Knowledge catalogue
arXiv:2604.09619v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into educational ecosystems promises to democratize access to personalized tutoring, yet the readiness
arXiv:2604.10905v1 Announce Type: cross Abstract: We present Audio Flamingo Next (AF-Next), the next-generation and most capable large audio-language model in the Audio Flamingo series, designed to ad
arXiv:2511.15875v2 Announce Type: replace Abstract: The automated analysis of historical documents, particularly maps, has drastically benefited from advances in deep learning and its success across v
arXiv:2604.10598v1 Announce Type: new Abstract: Human-in-the-loop (HITL) UAV operation is essential in complex and safety-critical aerial surveying environments, where human operators provide navigati
arXiv:2604.11560v1 Announce Type: cross Abstract: 1. Natural sounds have been recorded for millions of hours over the previous decades using passive acoustic monitoring. Improvements in deep learning
arXiv:2604.10528v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) demonstrate remarkable zero-shot recognition capabilities across a diverse spectrum of multimodal tasks, it yet rema
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:2603.13941v2 Announce Type: replace Abstract: Growing waste streams and the transition to a circular economy require efficient automated waste sorting. In industrial settings, materials move on
arXiv:2604.11324v1 Announce Type: cross Abstract: IoT botnet detection has advanced, yet most published systems are validated on a single dataset and rarely generalise across environments. Heterogeneo
arXiv:2604.11424v1 Announce Type: new Abstract: Speech Language Models (SLMs) exhibit strong semantic understanding, yet their generated speech often sounds flat and fails to convey expressive intent,
arXiv:2604.11019v1 Announce Type: cross Abstract: Professional designers work from client briefs that specify goals and constraints but often lack concrete design details. Translating these abstract r
arXiv:2604.10585v1 Announce Type: cross Abstract: Modern large language models (LLMs) are increasingly fine-tuned via reinforcement learning from human feedback (RLHF) or related reward optimisation s
arXiv:2511.21998v2 Announce Type: replace Abstract: Multi-modal Large Language Models (LLM) have advanced conversational abilities but struggle with providing live, interactive step-by-step guidance,
Catch Or Dagan, AI21's Chief Product & Strategy Officer, at #AIDev26 on April 29: 'An End to Manual Tinkering: Optimizing Accuracy, Cost & Latency in Real-World Agents'. We'll be at Booth 121. See you
arXiv:2602.03108v3 Announce Type: replace Abstract: We introduce ChemPro, a progressive benchmark with 4100 natural language question-answer pairs in Chemistry, across 4 coherent sections of difficult
arXiv:2604.09812v1 Announce Type: new Abstract: Recurrent claims present a major challenge for automated fact-checking systems designed to combat misinformation, especially in multilingual settings. W
arXiv:2604.11790v1 Announce Type: cross Abstract: Tool-augmented Large Language Model (LLM) agents have demonstrated impressive capabilities in automating complex, multi-step real-world tasks, yet rem
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:2604.10035v1 Announce Type: cross Abstract: In this study, we developed a computational implementation for a model of metaphor comprehension based on the theory of indeterminate natural transfor
arXiv:2604.10505v1 Announce Type: new Abstract: Agent based systems are more common than we may think. A Promise Theory perspective on cooperation, in systems of human-machine agents, offers a unified
arXiv:2508.16644v4 Announce Type: replace Abstract: Diffusion models excel at photorealistic synthesis but struggle with precise object counts, especially in high-density settings. We introduce COUNTL
arXiv:2604.11119v1 Announce Type: cross Abstract: This paper reorganizes the current manuscript around the DPO versus DDO-RM preference-optimization project and focuses on two parts: the algorithmic v
arXiv:2604.10377v1 Announce Type: new Abstract: Deep functional maps, leveraging learned feature extractors and spectral correspondence solvers, are fundamental to non-rigid 3D shape matching. Based o
arXiv:2604.11206v1 Announce Type: cross Abstract: Digital nudging systems lack architectural guidance for translating behavioral science into software design. While research identifies nudge strategie
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:2604.05896v2 Announce Type: replace Abstract: As robots increasingly operate in shared, safety critical environments, acting safely is no longer sufficient robots must also make their safety dec
arXiv:2604.10425v1 Announce Type: new Abstract: Recent advancements in Vision-Language Models (VLMs) have revolutionized general visual understanding. However, their application in the food domain rem
arXiv:2603.07462v2 Announce Type: replace Abstract: Determining whether AI systems process information similarly to humans is central to cognitive science and trustworthy AI. While modern AI models ca
arXiv:2508.15452v3 Announce Type: replace-cross Abstract: Numerous deep learning-based solutions have been developed for the automatic recognition of breast cancer using mammography images. However, t
arXiv:2512.18994v2 Announce Type: replace Abstract: Taxonomic classification of ecological families, genera, and species underpins biodiversity monitoring and conservation. Existing computer vision me
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:2604.09876v1 Announce Type: cross Abstract: Generative user interfaces (UIs) create new opportunities to adapt interfaces to individual users on demand, but personalization remains difficult bec
