Knowledge catalogue
arXiv:2604.24469v1 Announce Type: cross Abstract: Content-based image retrieval (CBIR) systems enable users to search images based on visual content instead of relying on metadata. The text domain has
arXiv:2604.23651v1 Announce Type: new Abstract: Robust in-bed human pose estimation under blanket occlusion remains challenging due to the scarcity of reliable labeled training data for heavily covere
GitHub is transitioning GitHub Copilot to a usage-based billing model to manage escalating AI inference costs. Effective June 1, subscribers will receive a set allotment of 'AI Credits'
Google has signed a classified deal that allows the US Department of Defense to use its AI models for 'any lawful government purpose,' The Information reports. The agreement was reported less than a d
This post discusses how large language models (LLMs) could serve as future chief financial officers, with Mercury as a platform enabling AI systems to manage finances and financial operations. The con
arXiv:2604.23982v1 Announce Type: new Abstract: Digital pathology has fundamentally altered diagnostic workflows by enabling the computational analysis of gigapixel Whole Slide Images (WSIs), yet effe
This skill documentation describes a TouchDesigner MCP (Model Context Protocol) integration that enables AI agents to interact with TouchDesigner, a node-based visual programming environment used for
arXiv:2604.24196v1 Announce Type: cross Abstract: This paper analyzes identifiability and stability for the drifting field underlying distributional matching in the Generative Drifting framework of De
arXiv:2604.23446v1 Announce Type: new Abstract: Industrial maintenance environments increasingly rely on AI systems to assist operators in understanding asset behavior, diagnosing failures, and evalua
arXiv:2604.24616v1 Announce Type: new Abstract: In this paper, we report the world's first infrastructure-guided communication-enhanced road crack detection pipeline that is effective and implementabl
arXiv:2604.24114v1 Announce Type: new Abstract: Curriculum learning helps language models tackle complex reasoning by gradually increasing task difficulty. However, it often fails to generate consiste
arXiv:2604.23493v1 Announce Type: cross Abstract: Early detection of mental health conditions, particularly stress and depression, from social media text remains a challenging open problem in computat
arXiv:2604.23268v1 Announce Type: new Abstract: This paper introduces a novel multi frame super-resolution network (MFSR) for burst hexadeca Bayer pattern Contact Image Sensor (CIS) images, which incl
arXiv:2410.01580v3 Announce Type: replace Abstract: Algorithmic recourse provides individuals who receive undesirable outcomes from machine learning systems with minimum-cost improvements to achieve a
arXiv:2604.23867v1 Announce Type: new Abstract: Scientific measurements are often bottlenecked by suboptimal conditions, whether that be noise, incomplete spatial coverage, or limited resolution, rend
arXiv:2604.22784v1 Announce Type: new Abstract: State estimation is a cornerstone of power system control-center operations, and its robust operation is increasingly a cyber-physical security concern
arXiv:2603.20806v2 Announce Type: replace Abstract: Multi-label fundus diagnosis requires features that capture both fine-grained lesions and large-scale retinal structure. Many multi-scale medical vi
arXiv:2603.19451v2 Announce Type: replace-cross Abstract: Fine-grained representation learning is crucial for retrieval and phrase grounding in chest X-rays, where clinically relevant findings are oft
LTX Desktop 1.0.5 is an open-source desktop app for generating videos with LTX models on Windows/Linux NVIDIA GPUs locally or via API . The version 1.0.5 release includes bug fixes such as LTX API ins
arXiv:2512.02791v2 Announce Type: replace Abstract: Dialogue-Based Generalized Referring Expression Comprehension (GREC) requires models to ground the expression and unlimited targets in complex visua
arXiv:2604.24178v1 Announce Type: cross Abstract: Multi-Objective Alignment aims to align Large Language Models (LLMs) with diverse and often conflicting human values by optimizing multiple objectives
arXiv:2604.23129v1 Announce Type: cross Abstract: Knowledge workers face increasing challenges in synthesizing information from multiple documents into structured conceptual understanding. This proces
arXiv:2604.23788v1 Announce Type: new Abstract: Appreciating multi-figure paintings requires understanding how characters relate through subtle cues like gaze alignment, gesture, and spatial arrangeme
arXiv:2604.24328v1 Announce Type: new Abstract: Monocular depth estimation (MDE) has witnessed remarkable progress driven by Convolutional Neural Networks and transformer-based architectures. However,
arXiv:2604.24337v1 Announce Type: cross Abstract: In this work, we extend the class of previously introduced non-Euclidean neural quantum states (NQS) which consists only of Poincare hyperbolic GRU, t
arXiv:2604.23402v1 Announce Type: cross Abstract: Haptic technologies have advanced rapidly, yet exploration of robotic touch remains dominated by replicating realistic environmental cues or hand gest
arXiv:2604.23599v1 Announce Type: cross Abstract: Gaussian basis functions provide an efficient and flexible alternative to spline activations in KANs. In this work, we introduce the partition-of-unit
arXiv:2604.24707v1 Announce Type: new Abstract: Doorways and passages are critical structural elements for indoor robot navigation, yet they remain underexplored in modern Visual SLAM (VSLAM) framewor
arXiv:2604.24020v1 Announce Type: cross Abstract: Autonomous AI agents deployed on platforms such as OpenClaw face prompt injection, memory poisoning, supply-chain attacks, and social engineering, yet
arXiv:2511.19339v2 Announce Type: replace Abstract: In computer vision, machine unlearning aims to remove the influence of specific visual concepts or training images without retraining from scratch.
