Knowledge catalogue
AI is booming. New use cases are emerging each day. To capitalize on the technology’s potential, enterprises require data at scale. In many cases, though, the relevant information is blocked or unstru
arXiv:2606.24622v1 Announce Type: new Abstract: Training safe Reinforcement Learning (RL) systems is inherently challenging, with no guarantee of avoiding unwanted behaviors. The most effective defens
Nous Research recommends using the 'hermes skills config' command to enable creative-ideation and other optional skills in their system. This command appears to be a configuration tool for activating
arXiv:2606.24297v1 Announce Type: new Abstract: Cross-domain Few-shot Segmentation (CD-FSS) aims to transfer knowledge learned from source domain to distinct target domains, segmenting unseen target c
arXiv:2606.23917v1 Announce Type: new Abstract: Advances in generative AI have made image falsification highly realistic, demanding trustworthy authentication systems. Existing forensic detectors can
arXiv:2606.24134v1 Announce Type: cross Abstract: Motivated by an application in machine learning optimization, this paper focuses on the challenges of sampling a matrix uniformly from the unit spectr
arXiv:2606.24094v1 Announce Type: new Abstract: Unifying image clustering across different clustering scenarios remains challenging due to fundamental gaps among tasks. We introduce a Guideline-Driven
arXiv:2606.24462v1 Announce Type: new Abstract: This paper presents a scalable framework for multi-robot task allocation in complex environments where estimating task execution costs is computationall
arXiv:2606.24635v1 Announce Type: cross Abstract: Traditional visual data storytelling relies on binary graphics that depict two simplified groups in conflict. This can increase political polarization
arXiv:2606.24602v1 Announce Type: new Abstract: Despite remarkable progress in multimodal understanding, current MLLMs still exhibit limitations in video text understanding, particularly when semantic
arXiv:2606.23740v1 Announce Type: cross Abstract: Offline reinforcement-learning losses (RFT, RIFT, DFT, Offline GRPO, DPO) are widely used to distill reasoning from large teachers into smaller studen
We’ve designed and built our first AI chip: Jalapeño. Designed from the ground up by OpenAI and brought to production with @Broadcom, Jalapeño is purpose-built for the LLM workloads powering ChatGPT,
This Databricks blog post explores how organizations can leverage their existing data assets to find answers to business questions without requiring additional data collection or external sources. The
arXiv:2410.11116v4 Announce Type: replace-cross Abstract: In this paper, we establish a novel connection between the metric entropy growth and the embeddability of function spaces into reproducing ker
This article discusses why Databricks leaders argue that the frontier AI ecosystem should remain open rather than closed, likely covering topics such as open-source AI development, the benefits of col
Written by: Chester Sng, Pete Boonyakarn, Logeswaran Nadarajan Introduction In early 2026, Mandiant identified a threat actor targeting SD-WAN infrastructure at a service provider. After gaining initi
arXiv:2405.10705v3 Announce Type: replace-cross Abstract: Digital Subtraction Angiography (DSA) is one of the gold standards for vascular disease diagnosis. With the help of a contrast agent, time-res
arXiv:2606.21776v1 Announce Type: new Abstract: A Prior-data fitted Network learns the posterior predictive induced by its training prior; bringing this paradigm to multivariate time-series classifica
arXiv:2606.22447v1 Announce Type: cross Abstract: Explanation requires ground truth: to verify an account of a system we must know its inner functioning-just what is missing where explainable AI (XAI)
arXiv:2507.07907v2 Announce Type: replace-cross Abstract: Learning is a complex dynamical process shaped by a range of interconnected decisions. Careful design of hyperparameter schedules for artifici
arXiv:2606.21304v1 Announce Type: new Abstract: This paper introduces the CERTH-ITI solution for the MediaEval NewsImages 2026 challenge, which focuses on generating images related to news headlines.
arXiv:2606.20620v1 Announce Type: new Abstract: Starting from the axiomatic formulation of scale-space theory, we develop a viscosity-solution framework for multiscale image representations arising fr
arXiv:2606.22112v1 Announce Type: new Abstract: The performance of advanced materials for extreme environments is underpinned by their microstructure, including the size and distribution of reinforcin
arXiv:2606.22091v1 Announce Type: new Abstract: Per-scene 3D Gaussian Splatting (3DGS) enables high-fidelity rendering, but practical robotic and AR scene capture pipelines often depend on external ge
arXiv:2606.19891v2 Announce Type: replace Abstract: We study adversarial bandit optimization in which the loss functions may be non-convex and non-smooth. In each round, the learner selects an action
arXiv:2606.20640v1 Announce Type: cross Abstract: Autonomous vehicles offer the potential for safer and more efficient mobility, yet public trust remains limited due to the lack of transparency in the
arXiv:2606.21177v1 Announce Type: cross Abstract: Segmenting the temporomandibular joint (TMJ) disc from MRI is essential for accurate diagnosis of internal derangement, yet it remains unreliable in p
arXiv:2606.22278v1 Announce Type: cross Abstract: Ensuring safety of learning-enabled robotic manipulation across diverse embodiments and tasks still requires significant manual engineering. Existing
arXiv:2606.23550v1 Announce Type: cross Abstract: In this work, Neural ODEs equipped with a curated collection of equilibrium points have been successfully employed for classification tasks.The plante
arXiv:2606.21938v1 Announce Type: new Abstract: Reconstructing articulated objects from sparse images requires recovering complete geometry, movable parts, and motion parameters. Recent methods typica