arXiv:2604.09561v1 Announce Type: cross Abstract: We present the first empirical analysis of social structure formation among autonomous AI agents on a live network. Our study examines 626 agents -- p
arXiv:2604.10978v1 Announce Type: cross Abstract: This study investigates students' AI use concealment intention in higher education by integrating the cognition-affect-conation (CAC) framework with a
arXiv:2604.10991v1 Announce Type: cross Abstract: The growing use of generative artificial intelligence (AI) in academic writing has raised increasing concerns regarding transparency and academic inte
arXiv:2502.18026v3 Announce Type: replace-cross Abstract: Retrieving targeted pathways in biological knowledge bases, particularly when incorporating wet-lab experimental data, remains a challenging t
arXiv:2604.10224v1 Announce Type: cross Abstract: Machine Learning (ML) systems are increasingly used to support decision-making processes that affect individuals. However, these systems often rely on
arXiv:2508.17431v3 Announce Type: replace-cross Abstract: Person re-identification (re-ID) is a fundamental task in intelligent surveillance and public safety. Federated learning (FL) provides a priva
arXiv:2604.10954v1 Announce Type: new Abstract: Diffusion-based image editing models have achieved significant progress in real world applications. However, conventional models typically rely on natur
arXiv:2604.11104v1 Announce Type: new Abstract: This paper presents an empirical study of a multi-model zero-shot pipeline for knowledge graph construction and exploitation, executed entirely through
arXiv:2602.09932v2 Announce Type: replace Abstract: Building height (BH) and footprint (BF) are fundamental urban morphological parameters required by climate modelling, disaster-risk assessment, and
Abner Li / 9to5Google: Google designates “back button hijacking” as malicious, saying sites interfering with a browser's back button function may be demoted in Search starting in June — Websites that
arXiv:2604.10658v1 Announce Type: new Abstract: Institutional decisions -- regulatory compliance, clinical triage, prior authorization appeal -- require a different AI architecture than general-purpos
arXiv:2604.10311v1 Announce Type: new Abstract: Artificial Intelligence (AI) models, encompassing both traditional machine learning (ML) and more advanced approaches such as deep learning and large la
arXiv:2604.10675v1 Announce Type: new Abstract: We propose a method to learn explicit, class-conditioned spatial priors for object placement in natural scenes by distilling the implicit placement know
arXiv:2512.03743v5 Announce Type: replace-cross Abstract: Dexterous manipulation is limited by both control and design, without consensus as to what makes manipulators best for performing dexterous ta
arXiv:2604.11133v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being explored for clinical question answering and decision support, yet safe deployment critically requir
arXiv:2604.09601v1 Announce Type: new Abstract: Discovering predictive alpha factors in quantitative finance remains a formidable challenge due to the vast combinatorial search space and inherently lo
arXiv:2604.09960v1 Announce Type: new Abstract: The rapid adoption of large language models has introduced a new class of AI-generated fake news that coexists with traditional human-written misinforma
arXiv:2604.10130v1 Announce Type: new Abstract: Background: Manual delineation of target volumes in head and neck cancer (HNC) remains a significant bottleneck in radiotherapy planning, characterized
arXiv:2604.11609v1 Announce Type: new Abstract: Large language models exhibit sycophantic tendencies--validating incorrect user beliefs to appear agreeable. We investigate whether this behavior varies
arXiv:2604.10707v1 Announce Type: new Abstract: While appearance-based gaze estimation has achieved significant improvements in accuracy and domain adaptation, the fairness of these systems across dif
arXiv:2604.11689v1 Announce Type: new Abstract: While the shortage of explicit action data limits Vision-Language-Action (VLA) models, human action videos offer a scalable yet unlabeled data source. A
arXiv:2505.21996v3 Announce Type: replace-cross Abstract: Foundational world models must be both interactive and preserve spatiotemporal coherence for effective future planning with action choices. Ho
arXiv:2604.09566v1 Announce Type: cross Abstract: The application of games as a therapeutic tool for cognitive training is beneficial for patients with cognitive impairments. However, effective game d
arXiv:2604.09604v1 Announce Type: new Abstract: Exploration and goal-directed navigation in unknown layouts are central to inspection, logistics, and search-and-rescue. We ask whether large language m
arXiv:2504.14386v2 Announce Type: replace-cross Abstract: Positional embeddings (PE) play a crucial role in Vision Transformers (ViTs) by providing spatial information otherwise lost due to the permut
arXiv:2512.20136v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has recently been extended to multimodal settings, connecting multimodal large language models (MLLMs) wi
arXiv:2604.10534v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is a new and emerging technology that extends the functionality of large language models, improving workflows but als
arXiv:2604.10989v1 Announce Type: new Abstract: Emergency situations in scheduling systems often trigger local functional failures that undermine system stability and even cause system collapse. Exist