Knowledge catalogue
arXiv:2604.22189v1 Announce Type: new Abstract: This letter presents an energy-efficient multi-robot coverage path planning (MRCPP) framework for large, nonconvex Regions of Interest (ROI) containing
arXiv:2604.22548v1 Announce Type: cross Abstract: Problem definition: Data-driven models in machine learning have enabled efficient management of production systems. However, a majority of machine lea
OpenAI's core principles outline the company's commitment to developing artificial intelligence safely and beneficially, emphasizing responsible AI development and deployment. These principles likely
Google Cloud Next ‘26 took place this week in Las Vegas, and the energy was incredible as we welcomed over 32,000 leaders, developers, and partners to explore the Agentic Era with us. Across three key
arXiv:2604.21251v1 Announce Type: cross Abstract: Large language models (LLMs) trained on unfiltered corpora inherently risk retaining sensitive information, necessitating selective knowledge unlearni
arXiv:2603.27189v2 Announce Type: replace-cross Abstract: Conformal prediction provides rigorous distribution-free finite-sample guarantees for marginal coverage under the assumption of exchangeabilit
arXiv:2604.20911v1 Announce Type: cross Abstract: LLM agents deployed in production operate under operator-defined behavioral policies (system-prompt instructions such as prohibitions on credential di
arXiv:2506.01937v2 Announce Type: replace Abstract: Reward models are used throughout the post-training of language models to capture nuanced signals from preference data and provide a training target
arXiv:2604.21076v1 Announce Type: cross Abstract: Medication reconciliation at clinical handoffs is a high-stakes, error-prone process. Large language models are increasingly proposed to assist with t
Tesla FSD is the first AI saving lives at scale....on real roads every single day Road accidents kill 1.19 million people every year - the #1 cause of death for ages 5–29 94%+ of crashes are caused by
We’ve invested deeply in security at Replit, including our recent launches with Security Agent + Auto-Protect. If you want to move your app to Replit, we’re offering free app imports for a limited tim
GPT-5.5 is out. It's available in OpenAI Codex and is rolling out to paid ChatGPT subscribers. I've had some preview access and found it to be a fast, effective and highly capable model. As is usually
arXiv:2604.20347v1 Announce Type: cross Abstract: Ultrasound (US)-guided needle insertion is a critical yet challenging procedure due to dynamic imaging conditions and difficulties in needle visualiza
arXiv:2512.15808v2 Announce Type: replace-cross Abstract: Foundation models (FMs) are driving a prominent shift in biomedical imaging from task-specific models to unified backbone models for diverse t
arXiv:2604.20191v1 Announce Type: cross Abstract: Interpretable driver attention prediction is crucial for human-like autonomous driving. However, existing datasets provide only scene-level global gaz
arXiv:2604.20652v1 Announce Type: new Abstract: Large language models trained on human feedback may suppress fraud warnings when investors arrive already persuaded of a fraudulent opportunity. We test
Last night was the biggest disaster in the history of Tesla. Let me walk you through what actually happened on that earnings call, because the headlines are doing you a disservice: Elon Musk got on th
arXiv:2410.06239v3 Announce Type: replace Abstract: Enabling robots to autonomously navigate unknown, complex, and dynamic real-world environments presents several challenges, including imperfect perc
arXiv:2604.20423v1 Announce Type: new Abstract: The rapid iteration of autonomous driving algorithms has created a growing demand for high-fidelity, replayable, and diagnosable testing data. However,
arXiv:2501.00112v2 Announce Type: replace Abstract: This work proposes QuadPiPS, a perception-informed framework for quadrupedal foothold planning in the perception space. QuadPiPS employs a novel ego
arXiv:2604.20087v1 Announce Type: new Abstract: Skills have become the de facto way to enable LLM agents to perform complex real-world tasks with customized instructions, workflows, and tools, but how
arXiv:2604.20190v1 Announce Type: new Abstract: Wildfire monitoring requires timely, actionable situational awareness from airborne platforms, yet existing aerial visual question answering (VQA) bench
arXiv:2502.02779v3 Announce Type: replace-cross Abstract: Head computed tomography (CT) imaging is a widely-used imaging modality with multitudes of medical indications, particularly in assessing path
Today, we announced the preview of Spanner Omni, a downloadable version of Spanner, that expands its industry-leading distributed database capabilities beyond Google Cloud. This enables enterprises to
arXiv:2604.19342v1 Announce Type: new Abstract: Generative AI-powered by Large Language Models (LLMs)-is increasingly deployed in industry across healthcare decision support, financial analytics, ente
arXiv:2604.18663v1 Announce Type: cross Abstract: Existing jamming attacks on Retrieval-Augmented Generation (RAG) systems typically induce explicit refusals or denial-of-service behaviors, which are
The era of agentic AI is accelerating from human- to machine-speed operations, while also creating profound stress on legacy technology infrastructure. This new reality pushes foundational systems to
arXiv:2604.18963v1 Announce Type: cross Abstract: Knowledge distillation (KD) transfers capabilities from large language models (LLMs) to smaller students, yet it can fail unpredictably and also under
arXiv:2604.19522v1 Announce Type: new Abstract: Bimanual mobile manipulation requires a seamless integration between high-level semantic reasoning and safe, compliant physical interaction - a challeng
arXiv:2604.18901v1 Announce Type: cross Abstract: Harmful intent is geometrically recoverable from large language model residual streams: as a linear direction in most layers, and as angular deviation
