Knowledge catalogue
arXiv:2609.00510v1 Announce Type: new Abstract: Artificial intelligence systems increasingly enact market-facing promises through chatbots, recommendation systems, automated decisions, and generative
arXiv:2607.17883v2 Announce Type: replace-cross Abstract: Enterprises will not deploy AI agents they cannot trust, and the most-cited reason for distrust is hallucination: confident, fluent output tha
arXiv:2608.29347v1 Announce Type: new Abstract: Operators remain essential to Remotely Operated Vehicle (ROV) operation, yet often suffer from low situational awareness and high workload, both of whic
arXiv:2608.30033v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to simulate human behavior but frequently fail to exhibit realistic cognitive constraints, sufferin
arXiv:2608.28990v1 Announce Type: new Abstract: Protein co-abundance clusters preserved across tissues can reveal shared disease mechanisms and candidate therapeutic targets, particularly when protein
arXiv:2608.30478v1 Announce Type: new Abstract: Cognitive language agents have achieved substantial progress by equipping language models with memory, tools, and decision-making procedures, enabling a
arXiv:2607.09600v2 Announce Type: replace Abstract: Enhancing the reasoning capabilities of large language model (LLM) agents requires effective orchestration of diverse expert models and tools. Howev
arXiv:2608.29237v1 Announce Type: cross Abstract: Insect pollination is critical for global food production, yet monitoring pollinators at commercial farm scale remains a challenge. Recent advances in
arXiv:2608.28637v1 Announce Type: new Abstract: Autonomous scientific discovery systems can generate large numbers of research ideas, experiments, and manuscripts with minimal human intervention. As t
arXiv:2310.04363v3 Announce Type: replace-cross Abstract: Autoregressive large language models (LLMs) compress knowledge from their training data through next-token conditional distributions. This lim
arXiv:2608.29973v1 Announce Type: new Abstract: Cryptocurrency markets generate high-frequency, multi-source data that is expensive to work with unless a team already has commercial-grade streaming an
arXiv:2603.16138v2 Announce Type: replace-cross Abstract: Generative search systems are increasingly replacing link-based retrieval with AI-generated summaries, yet little is known about how these sys
arXiv:2608.30345v1 Announce Type: new Abstract: Generating multiple diverse and high-quality solutions is valuable for many applications, such as code-test generation and drug discovery. However, Larg
arXiv:2608.29128v1 Announce Type: new Abstract: Tool-using agents are commonly evaluated by a single bit: whether an end-to-end workflow completed. This metric fails to distinguish failures that matte
arXiv:2608.30656v1 Announce Type: new Abstract: Proactive tamper localization embeds an imperceptible signal into an image prior to distribution, enabling pixel-level manipulation detection. Existing
arXiv:2606.18586v2 Announce Type: replace-cross Abstract: Physical events are not understood by their names alone, but by the causal state changes that compose them. A clip-level label such as 'bounce
arXiv:2608.29529v1 Announce Type: cross Abstract: Semantic alignment between specialized normative texts is challenging when equivalent requirements use different terms, syntax, and levels of abstract
arXiv:2506.03828v4 Announce Type: replace Abstract: AI for Industrial Asset Lifecycle Management aims to automate complex operational workflows, such as condition monitoring and maintenance scheduling
arXiv:2608.28790v1 Announce Type: cross Abstract: Technical operations teams resolve large volumes of incidents by synthesizing fragmented evidence from ticket text, historical cases, system logs, and
arXiv:2601.03087v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit systematic biases across demographic groups. Auditing is proposed as an accountability tool for black-box
arXiv:2608.30372v1 Announce Type: new Abstract: As Large Language Models rapidly advance, performance on standard multiple-choice question answering (MCQA) benchmarks is reaching saturation. While the
arXiv:2608.28945v1 Announce Type: new Abstract: Automating alignment research may accelerate progress toward aligned AI, but whether it does is hard to measure. Luckily, many alignment failures, such
arXiv:2608.30581v1 Announce Type: new Abstract: Large language models (LLMs) are used as post hoc explainers of sequential decision-making policies, producing natural-language explanations of why an a
arXiv:2608.29463v1 Announce Type: cross Abstract: A benchmark score is a joint property of the model, the evaluation harness, the elicitation budget, the sampled population, and contamination status.
