Knowledge catalogue
arXiv:2605.04375v2 Announce Type: replace-cross Abstract: To unleash the full potential of AI for Science, we must untether the agents from a purely digital environment. The agent's ability to control
arXiv:2501.12709v2 Announce Type: replace-cross Abstract: Federated learning enables decentralized, privacy-preserving training but remains vulnerable to privacy leakage in the quantum era. Quantum fe
arXiv:2412.00666v4 Announce Type: replace Abstract: Visual explanations for object detectors are crucial for enhancing their reliability. Object detectors identify and localize instances by assessing
arXiv:2603.11689v2 Announce Type: replace Abstract: Frontier Multimodal Large Language Models (MLLMs) exhibit remarkable capabilities in Visual-Language Comprehension (VLC) tasks. However, they are of
arXiv:2605.16770v1 Announce Type: cross Abstract: Criminal Court View Generation (CVG) is a critical task in Legal Artificial Intelligence (Legal AI), involving the generation of court view based on c
arXiv:2605.18036v1 Announce Type: cross Abstract: Trust calibration -- aligning user trust judgment with model capability -- is crucial for safe deployment of explainable AI (XAI), yet is often evalua
In this post, we demonstrate how you can extend the conversational memory of Kiro CLI by implementing a custom Model Context Protocol (MCP) server that integrates with Amazon Bedrock AgentCore Memory.
arXiv:2605.16975v1 Announce Type: cross Abstract: Electrocardiogram (ECG) foundation models pretrained on typical diagnostic 10-second ECG segments, have demonstrated strong transferability across a r
arXiv:2605.17531v1 Announce Type: new Abstract: Referring segmentation aims to segment the target objects in images or videos based on the textual query. Despite remarkable progress over the past year
arXiv:2510.14102v2 Announce Type: replace-cross Abstract: Spectral signatures are crucial in the era of large X-ray surveys. Automatic machine learning methods have proven useful in this respect, but
arXiv:2605.17361v1 Announce Type: cross Abstract: Multi-agent systems (MAS) powered by large language models (LLMs) have emerged as a powerful paradigm for complex problem solving, where performance c
arXiv:2605.16630v1 Announce Type: cross Abstract: Hybrid local--cloud agents enrich user requests with context from persistent working state before delegating capability-intensive subtasks to a cloud
arXiv:2406.15797v2 Announce Type: replace-cross Abstract: Employing graph neural networks (GNNs) for graph clustering has shown promising results in deep graph clustering. However, existing methods di
arXiv:2605.17115v1 Announce Type: new Abstract: Biased manipulation of facts across regional and national media outlets complicates misinformation detection in diverse landscapes like India. This pape
arXiv:2605.16696v1 Announce Type: new Abstract: Face inpainting techniques recover missing or occluded facial regions in a visually realistic manner, but preserving the identity in the final output re
arXiv:2601.21350v2 Announce Type: replace Abstract: A reliable reward model is essential for aligning large language models with human preferences through reinforcement learning from human feedback. H
arXiv:2605.17165v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPA) are a promising framework for self-supervised video representation learning, yet the behavior of auxilia
arXiv:2507.18406v2 Announce Type: replace Abstract: Wikipedia serves as a globally accessible knowledge source with content in over 300 languages. Despite covering the same topics, the different versi
Fair expectations Does it make you “far right” to want: - vetted immigration - no digital ID - lower taxes - no two-tier policing - free speech - pedophiles out of office - lower cost of living MSM an
arXiv:2503.16492v3 Announce Type: replace-cross Abstract: ffective Human-Robot Interaction (HRI) is crucial for enhancing accessibility and usability in real-world robotics applications. However, exis
Fascinatingly Antigravity is actually the best tool so far at providing this sort of transparency, doing something by default that Codex and Code do not: offering a summary of exactly what it did at t
arXiv:2505.18991v3 Announce Type: replace Abstract: Pansharpening seeks to fuse high-resolution panchromatic (PAN) and low-resolution multispectral (LRMS) images into a single image with both fine spa
arXiv:2602.05742v2 Announce Type: replace-cross Abstract: Weighted empirical risk minimization is a common approach to prediction under distribution drift. This article studies its out-of-sample predi
arXiv:2605.17447v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have shown strong promise on Optical Character Recognition (OCR), yet the sheer number of visual tokens required to enco
The FBI is seeking up to $36 million for nationwide access to automated license plate reader (ALPRs) data, which would allow it to query vehicle movements across the U.S. and its territories through a
arXiv:2605.17767v1 Announce Type: cross Abstract: We study feature learning in two-layer neural networks within the linear-width regime, where the number of hidden neurons, sample size, and input dime
arXiv:2508.14769v2 Announce Type: replace Abstract: Federated distillation has emerged as a promising collaborative machine learning approach, offering enhanced privacy protection and reduced communic
arXiv:2605.18020v1 Announce Type: new Abstract: Federated Learning (FL) algorithms implicitly assume that clients passively comply with server-side orchestration by sharing local model updates upon se
arXiv:2605.18554v1 Announce Type: new Abstract: Federated Bayesian neural networks require fixing a prior on the model parameters together with a likelihood. Eliciting meaningful priors on the weight
arXiv:2605.16350v1 Announce Type: cross Abstract: We rethink Federated Learning (FL) from a nested learning perspective, framing the core challenge as how to collaboratively learn optimization rules,
