Knowledge catalogue
arXiv:2407.20432v3 Announce Type: replace Abstract: Bayesian inference methods such as Markov Chain Monte Carlo (MCMC) typically require repeated computations of the likelihood function, but in some s
Obsidian Security Inc. has raised an 85 million Series D funding round at a post-money valuation of 1.1 billion as enterprises increasingly look to secure autonomous artificial intelligence agents acc
arXiv:2407.15260v3 Announce Type: replace Abstract: Statistical Shape Models (SSMs) excel at identifying population level anatomical variations, which is at the core of various clinical and biomedical
arXiv:2406.14657v4 Announce Type: replace Abstract: We introduce OpenDebateEvidence, a comprehensive dataset for argument mining and summarization sourced from the American Competitive Debate communit
arXiv:2608.01034v1 Announce Type: new Abstract: We introduce Opt.Gear, a foundation model designed for efficient on-device deployment, real-tim inference, and strong task capability. It includes a den
arXiv:2608.02533v1 Announce Type: cross Abstract: We construct unambiguous DNFs having width O(n) but 0-certificate complexity Omega(n^2). By utilizing the special structure of these DNFs, we prove a
arXiv:2602.06737v2 Announce Type: replace Abstract: We present a generalized framework for the range verification of neural networks featuring non-linear activation functions. Our approach first const
arXiv:2608.01458v1 Announce Type: new Abstract: Large language models are being extensively used to simulate individual user behavior, yet faithfully representing a population requires capturing the s
arXiv:2608.01825v1 Announce Type: new Abstract: Part-level 3D generation has recently attracted increasing attention for producing structured and editable 3D assets. However, existing methods typicall
arXiv:2608.00870v1 Announce Type: new Abstract: Panoptic crop mapping requires both delineating individual agricultural parcels and assigning a crop type to each parcel from satellite image time serie
arXiv:2608.00045v1 Announce Type: new Abstract: This study shows that textual descriptors alone can predict early-stage startup success, defined as Exit, without relying on contextual, financial, or h
arXiv:2608.02480v1 Announce Type: cross Abstract: With AI systems gaining more access to individuals' information, it is important to protect privacy when reporting statistical answers. Equally import
arXiv:2608.00129v1 Announce Type: new Abstract: Knowledge distillation (KD) is a widely utilized technique for transferring knowledge from a large model (the teacher) to a smaller model (the student).
arXiv:2608.02053v1 Announce Type: cross Abstract: Brain tissue microstructure estimation with machine learning provides higher computational efficiency than conventional fitting. However, machine lear
Qwen 3.8‑Max, Alibaba.Qwen’s latest large‑language model, has been added to Hermes Agent and can currently be accessed at a 20 % discount. The update aims to streamline integration of the model for de
arXiv:2608.01626v1 Announce Type: new Abstract: Short-term precipitation nowcasting is important for hydrometeorological early warning, especially when intense convective rainfall may trigger urban fl
arXiv:2608.00508v1 Announce Type: new Abstract: Object detection and segmentation in three-dimensional medical images is a very active area of research. However, most proposed deep learning models car
arXiv:2608.01509v1 Announce Type: new Abstract: Rolling shutter (RS) cameras are widely used in consumer devices, but their row-wise exposure causes distortions under motion, making geometric 3D visio
arXiv:2608.02027v1 Announce Type: new Abstract: We present scikit-fingerprints, a comprehensive, fully scikit-learn compatible library for molecular machine learning in Python, based on RDKit. Molecul
arXiv:2507.02778v3 Announce Type: replace Abstract: Although large language models (LLMs) have transformed AI, they still make errors and follow unproductive reasoning paths. Self-correction is vital
arXiv:2608.02348v1 Announce Type: cross Abstract: Malware clustering is a critical task in cybersecurity that helps discover threats and analyze evolving malware families. While self-supervised learni
arXiv:2608.01670v1 Announce Type: new Abstract: This paper answers the one-dimensional local root anti-concentration questions posed by Balcan, Pegden, and Sharma in the context of online optimization
arXiv:2608.01318v1 Announce Type: cross Abstract: Modern sensing, communication, and learning systems generate heterogeneous network signals, with local data differing in dimension, modality, and geom
arXiv:2209.03282v5 Announce Type: replace-cross Abstract: Accelerating the convergence of second-order optimization, particularly Newton-type methods, remains a pivotal challenge in algorithmic resear
arXiv:2509.17920v2 Announce Type: replace Abstract: Current deep learning models for electroencephalography (EEG) are often task-specific and depend on large labeled datasets, limiting their adaptabil
arXiv:2608.01083v1 Announce Type: new Abstract: Manipulation involving rigid-deformable interactions, such as hanging clothes or dressing humans, is common in daily life, making it essential for house
arXiv:2608.01659v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting enables efficient novel-view synthesis without per-scene optimization, but most existing methods assume a fixed set o
arXiv:2608.01053v1 Announce Type: new Abstract: Constructing photorealistic Free-Viewpoint Videos (FVVs) of dynamic scenes from a set of posed 2D images has been an intriguing yet challenging task in
arXiv:2509.22992v2 Announce Type: replace Abstract: As machine learning models continue to grow in size and complexity, efficient serving faces increasingly broad trade-offs spanning accuracy, latency
arXiv:2608.00492v1 Announce Type: cross Abstract: Predictive coding offers a powerful theory of cortical computation, but corresponding scalable algorithmic implementations for artificial intelligence