arXiv:2604.18847v1 Announce Type: new Abstract: As LM agents gain the ability to execute actions on real computer systems, we need ways to not only prevent harmful actions at scale but also effectivel
In the early days of generative AI, building safe and reliable business tools took massive engineering effort and a high tolerance for trial and error. We helped solve that with Vertex AI, our trusted
arXiv:2604.18610v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but incur substantial computational overhead and energy consumption during
The first wave of AI changed how we find information; the next wave is changing how we get work done. Today, we’re enhancing our most powerful AI tools and bringing them together under one roof. Gemin
arXiv:2604.18718v1 Announce Type: cross Abstract: Agentic security systems increasingly audit live targets with tool-using LLMs, but prior systems fix a single coordination topology, leaving unclear w
arXiv:2412.01782v4 Announce Type: replace-cross Abstract: DETR and its variants have emerged as promising architectures for object detection, offering an end-to-end prediction pipeline. In practice, h
arXiv:2508.00161v3 Announce Type: replace-cross Abstract: The releases of powerful open-weight large language models (LLMs) are often not accompanied by access to their full training data. Existing in
arXiv:2508.13401v3 Announce Type: replace Abstract: This report presents an overview of the AIM 2025 RipSeg Challenge, a competition designed to advance techniques for automatic rip current segmentati
arXiv:2604.17998v1 Announce Type: new Abstract: Anomaly detection in multivariate time series is a central challenge in industrial monitoring, as failures frequently arise from complex temporal dynami
arXiv:2507.20409v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting helps models think step by step. But naive CoT breaks down in visually grounded social tasks, where models must per
arXiv:2604.17941v1 Announce Type: cross Abstract: Recent work has increasingly explored neuron-level interpretation in vision-language models (VLMs) to identify neurons critical to final predictions.
arXiv:2604.16436v1 Announce Type: cross Abstract: This paper develops an end-to-end fuzzy encoder-decoder architecture for enhancing vision-based multi-modal deep spiking Q-networks in autonomous driv
arXiv:2604.16422v1 Announce Type: new Abstract: The injection of domain-specific knowledge is crucial for adapting language models (LMs) to specialized fields such as biomedicine. While most current a
arXiv:2601.09853v2 Announce Type: replace Abstract: Real-world health questions from patients often unintentionally embed false assumptions or premises. In such cases, safe medical communication typic
arXiv:2604.17070v1 Announce Type: new Abstract: This report presents the NTIRE 2026 Rip Current Detection and Segmentation (RipDetSeg) Challenge, which targets automatic rip current understanding in i
arXiv:2506.06024v2 Announce Type: replace-cross Abstract: Signal restoration and inverse problems are key elements in most real-world data science applications. In the past decades, with the emergence
arXiv:2604.17301v1 Announce Type: new Abstract: Detecting harmful content in multi turn dialogue requires reasoning over the full conversational context rather than isolated utterances. However, most
arXiv:2604.16993v1 Announce Type: cross Abstract: As embodied AI transitions to real-world deployment, the success of the Vision-and-Language Navigation (VLN) task tends to evolve from mere reachabili
arXiv:2604.16848v1 Announce Type: new Abstract: Fine-grained semantic segmentation of transmission-corridor point clouds is fundamental for intelligent power-line inspection. However, current progress
arXiv:2604.15415v1 Announce Type: cross Abstract: Large language models (LLMs) have evolved into autonomous agents that rely on open skill ecosystems (e.g., ClawHub and Skills.Rest), hosting numerous
F1's 2026 regulations feature new V6 hybrid engines with a near 50/50 split between combustion and electrical power, creating challenges with energy management and an unpopular driving style among dri
arXiv:2506.15064v3 Announce Type: replace Abstract: Deep neural networks are powerful tools for solving nonlinear problems in science and engineering, but training highly accurate models becomes chall
arXiv:2604.15597v1 Announce Type: new Abstract: Large Language Models (LLMs) are poised to disrupt knowledge work, with the emergence of delegated work as a new interaction paradigm (e.g., vibe coding
arXiv:2511.10262v3 Announce Type: replace-cross Abstract: Full-Duplex Speech Language Models (FD-SLMs) enable real-time, overlapping conversational interactions, offering a more dynamic user experienc
This post compares AI assistants' responses to a request about driving to get gas, claiming that Grok 4.3 provides the requested information while ChatGPT, Claude, and Gemini decline or suggest altern
Simon Willison documents the differences between Anthropic's Claude Opus 4.6 and 4.7 system prompts, analyzing changes that Anthropic made public. The notes likely highlight modifications to model beh
arXiv:2604.13097v1 Announce Type: cross Abstract: Embodied agents increasingly rely on modular capabilities that can be installed, upgraded, composed, and governed at runtime. Prior work has introduce
arXiv:2604.14593v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate increasingly sophisticated affective capabilities, the internal mechanisms by which they process complex
arXiv:2604.13757v1 Announce Type: new Abstract: The next generation of autonomous AI systems will be constrained not only by model capability, but by how intelligence is structured across heterogeneou
Ethan Mollick observes that an AI system (likely Claude or another large language model) still declines to write sestinas, suggesting that certain behavioral constraints or limitations persist despite