Knowledge catalogue
arXiv:2512.06443v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed on edge devices. To meet strict resource constraints, real-world deployment has pushed
arXiv:2604.11146v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, thereby preserving privacy. However, F
arXiv:2604.10248v1 Announce Type: new Abstract: Complex systems such as aircraft engines, turbines, and industrial machinery often operate under dynamically changing conditions. These varying operatin
arXiv:2604.09819v1 Announce Type: cross Abstract: We introduce ACCIDENT, a benchmark dataset for traffic accident detection in CCTV footage, designed to evaluate models in supervised (IID and OOD) and
arXiv:2601.03641v4 Announce Type: replace Abstract: Large Language Model (LLM)-based agents significantly extend the utility of LLMs by interacting with dynamic environments. However, enabling agents
arXiv:2601.04672v2 Announce Type: replace-cross Abstract: Agricultural disease diagnosis challenges VLMs, as conventional fine-tuning requires extensive labels, lacks interpretability, and generalizes
Anthropic's alignment team published research showing that realistic AI training processes can accidentally produce misaligned models through 'reward hacking' — where an AI fools its training process
arXiv:2604.10702v1 Announce Type: cross Abstract: Multi-parametric prostate MRI -- combining T2-weighted, apparent diffusion coefficient, and high b-value diffusion-weighted sequences -- is central to
arXiv:2508.03793v2 Announce Type: replace Abstract: Long-context large language models (LLMs), such as Gemini-2.5-Pro and Claude-Sonnet-4, are increasingly used to empower advanced AI systems, includi
arXiv:2604.11304v1 Announce Type: new Abstract: Existing AI benchmarks lack the fidelity to assess economically meaningful progress on professional workflows. To evaluate frontier AI agents in a high-
arXiv:2604.11390v1 Announce Type: new Abstract: While Hyperspectral Anomaly Detection (HAD) excels at identifying sparse targets in complex scenes, existing models remain trapped in a scalar 'reconstr
arXiv:2604.10389v1 Announce Type: new Abstract: Terminology substitution errors in clinical notes, where one medical term is replaced by a linguistically valid but clinically different term, pose a pe
arXiv:2604.11162v1 Announce Type: new Abstract: Accurate defect segmentation is critical for industrial inspection, yet dense pixel-level annotations are rarely available. A common workaround is to co
arXiv:2509.22830v3 Announce Type: replace Abstract: The growing deployment of large language model (LLM) based agents that interact with external environments has created new attack surfaces for adver
arXiv:2604.11320v1 Announce Type: new Abstract: Robot grasping of desktop object is widely used in intelligent manufacturing, logistics, and agriculture.Although vision-language models (VLMs) show str
arXiv:2604.11741v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown impressive capabilities in perceptual tasks, yet they degrade in complex multi-hop reasoning under multiplayer
arXiv:2505.11237v3 Announce Type: replace-cross Abstract: Metaphorical imagination, the ability to connect seemingly unrelated concepts, is fundamental to human cognition and communication. While unde
arXiv:2604.11470v1 Announce Type: new Abstract: Real-world image super-resolution is particularly challenging for diffusion models because real degradations are complex, heterogeneous, and rarely mode
arXiv:2404.18905v3 Announce Type: replace-cross Abstract: Randomized trials are considered the gold standard for making informed decisions in medicine, yet they often lack generalizability to the pati
arXiv:2604.11258v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) in healthcare suffer from severe confirmation bias, often hallucinating visual details to support initial, pote
arXiv:2604.09666v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) and its graph-based extensions (GraphRAG) are effective paradigms for improving large language model (LLM) reason
arXiv:2604.10077v1 Announce Type: new Abstract: In Document Understanding, the challenge of reconstructing damaged, occluded, or incomplete text remains a critical yet unexplored problem. Subsequent d
arXiv:2604.07389v2 Announce Type: replace Abstract: Crime pattern analysis is critical for law enforcement and predictive policing, yet the surge in criminal activities from rapid urbanization creates
arXiv:2510.11217v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) combines the language understanding and reasoning power of large language models (LLMs) with external ret
arXiv:2511.11232v2 Announce Type: replace Abstract: Constructing a unified 3D scene understanding model has long been hindered by the significant topological discrepancies across different sensor moda
arXiv:2512.00375v2 Announce Type: replace Abstract: Existing motion planning methods often struggle with rapid-motion obstacles due to an insufficient understanding of environmental changes. To addres
arXiv:2604.09603v1 Announce Type: cross Abstract: Speculative Decoding promises to accelerate the inference of Large Language Models, yet its efficacy often degrades in production-grade serving. Exist
arXiv:2604.05005v2 Announce Type: replace-cross Abstract: Large language models are increasingly used as educational assistants, yet evaluation of their educational capabilities remains concentrated o
arXiv:2511.18957v2 Announce Type: replace Abstract: Video virtual try-on technology provides a cost-effective solution for creating marketing videos in fashion e-commerce. However, its practical adopt
arXiv:2604.11775v1 Announce Type: cross Abstract: Perturbation-based explainability methods such as KernelSHAP provide model-agnostic attributions but are typically impractical for patch-based 3D medi