arXiv:2606.23153v1 Announce Type: new Abstract: Animal collectives navigate cluttered environments through local coordination, yet robot swarms still struggle to reproduce this capability in the physi
arXiv:2606.23606v1 Announce Type: cross Abstract: Global communications rely on subsea cable infrastructure that remains vulnerable to damage from natural hazards and human activity. Autonomous underw
llama.cpp release b9771 addresses Vulkan optimization by making mul_mm ALIGNED a spec constant, reducing shader variant explosion and binary size. This release is part of the ongoing development of ll
arXiv:2606.22089v1 Announce Type: new Abstract: Breast arterial calcification (BAC) on screening mammograms is an emerging cardiovascular risk biomarker, but quantitative use requires reproducible seg
arXiv:2606.21014v1 Announce Type: new Abstract: Robots must generate trajectories that remain faithful to learned expert behavior while satisfying safety constraints and task-specific objectives speci
arXiv:2512.14200v2 Announce Type: replace Abstract: Recent advances in Neural Radiance Fields and 3D Gaussian Splatting have demonstrated strong potential for large-scale UAV-based 3D reconstruction t
arXiv:2606.22456v1 Announce Type: new Abstract: Maintaining accurate navigation during GNSS outages remains a significant challenge for autonomous systems relying on low-cost inertial sensors. While c
arXiv:2505.11129v2 Announce Type: replace Abstract: Representation learning is one of the key research topics in machine learning, and the framework of self-supervised learning (SSL) has revolutionize
arXiv:2606.21497v1 Announce Type: new Abstract: Modern deep neural network architectures are trained via backpropagation, which requires errors to be sequentially propagated through all layers before
arXiv:2606.18872v2 Announce Type: replace Abstract: Clinical prostate multi-parametric MRI relies heavily on high-quality diffusion-weighted imaging (DWI), yet reading DWI is frequently compromised by
This post shows you how to build a conversational protein research assistant that combines three capabilities: Natural language query parsing to extract structured search parameters, vector similarity
The NVIDIA BioNeMo Agent Toolkit enables AI scientists to use structure prediction, molecular generation, docking, sequence analysis, design, and genomics as callable tools , allowing AI agents to exe
arXiv:2409.15493v4 Announce Type: replace-cross Abstract: Persistent semantic monitoring of indoor spaces such as warehouses, hospitals, and offices requires a robot to repeatedly monitor an environme
arXiv:2606.22389v1 Announce Type: new Abstract: Singular Learning Theory leverages the Local Learning Coefficient (LLC) to quantify the geometry of neural network loss landscapes. However, mean-energy
arXiv:2606.22987v1 Announce Type: new Abstract: Single-view mesh reconstruction predicts object meshes and spatial layouts from a single observation, making it attractive for fast robot spatial reason
arXiv:2602.03389v2 Announce Type: replace Abstract: Offline goal-conditioned reinforcement learning remains challenging for long-horizon tasks. While hierarchical approaches mitigate this issue by dec
arXiv:2509.13793v2 Announce Type: replace-cross Abstract: It is shown that the port behavior of a resistor-diode network corresponds to the solution of a ReLU monotone operator equilibrium network (a
arXiv:2606.12966v2 Announce Type: replace Abstract: Grokking is the delayed generalisation phenomenon where a transformer trained on modular arithmetic abruptly transitions from near-chance to near-pe
arXiv:2606.22939v1 Announce Type: cross Abstract: Radio frequency jamming poses a critical threat to the availability of wireless Industrial Internet of Things (IIoT) networks. Existing detection and
arXiv:2507.08262v2 Announce Type: replace-cross Abstract: The spatial information inherent in 3D point clouds is crucial for robotic manipulation. However, existing 3D pre-training methods face a fund
arXiv:2603.07005v2 Announce Type: replace Abstract: A matching platform is a system that matches participants of different types, such as companies and job-seekers. In such a platform, maximizing matc
arXiv:2606.21752v1 Announce Type: cross Abstract: Histopathologic cancer detection is challenging due to tissue variability, staining differences, and subtle visual distinctions between disease classe
arXiv:2606.21900v1 Announce Type: cross Abstract: Continuous authentication for mobile and zero-trust systems requires nonintrusive evidence confirming the enrolled user-device context remains valid a
arXiv:2510.15623v2 Announce Type: replace Abstract: Complex query answering (CQA) goes beyond the widely studied link prediction task by addressing more sophisticated queries that require multi-hop re
arXiv:2509.23340v4 Announce Type: replace-cross Abstract: Automatically assessing the credibility of online sources presents an invaluable tool for navigating today's information ecosystem. However, e
arXiv:2606.20725v1 Announce Type: new Abstract: Accurate, up-to-date representations of road structures are critical for the safe operation of autonomous vehicles. Existing systems rely either on cost
arXiv:2606.21158v1 Announce Type: new Abstract: Singular learning theory characterises the complexity of a deep network through the geometry of its loss singularities. The local learning coefficient (
arXiv:2606.23585v1 Announce Type: cross Abstract: As autonomous aircraft are introduced at scale and traffic density increases, centralized management becomes insufficient to coordinate the large numb
arXiv:2606.23557v1 Announce Type: new Abstract: Multi-view 3D Visual Question Answering (MV3D-VQA) requires integrating partial observations into a coherent 3D scene representation and selecting infor
arXiv:2606.20976v1 Announce Type: new Abstract: Radio-frequency (RF) monitoring is essential for space domain awareness, but it often generates large, variable, and sparsely populated datasets with fe