Type: cross Abstract: Anomaly detection in medical imaging is essential for identifying rare pathological conditions, particularly when annotated abnormal samples are limit
Anyscale Agent Skills is a framework built on Ray that enables developers to build AI agents more efficiently with improved debugging capabilities and workload optimization. The tool likely provides a
This article explores the implementation of Internet of Things technology in manufacturing environments, covering strategic approaches, key hardware and software components, practical applications acr
arXiv:2511.04320v2 Announce Type: replace Abstract: Autonomous navigation in unknown environments requires multi-scale spatial understanding that captures geometric details, topological connectivity,
This post likely clarifies the distinction between testing platforms and agent platforms, suggesting that a particular tool or framework (possibly LangChain, given Harrison Chase's role) is better cha
NVIDIA and Google Cloud have collaborated for more than a decade, co‑engineering a full‑stack AI platform that spans every technology layer — from performance‑optimized libraries and frameworks to ent
arXiv:2502.16161v2 Announce Type: replace-cross Abstract: Visually-situated text parsing (VsTP) has recently seen notable advancements, driven by the growing demand for automated document understandin
arXiv:2411.06837v2 Announce Type: replace Abstract: The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, enabling fully-automated, pers
arXiv:2604.19684v1 Announce Type: new Abstract: Explainable artificial intelligence (XAI) has predominantly focused on generating model-centric explanations that approximate the behavior of black-box