Knowledge catalogue
arXiv:2605.03440v1 Announce Type: new Abstract: The rapid growth of electronic communication has necessitated more robust systems for email classification and sentiment detection. This study presents
arXiv:2605.02366v1 Announce Type: new Abstract: Research funding discovery remains fundamentally fragmented: researchers navigate disparate agency portals (e.g., in the United States, NSF, NIH, DARPA,
arXiv:2605.03696v1 Announce Type: new Abstract: The performance of end-to-end automatic speech recognition (ASR) systems enables their increasing integration into numerous applications. While there ar
A critical question in agent design is “how do we build agentic workflows so humans are given significant, interesting, or variance-producing decisions as they come up in the work?” A Claude-run compa
arXiv:2605.03857v1 Announce Type: new Abstract: This work presents a deeper analysis of the 'irreversibility' property of PolyProtect, a biometric template protection method initially proposed for sec
arXiv:2605.03832v1 Announce Type: new Abstract: In recent years, machine learning has made significant progress in clinical outcome prediction, demonstrating increasingly accurate results. However, th
arXiv:2605.03623v1 Announce Type: new Abstract: We propose a unified, few-step generative modeling framework based on cumulative flow maps for long-range transport in probability space, inspired by fl
arXiv:2605.02942v1 Announce Type: cross Abstract: Bias in medical AI is often framed as a problem of representation. However, in image-based tasks such as fetal ultrasound, performance disparities can
A great conversation between Noah Kravitz from the @nvidia team + @hwchase17. “Every enterprise needs a claw strategy.” How did @LangChain go from a weekend project to 1B+ downloads in 3 years? We sat
arXiv:2605.03499v1 Announce Type: new Abstract: We study expected generalization bounds for the Hierarchical Federated Learning (HFL) setup using Wasserstein distance. We introduce a generalized frame
arXiv:2605.01100v1 Announce Type: new Abstract: This work presents a knowledge-driven decision-support system that integrates structured defect knowledge with LLM-based reasoning to provide explainabl
arXiv:2605.01143v1 Announce Type: new Abstract: Large Language Model (LLM)-powered agents demonstrate strong capabilities in autonomous task execution, tool use, and multi-step reasoning. However, the
arXiv:2512.12109v3 Announce Type: replace-cross Abstract: Automated eligibility systems increasingly determine access to essential public benefits, but the explanations they generate often fail to ref
arXiv:2507.04330v2 Announce Type: replace-cross Abstract: We consider the problem of sampling from a probability distribution pi which admits a density w.r.t. a dominating measure. It is well known th
arXiv:2605.03671v1 Announce Type: new Abstract: The most commonly used metrics for evaluating automatic speech transcriptions, namely Word Error Rate (WER) and Character Error Rate (CER), have been he
arXiv:2605.03203v1 Announce Type: cross Abstract: An alternative generating function is proposed to enumerate row-convex polyominoes without internal holes on a discrete grid. The approach is based on
arXiv:2508.13100v3 Announce Type: replace Abstract: Calibration requires that predictions are conditionally unbiased and, therefore, reliably interpretable as probabilities. A calibration measure quan
arXiv:2605.03787v1 Announce Type: new Abstract: Labeling medical images is a major bottleneck in the field of medical imaging, as it requires domain-specific expertise, and it gets further complicated
arXiv:2401.12783v3 Announce Type: replace-cross Abstract: Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad
arXiv:2605.01078v1 Announce Type: cross Abstract: Retrieval-augmented generation and tool-integrated LLM agents increasingly depend on external textual sources. This reliance broadens the available at
arXiv:2605.02249v1 Announce Type: new Abstract: We investigate the belief revision problem in epistemic planning, i.e., what will be the beliefs of all agents in a multi-agent system after an agent ga
arXiv:2605.01282v1 Announce Type: cross Abstract: In MRI, variations in scan parameters, sequence, or hardware can lead to discrepancies in image appearance, even for the same subject. These inconsist
arXiv:2506.04680v2 Announce Type: replace Abstract: During the development of wearable exoskeletons, evaluations involving human subjects pose inherent safety risks. Therefore, systematic testing is o
A TLDR on Harness Profiles: ✅ Model-specific profiles to adjust prompts, tools, and middleware. 📦 Profiles for @OpenAI, @Anthropic, and @Google models out of the box. 📈 A 10–20 point jump on a subset
arXiv:2405.16971v2 Announce Type: replace Abstract: Deep learning (DL) models require extensive data to achieve strong performance and generalization. Deep generative models (DGMs) offer a solution by
arXiv:2605.03262v1 Announce Type: new Abstract: We introduce the Yat kernel $k_{b,arepsilon}(mathbf{w},mathbf{x})=frac{(mathbf{w}^opmathbf{x}+b)^2}{|mathbf{x}-mathbf{w}|^2+arepsilon},qquad bge 0, arep
Jon Brodkin / Ars Technica: A US appeals court strikes down a 2023 FCC rule banning broadband access discrimination based on income, race, and more; Chair Brendan Carr welcomes the ruling — An appeals
arXiv:2605.02903v1 Announce Type: cross Abstract: In recent years, AI systems in the medical domain have advanced significantly. However, despite outperforming humans, they are rarely used in practice
arXiv:2508.14994v3 Announce Type: replace-cross Abstract: In hazardous and remote environments, robotic systems perform critical tasks demanding improved safety and efficiency. Among these, quadruped
arXiv:2602.18843v3 Announce Type: replace Abstract: We introduce ABD, a benchmark for default-exception abduction over finite first-order worlds. Given a background theory with an abnormality predicat