arXiv:2608.01615v1 Announce Type: cross Abstract: We present a set of tools for mapping general stochastic programs to thermodynamic hardware designed for energy-efficient stochastic sampling. Given a
arXiv:2608.00315v1 Announce Type: cross Abstract: Robot policies are becoming increasingly general, with vision-language-action (VLA) models enabling a single policy to execute diverse tasks specified
arXiv:2608.02238v1 Announce Type: cross Abstract: Ensuring trust in AI systems is essential for the safe and ethical integration of machine learning systems into high-stakes domains such as digital he
arXiv:2608.02583v1 Announce Type: cross Abstract: Sparse retrieval underpins modern search systems, from web search to retrieval-augmented generation. Existing work has introduced Learned Sparse Retri
arXiv:2608.00984v1 Announce Type: new Abstract: This paper explores the challenges and the methodologies associated with learning quality representations in scenarios with unlabelled small or limited
arXiv:2608.00072v1 Announce Type: new Abstract: Recent advances in quantum computing are opening new possibilities for Earth Observation (EO) data analysis. Quantum machine learning (QML) approaches o
arXiv:2608.00076v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) increasingly support high-stakes decision making by combining complementary information from images and text. W
arXiv:2510.24598v2 Announce Type: replace Abstract: Current quantum machine learning approaches often face challenges balancing predictive accuracy, robustness, and interpretability. To address this,
arXiv:2607.28952v1 Announce Type: new Abstract: Humanoid and quadrupedal robots have the potential to revolutionize the way we work, interact, and coexist with intelligent machines. To understand thei
arXiv:2607.29549v1 Announce Type: new Abstract: Large language models have demonstrated strong mathematical problem-solving capabilities, yet reliably verifying their candidate answers remains challen
CUDA: Add backend sampler for penalties sampler (#25262) sampling: enhance penalty handling in common_sampler_init Set default value for penalty_last_n based on model context if not specified. Ensure
arXiv:2607.29440v1 Announce Type: new Abstract: Long-term multimodal memory must support not only retrieving relevant information but also computing over observations accumulated across interactions.
arXiv:2607.29302v1 Announce Type: cross Abstract: Reliable robot learning requires a world simulator that can predict action consequences before execution on physical hardware, including risky and fai
arXiv:2604.05150v2 Announce Type: replace-cross Abstract: We study compiled AI, a paradigm in which large language models generate executable code artifacts during a compilation phase, after which wor
arXiv:2605.05895v2 Announce Type: replace-cross Abstract: Modern AI-generated videos are photorealistic at the single-frame level, leaving inter-frame dynamics as the main remaining axis for detection
arXiv:2603.13415v2 Announce Type: replace Abstract: Valence-arousal (VA) estimation is crucial for capturing the nuanced nature of human emotions in naturalistic environments. While pre-trained vision
arXiv:2607.28826v1 Announce Type: new Abstract: Autonomous Cyber Operations (ACO) are increasingly important for defending enterprise networks as cyber threats continue to evolve in sophistication. AC
arXiv:2607.29491v1 Announce Type: cross Abstract: Reinforcement-learning-based quantum architecture search (RL-QAS) repeatedly optimizes a variational quantum eigensolver (VQE) after extending a circu
arXiv:2607.29577v1 Announce Type: new Abstract: Games and simulators make valuable benchmarks by turning decisions into measurable outcomes, but many current suites under-test rules-rich tactical reas
arXiv:2511.02570v3 Announce Type: replace Abstract: Bayesian optimization (BO) is a widely used approach to hyperparameter optimization (HPO). However, most existing HPO methods only incorporate exper
arXiv:2604.08342v2 Announce Type: replace Abstract: Long context egocentric video understanding has recently attracted significant research attention, with augmented reality (AR) highlighted as one of
arXiv:2607.29182v1 Announce Type: cross Abstract: Transcranial focused ultrasound (tFUS) is a non-invasive technique that delivers focused acoustic energy through the skull for neuromodulation and the
arXiv:2607.29132v1 Announce Type: new Abstract: Surgical gauze is an essential part of surgical procedures, primarily used for controlling bleeding and absorbing bodily fluids. The post-surgical reten
arXiv:2602.08913v3 Announce Type: replace Abstract: In underdetermined regression and classification problems, multiple feature subsets often yield equivalent predictive performance. In applied settin
arXiv:2601.02854v2 Announce Type: replace Abstract: As an agent-level reasoning and coordination paradigm, Multi-Agent Debate (MAD) orchestrates multiple agents through structured debate to improve an
arXiv:2607.28675v1 Announce Type: cross Abstract: Polygonal meshes are the standard surface representation of modern 3D pipelines, and generating high-quality meshes with artist-style topology is esse
arXiv:2607.29633v1 Announce Type: new Abstract: Single-image 3D hand avatar reconstruction is fundamentally ill-posed and particularly challenging due to limited visual evidence under severe self-occl
arXiv:2607.28686v1 Announce Type: cross Abstract: Optical flow characterizes motion in the visual field and is fundamental to motion perception and tracking in biological and artificial vision systems
arXiv:2607.28990v1 Announce Type: new Abstract: Large language model agents have shown promising capabilities in data-driven scientific discovery tasks, where an agent interacts with an execution envi
arXiv:2607.28692v1 Announce Type: new Abstract: Large language model (LLM) agents have been increasingly adopted in scientific research for organizing and invoking specialized computational tools. How