arXiv:2608.30364v1 Announce Type: new Abstract: Retail banking attrition is usually represented as a terminal binary event, even though client relationships often weaken earlier through partial moveme
arXiv:2608.30373v1 Announce Type: new Abstract: Multi-Agent Debate (MAD) has been widely adopted to improve LLM-based evaluation by prompting multiple agents to negotiate and reach a consensus. Howeve
arXiv:2608.29804v1 Announce Type: new Abstract: Virtual try-on (VTON) requires not only realistic generation but also faithful preservation of garment characteristics. However, existing evaluation met
arXiv:2608.30256v1 Announce Type: cross Abstract: Logical reasoning with large language models (LLMs) is a critical capability, as it reflects a system's ability to correctly deduce hypotheses from a
arXiv:2608.30319v1 Announce Type: cross Abstract: Large language models (LLMs) finetuned for specialized domains represent crucial high-impact applications. Inference-time alignment improves safety de
arXiv:2608.28967v1 Announce Type: cross Abstract: Electroencephalography (EEG)-based robotic control is commonly formulated as a direct classification problem, in which electrical neural signals are m
arXiv:2510.01359v3 Announce Type: replace-cross Abstract: Code-capable large language model (LLM) agents are embedded in software engineering workflows where they can read, write, and execute code, ra
arXiv:2608.30047v1 Announce Type: new Abstract: Recent AI systems promise autonomous scientific discovery, claiming to discover algorithms and produce research papers, yet understanding whether they e
arXiv:2608.30689v1 Announce Type: new Abstract: Autoregressive large models have recently advanced Text-to-SVG generation from simple icons to complex, long-context graphics, yet standard autoregressi
arXiv:2608.28628v1 Announce Type: new Abstract: Compound drought-to-extreme-precipitation (CDEP) events are recognized in climate science as a growing driver of extreme impact, but whether this recogn
arXiv:2608.30201v1 Announce Type: new Abstract: Directly robustifying small-signal stability in AC optimal power flow is challenging since the stability boundary in the original uncertainty space is i
arXiv:2608.29644v1 Announce Type: cross Abstract: Attributing an artwork to an artist has traditionally relied on detailed visual observations and descriptions, known as stylistic analysis in art hist
arXiv:2608.28896v1 Announce Type: new Abstract: Industrial process networks do not maintain a single effective topology while operating: streams are throttled or bypassed, and units move between idle,
arXiv:2608.30220v1 Announce Type: new Abstract: Reliable three-dimensional (3D) navigation of magnetically actuated untethered microrobots remains a major barrier to clinical translation. X-ray fluoro
arXiv:2509.04859v4 Announce Type: replace Abstract: Fast and efficient photorealistic 3D reconstruction with (semantic) Gaussian Splatting (GS) is crucial for time-critical robotic perception and navi
arXiv:2608.29675v1 Announce Type: cross Abstract: Repository exploration is a distinct and costly stage of coding-agent pipelines: before generating a patch, an agent must identify which repository fi
arXiv:2608.29352v1 Announce Type: new Abstract: Large Language Models (LLMs) still exhibit limited capability in following complex instructions. While existing approaches often rely on preference lear
arXiv:2608.29966v1 Announce Type: new Abstract: Domain adaptation of large language models increasingly depends on constructing high-quality training data, yet existing data-preparation pipelines typi
arXiv:2607.11577v2 Announce Type: replace-cross Abstract: Conventional Graph Neural Networks (GNNs) couple feature transformation and neighborhood aggregation, which often renders them vulnerable to t
arXiv:2601.22118v3 Announce Type: replace Abstract: Artificial Intelligence (AI) has been on the rise in many domains, including numerous safety-critical applications. However, for complex systems in
arXiv:2608.30405v1 Announce Type: new Abstract: Medical knowledge changes continually, making large language models vulnerable to relying on outdated yet clinically plausible information. We study whe
arXiv:2608.29307v1 Announce Type: cross Abstract: Language models increasingly answer questions by consulting retrieved documents rather than memory alone, a design now common in search assistants and
arXiv:2608.29037v1 Announce Type: cross Abstract: Real-world degradations such as blur, shadow, distortion, and moire patterns severely impair the document question-answering capabilities of Multimoda
arXiv:2608.29711v1 Announce Type: new Abstract: While MLLMs have made significant strides in chart comprehension and video understanding, current evaluations largely isolate these capabilities, leavin
arXiv:2608.28791v1 Announce Type: new Abstract: Real-time decision-making for enhanced geothermal systems (EGS) is challenging because long-term production periods involve high-dimensional control spa
arXiv:2608.28968v1 Announce Type: new Abstract: Semantic Search on LinkedIn must retrieve relevant profiles from a corpus of hundreds of millions in response to natural-language queries such as 'a fin
arXiv:2608.29896v1 Announce Type: new Abstract: A robot's effective ``mind'' need not reside in a single policy. It can emerge when specialized components perceive, reason, predict, act, verify, and r
arXiv:2608.29738v1 Announce Type: new Abstract: Large language models (LLMs) can generate apparently highly persuasive text, but does sounding persuasive mean arguing well? We introduce extsc{Persuasi
arXiv:2608.28714v1 Announce Type: cross Abstract: Objective: Deep learning accelerates brain MRI four- to tenfold, but models can erase lesions or synthesize false tissue - failures pixel-averaged met
arXiv:2608.30429v1 Announce Type: new Abstract: LLM-based agent systems increasingly adopt skill-based architectures to reduce repetitive reasoning costs and improve stable, efficient task execution.
arXiv:2608.28820v1 Announce Type: new Abstract: Computational pathology (CompPath) is transforming medicine by leveraging artificial intelligence (AI) algorithms to support diagnosis, prognosis, and t
arXiv:2608.30223v1 Announce Type: cross Abstract: We propose a new design of fair classifiers for multi-class classification problems in the presence of vector-valued sensitive attributes. In that sce
arXiv:2608.29384v1 Announce Type: new Abstract: The growing availability of dense commercial Synthetic Aperture Radar (SAR) time series enables temporal Interferometric SAR (InSAR) analysis, but fixed
Introduction Beginning in 2024 Mandiant investigated a string of compromises affecting Brazilian financial services, retail, and eCommerce organizations. Google Threat Intelligence Group (GTIG) tracks
arXiv:2608.31005v1 Announce Type: new Abstract: Existing long-video agents acquire evidence through one uniform behavior, ignoring whether the required evidence is concentrated, requires broad occurre
arXiv:2608.30419v1 Announce Type: new Abstract: Healthcare workforce scheduling is an NP-hard optimization problem requiring simultaneous satisfaction of labor regulations, coverage requirements, empl