arXiv:2605.01341v1 Announce Type: cross Abstract: Given a knowledge base (KB) with a non-entailed fact, the ABox abduction problem asks for possible extensions of the KB that would entail this fact. T
arXiv:2605.02661v1 Announce Type: new Abstract: Benchmarks within the OpenClaw ecosystem have thus far evaluated exclusively assistant-level tasks, leaving the academic-level capabilities of OpenClaw
arXiv:2505.24791v2 Announce Type: replace Abstract: Discrete normalizing flows are promising generative models with advantages such as analytical log-likelihood computation and end-to-end training. Ho
arXiv:2605.00968v1 Announce Type: cross Abstract: Positional encoding plays a pivotal role in determin?ing the extrapolation and generalization performance of wireless foundation models for channel st
arXiv:2605.03085v1 Announce Type: new Abstract: Electroencephalography (EEG) signals provide millisecond-level temporal resolution but their analysis is limited by remarkable noise and inter-subject v
arXiv:2605.03393v1 Announce Type: cross Abstract: Contextual MDPs are powerful tools with wide applicability in areas from biostatistics to machine learning. However, specializing them to offline data
arXiv:2605.03495v1 Announce Type: new Abstract: We develop graph-based methods for semi-supervised learning based on label propagation on a data similarity graph. When data is abundant or arrive in a
arXiv:2605.03076v1 Announce Type: new Abstract: Graph contrastive learning (GCL) has become a central paradigm for self-supervised representation learning in computational intelligence, with applicati
arXiv:2605.03212v1 Announce Type: cross Abstract: Modeling latent clinical constructs from unconstrained clinical interactions is a unique challenge in affective computing. We present ADAPTS (Agentic
This article discusses the integration of Benchmaxxer Repellant into the Open ASR (Automatic Speech Recognition) Leaderboard, likely a tool or mechanism designed to prevent gaming or manipulation of l
Adobe Inc. today introduced an artificial intelligence experience embedded in its ubiquitous PDF document reader and creator, Acrobat, to transform how people create, understand and share information.
arXiv:2601.06395v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly multilingual, yet open models continue to underperform relative to proprietary systems, with the gap m
arXiv:2605.03590v1 Announce Type: new Abstract: Recent large language models (LLMs) show strong speech recognition and translation capabilities for high-resource languages. However, African languages
arXiv:2605.02911v1 Announce Type: new Abstract: Future sixth-generation (6G) mobile networks are envisioned to be equipped with a diverse set of powerful, yet highly specialized, optimization experts.
arXiv:2605.01214v1 Announce Type: new Abstract: This position paper argues that agentic AI systems should be designed and evaluated as marginal token allocation economies rather than as text generator
arXiv:2605.03808v1 Announce Type: cross Abstract: Agentic data science (ADS) systems are rapidly improving their capability to autonomously analyze, fit, and interpret data, potentially moving towards
arXiv:2603.01486v2 Announce Type: replace Abstract: Accurately mapping user queries to business categories is a fundamental Information Retrieval challenge for multi-category marketplaces, where conte
arXiv:2503.10070v2 Announce Type: replace-cross Abstract: Scaling Vision-Language-Action models for embodied manipulation demands large volumes of diverse manipulation data, yet the high cost of comme
arXiv:2605.03317v1 Announce Type: new Abstract: Representation alignment has recently emerged as an effective paradigm for accelerating Diffusion Transformer training. Despite their success, existing
arXiv:2602.12631v2 Announce Type: replace-cross Abstract: Inventory control is a fundamental operations problem in which ordering decisions are traditionally guided by theoretically grounded operation
arXiv:2605.00841v1 Announce Type: new Abstract: This study presents a novel, AI-driven framework for assessing Environmental, Social, and Governance (ESG) performance in European small and medium-size
AI agents often struggle to plan movements because their internal representations of the physical world can be overly tangled. CDS PhD student Ying Wang (@yingwww_) shows how straightening these pathw
Autonomous agents are rapidly redefining how enterprise systems operate, exposing new security gaps as machine-driven activity begins to outpace the infrastructure designed for human users. Systems bu
arXiv:2605.02738v1 Announce Type: new Abstract: Solar photovoltaic (PV) deployment is expanding rapidly, yet detailed, up-to-date information on the spatial distribution and capacity of rooftop PV rem
arXiv:2605.01401v1 Announce Type: cross Abstract: Tacit knowledge embedded in expert practice remains difficult to capture, formalise, and scale. While AI-driven educational systems have advanced pers
arXiv:2605.02741v1 Announce Type: cross Abstract: The promise of Large Language Models in automated software engineering is often measured by functional correctness, overlooking the critical issue of
arXiv:2507.22101v2 Announce Type: replace Abstract: Crops, fisheries and livestock form the backbone of global food production, essential to feed the ever-growing global population. However, these sec
Law enforcement worldwide is under pressure — rising complexity, shrinking budgets and an explosion of AI-driven crime. In response, AI policing modernization looks to replace fragmented legacy tools
arXiv:2605.01415v1 Announce Type: new Abstract: Recent AI systems compress the distance between capability growth and capability deployment. Earlier high-risk technologies were slowed by capital inten
AI supercomputers need a new kind of network to stay in sync at massive scale. OpenAI’s @markjhandley and @poyntingatgreg join @AndrewMayne to discuss what it takes to move data across record numbers