arXiv:2509.06984v3 Announce Type: replace-cross Abstract: Federated Learning with LoRA fine-tuning offers an efficient and privacy-aware solution for institutions to collaboratively leverage their lar
arXiv:2605.18028v1 Announce Type: cross Abstract: Federated fine-tuning of Large Language Models faces severe statistical heterogeneity. However, existing model-level defenses often overlook the root
arXiv:2605.17282v1 Announce Type: cross Abstract: Estimating the largest Lyapunov exponent from a scalar time series is difficult when the governing equations, tangent dynamics, and full state vector
arXiv:2605.17530v1 Announce Type: cross Abstract: Network intrusion detection systems play a vital role in protecting networks by detecting malicious network traffic which can then be investigated by
arXiv:2602.00470v2 Announce Type: replace Abstract: Individual tree crown segmentation is an important task in remote sensing for forest biomass estimation and ecological monitoring. However, accurate
arXiv:2605.17246v1 Announce Type: cross Abstract: We introduce fidelity probes: natural-language questions generated from a reference artifact with code-derived ground-truth answers, answered from a c
arXiv:2605.17201v1 Announce Type: cross Abstract: Social engineering attacks exploit human trust rather than software vulnerabilities, making them difficult to detect using conventional filters. We pr
arXiv:2605.16800v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) assigns a uniform rank to every adapted weight matrix - a practical convenience that ignores a fundamental reality: differe
arXiv:2510.08886v3 Announce Type: replace Abstract: Going beyond simple text processing, financial auditing requires detecting semantic, structural, and numerical inconsistencies across large-scale di
arXiv:2602.11699v3 Announce Type: replace Abstract: Nonsensical and anomalous sentences have been instrumental in the development of computational models of semantic interpretation. A core challenge i
arXiv:2505.20218v2 Announce Type: replace Abstract: Accurate and safe medication recommendations are critical for effective clinical decision-making, especially in multimorbidity cases. However, exist
arXiv:2512.05136v3 Announce Type: replace-cross Abstract: CAD remains a major global public health burden, yet scalable screening tools are limited. Although CCTA is a first-line non-invasive diagnost
arXiv:2605.17693v1 Announce Type: cross Abstract: Structure-based drug design has been accelerated by pocket-aware 3D generative models, yet most methods primarily fit the training distribution and ma
arXiv:2602.05172v2 Announce Type: replace-cross Abstract: We derive finite-particle rates for the regularized Stein variational gradient descent (R-SVGD) algorithm introduced by He et al. (2024) that
arXiv:2505.20650v5 Announce Type: replace-cross Abstract: Accurate interpretation of numerical data in financial reports is critical for markets and regulators. Although XBRL (eXtensible Business Repo
arXiv:2605.17558v1 Announce Type: cross Abstract: Training tool-calling agents requires large-scale trajectory data with verifiable labels, yet existing approaches either synthesize environments that
arXiv:2508.20836v3 Announce Type: replace Abstract: In this letter, we report the first experimental demonstration of the recently emerged new paradigm in hovering and flapping flight physics called (
A researcher from a resource-limited region discusses challenges with attending an accepted ICML workshop (GlobalSouthML) in South Korea and seeks advice on affordable attendance options, likely explo
arXiv:2605.17231v1 Announce Type: cross Abstract: Activation steering methods modify intermediate representations of language models to control output behavior, but universally assume the activation s
Like most vendor event keynotes this year, Michael Dell used his Dell Technologies World 2026 keynote to argue that artificial intelligence has moved beyond experimentation and into the physical, oper
arXiv:2602.03784v2 Announce Type: replace Abstract: Long-context LLM agents often struggle with growing token, memory, and latency costs, making efficient context compression essential for practical d
arXiv:2605.18184v1 Announce Type: cross Abstract: Commonly available prior information, such as BIM models, floor plans, and remote sensing images, can provide valuable geometric and semantic context
arXiv:2605.18055v1 Announce Type: cross Abstract: Predicting spatial gene expression from routine H&E enables large-scale molecular profiling, yet current models treat this as isolated pointwise tasks
Vercel announced a flat-rate CDN pricing model entering limited beta, offering predictable content delivery costs instead of usage-based pricing. This new offering allows developers to pay a fixed fee
arXiv:2512.23070v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models enable scalable neural networks through conditional computation, offering enhanced effectiveness and efficiency for
arXiv:2605.16348v1 Announce Type: cross Abstract: Training-free guidance enables pre-trained diffusion and flow models to optimize application-specific objectives using feedback from external black-bo
arXiv:2605.16469v1 Announce Type: cross Abstract: Rare diseases dominate the diagnostic challenge in medical imaging yet are severely underrepresented in clinical datasets, causing classifiers to fail
arXiv:2605.18472v1 Announce Type: cross Abstract: Generative models can produce nonsensical text, unrealistic images, and unstable materials faster than simulation or human review can absorb; without
arXiv:2505.16786v2 Announce Type: replace Abstract: We introduce FlowMixer, a single-layer neural architecture that leverages constrained matrix operations to model structured spatiotemporal patterns
arXiv:2605.17373v1 Announce Type: cross Abstract: AI research agents accelerate ML research by automating hypothesis generation, experimentation, and empirical refinement. Existing agent strategies ra