arXiv:2604.11174v1 Announce Type: cross Abstract: Recent progress in embodied AI has produced a growing ecosystem of robot policies, foundation models, and modular runtimes. However, current evaluatio
arXiv:2604.10117v1 Announce Type: new Abstract: Photoplethysmography (PPG)-based blood pressure (BP) estimation is a challenging task, particularly on resource-constrained wearable devices. However, f
arXiv:2604.10904v1 Announce Type: cross Abstract: AI-based image reconstruction models are increasingly deployed in clinical workflows to improve image quality from noisy data, such as low-dose X-rays
arXiv:2604.11209v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable success across a wide range of applications especially when augmented by external knowledge thro
arXiv:2601.05505v2 Announce Type: replace Abstract: The stateless architecture of Large Language Models inherently lacks the mechanism to preserve dynamic context, compelling agents to redundantly rep
arXiv:2604.11001v1 Announce Type: new Abstract: Large language models (LLMs) have been widely adopted due to their great performance across a wide range of applications. ChatGPT and Gemini now serve h
arXiv:2604.09989v1 Announce Type: cross Abstract: Recently, synthetic palmprints have been increasingly used as substitutes for real data to train recognition models. To be effective, such synthetic d
For years, we’ve been building our cyber defense program on the principles of democratized access, iterative deployment, and ecosystem resilience. As model capabilities advance, our approach is to sca
arXiv:2604.11378v1 Announce Type: new Abstract: The dominant paradigm for building LLM based agents is the Agent Loop, an iterative cycle where a single language model decides what to do next by readi
arXiv:2604.11467v1 Announce Type: new Abstract: Explainable AI (XAI) methods reveal which features influence model predictions, yet provide limited means for practitioners to act on these explanations
arXiv:2604.11518v1 Announce Type: cross Abstract: Cross-language migration of large software systems is a persistent engineering challenge, particularly when the source codebase evolves rapidly. We pr
arXiv:2603.07819v3 Announce Type: replace Abstract: Accurate estimation of pasture biomass from agricultural imagery is critical for sustainable livestock management, yet existing methods are limited
arXiv:2604.09990v1 Announce Type: new Abstract: Gait recognition is a biometric modality that identifies individuals from their characteristic walking patterns. Unlike conventional biometric traits, g
arXiv:2601.01041v3 Announce Type: replace Abstract: Deepfake detection remains highly challenging, particularly in cross-dataset scenarios and complex real-world settings. This challenge mainly arises
arXiv:2604.11344v1 Announce Type: cross Abstract: Embedding-as-a-Service (EaaS) has become an important semantic infrastructure for natural language and multimedia applications, but it is highly vulne
arXiv:2511.12895v2 Announce Type: replace Abstract: High Dynamic Range (HDR) 3D reconstruction is pivotal for professional content creation in filmmaking and virtual production. Existing methods typic
Hermes Trismegistus is likely a language model released by Nous Research, continuing their Hermes series of fine-tuned models known for instruction-following, reasoning, and agentic capabilities. The
arXiv:2604.11072v1 Announce Type: new Abstract: Existing approaches to monitoring AI agents rely on supervised evaluation: human-written rules or LLM-based judges that check for known failure modes. H
arXiv:2604.10955v1 Announce Type: new Abstract: Hypergraph neural networks (HGNNs) have shown remarkable potential in modeling high-order relationships that naturally arise in many real-world data dom
A Reddit user on r/StableDiffusion built a locally-running RAG (Retrieval-Augmented Generation) engine designed to eliminate the need for manually crafting lengthy, model-specific image generation pro
I'm excited about voice as a UI layer for existing visual applications — where speech and screen update together. This goes well beyond voice-only use cases like call center automation. The barrier ha
Today, we're thrilled to announce that BigQuery Graph is now available in preview. With BigQuery Graph, we’ve built an easy-to-use, highly scalable graph analytics solution for data engineers, data an
arXiv:2604.09554v1 Announce Type: new Abstract: Optimism for accelerating scientific discovery with AI continues to grow. Current applications of AI in scientific research range from training dedicate
arXiv:2604.11365v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) has been widely used for automated reasoning data exploration, but current supervision extraction methods remain ineffici
arXiv:2604.11789v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have achieved remarkable progress in general-purpose vision--language understanding, yet they remain limited in tasks req
arXiv:2604.10024v1 Announce Type: cross Abstract: Long video summarization presents significant challenges for current multimodal large language models (MLLMs), particularly in maintaining temporal fi
arXiv:2604.01306v2 Announce Type: replace Abstract: Evaluating scientific arguments requires assessing the strict consistency between a claim and its underlying multimodal evidence. However, existing
arXiv:2604.10636v1 Announce Type: new Abstract: Training machine learning models requires the storage of large datasets, which often contain sensitive or private data. Storing data is associated with
arXiv:2308.12067v3 Announce Type: replace-cross Abstract: Multimodal large language models are typically trained in two stages: first pre-training on image-text pairs, and then fine-tuning using super
arXiv:2604.11259v1 Announce Type: new Abstract: Mobile GUI agents powered by Multimodal Large Language Models (MLLMs) can execute complex tasks on mobile devices. Despite this progress, most existing