arXiv:2604.23804v1 Announce Type: new Abstract: We generalise the reparameterization trick applied in variational autoencoders (VAEs) letting these have latent spaces of non-trivial topology - i.e. th
arXiv:2604.24153v1 Announce Type: new Abstract: Current AI systems increasingly operate in contexts where their outputs directly trigger real-world actions. Most existing approaches to AI safety, risk
arXiv:2604.24036v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have enhanced grounding capabilities in general scenes, their robustness in crowded scenes remains undere
arXiv:2604.24368v1 Announce Type: new Abstract: Generating high-fidelity synthetic tabular data remains a critical challenge for enhancing data availability in privacy-sensitive and low-resource domai
arXiv:2604.23841v1 Announce Type: cross Abstract: Efficiently solving the Job Shop Scheduling Problem in real-world industrial applications requires policies that are both computationally lean and top
arXiv:2604.22948v1 Announce Type: new Abstract: History-dependent sampling can reduce long-run Monte Carlo variance by discouraging redundant revisits, but existing schemes typically encode history th
arXiv:2604.22805v1 Announce Type: cross Abstract: Augmented reality (AR) systems pose unique privacy risks due to their continuous capture of visual data. Existing AR privacy frameworks lack semantic
arXiv:2604.23812v1 Announce Type: cross Abstract: Rootkits are among the most elusive types of malware, capable of bypassing traditional static analysis methods due to their metamorphic behavior. Sign
arXiv:2512.20562v2 Announce Type: replace-cross Abstract: We study the problem of learning a low-degree spherical polynomial of degree ell_0 = Theta(1) ge 1 defined on the unit sphere in RR^d by train
arXiv:2602.00417v2 Announce Type: replace-cross Abstract: We present the first algorithms for generalized linear contextual bandits under shuffle differential privacy and joint differential privacy. W
arXiv:2604.22807v1 Announce Type: cross Abstract: Optimal transport with quadratic cost provides a geometric framework for steering an ensemble, modeled by a probability law, with minimal effort. Yet
arXiv:2604.23996v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has become a prevalent backbone for large vision-language models (VLMs), yet how modality-specific signals should guide expert
arXiv:2604.23135v1 Announce Type: new Abstract: Natural-language variation poses a key challenge in Lean autoformalization: semantically equivalent paraphrases of the same theorem statements can induc
arXiv:2604.23205v1 Announce Type: cross Abstract: Deploying proprietary Deep Neural Networks (DNNs) on commodity edge devices demands hardware-backed Digital Rights Management (DRM) capable of withsta
arXiv:2604.23575v1 Announce Type: cross Abstract: Silicon samples are increasingly used as a low-cost substitute for human panels and have been shown to reproduce aggregate human opinion with high fid
arXiv:2604.23605v1 Announce Type: new Abstract: The application of large language models (LLMs) in clinical decision support faces significant challenges of 'tunnel vision' and diagnostic hallucinatio
arXiv:2604.23094v1 Announce Type: new Abstract: The real-world adoption of portrait relighting is hindered by dataset domain gaps, camera sensitivity, and computational costs. We address these challen
arXiv:2604.23083v1 Announce Type: cross Abstract: Generative approaches to clustering provide information on geometric properties of clusters, whereas discriminative approaches provide boundaries betw
arXiv:2604.22985v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed to autonomously solve real-world tasks. A key ingredient for this is the LLM Function-Calling par
arXiv:2602.12134v2 Announce Type: replace Abstract: Existing work on value alignment typically characterizes value relations statically, ignoring how alignment interventions, such as prompting, fine-t
arXiv:2512.21786v2 Announce Type: replace Abstract: Genomic prediction of drug resistance in Mycobacterium tuberculosis is often hindered by complex epistatic interactions and variable sequencing qual
arXiv:2604.22824v1 Announce Type: cross Abstract: WeatherSeg, an advanced semi-supervised segmentation framework, addresses autonomous driving's environmental perception challenges in adverse weather
What a week at @iclr_conf in Rio 🇧🇷 ! As my first conference, it would have been hard to ask for a better experience 😍. I had the chance to present two papers: - EB-JEPA https://github.com/facebookres
This post likely discusses how to prompt or configure an AI coding agent to incorporate unexpected or whimsical elements like goblins into its outputs, possibly as part of a broader discussion about A
arXiv:2604.24519v1 Announce Type: cross Abstract: AI risk assessment is the primary tool for identifying harms caused by AI systems. These include intersectional harms, which arise from the interactio
arXiv:2604.22227v1 Announce Type: cross Abstract: Classical robot ethics is often framed around obedience, most famously through Asimov's laws. This framing is too narrow for contemporary AI systems,
arXiv:2604.21958v1 Announce Type: cross Abstract: This paper aims to synthesize current knowledge on generative AI in IT project management using the PRISMA methodology to provide researchers with a c
arXiv:2510.16853v3 Announce Type: replace-cross Abstract: Autonomous AI agents capable of complex planning and action mark a shift beyond today's generative tools. As these systems enter political and
arXiv:2604.22236v1 Announce Type: cross Abstract: Human decision-makers often face choices about complex cases with many potentially relevant features, but limited bandwidth to inspect and integrate a
arXiv:2604.22095v1 Announce Type: new Abstract: This paper presents a highly efficient Retrieval-Augmented Generation (RAG) system built specifically for Ukrainian document question answering, which a