Knowledge catalogue
Editor's note: Generative AI startups are moving rapidly beyond static clip generation to build interactive, real-time worlds. In this technical deep dive, we explore how AI startup Visko collaborated
arXiv:2610.14960v1 Announce Type: cross Abstract: Can an autonomous AI agent reverse engineer a binary as well as a skilled human analyst? Do they adopt the same strategy, and can agents scale to real
arXiv:2610.19347v1 Announce Type: cross Abstract: Novelty detection is crucial in various technological and scientific domains. Its importance spans from ensuring the reliability of sensor networks to
arXiv:2610.14699v1 Announce Type: new Abstract: The design of high-affinity, target-specific protein binders is central to the development of modern therapeutics. However, existing protein-generation
arXiv:2610.17391v1 Announce Type: new Abstract: Amazing breakthroughs in reinforcement learning have taken place. Computers teach themselves to play Chess and Go and beat world champions. There is tal
arXiv:2610.14705v1 Announce Type: cross Abstract: Large language models have advanced medical reasoning, but clinically grounded reasoning in traditional Chinese medicine (TCM) remains challenging bec
arXiv:2308.12241v2 Announce Type: replace-cross Abstract: Recently, the fast development of Large Language Models (LLMs) such as ChatGPT has significantly advanced NLP tasks by enhancing the capabilit
arXiv:2610.14777v1 Announce Type: new Abstract: LLM-powered data analytics aims to translate natural language instructions into executable analytical programs over underlying data. However, existing a
arXiv:2610.17613v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems (MAS) can solve complex problems beyond the reach of a single agent by decomposing tasks and coordi
arXiv:2509.09658v3 Announce Type: replace Abstract: Hallucinations in multimodal large language models (MLLMs), where a model generates content inconsistent with the input image, pose significant risk
arXiv:2610.14507v1 Announce Type: new Abstract: Generative modeling offers a promising solution to the scarcity of labeled clinical electroencephalography (EEG) data under strict privacy constraints.
arXiv:2610.19104v1 Announce Type: cross Abstract: Learning an individualized treatment rule (ITR) with many treatments requires estimating treatment-specific effects from limited observations per arm.
NVIDIA Nemotron 3.5 Bolt 74B-A9B 24GB is now on Ollama This model vision-language model (VLM) is designed to run everyday agentic tasks locally, using a native 2-bit quantization to fit in 24GB of mem
NVIDIA has made its Nemotron 3.5 Super VL model available on the Perplexity AI platform for users on Pro and Max subscription plans, as well as through a new Agent API endpoint. The release was announ
arXiv:2610.19883v1 Announce Type: new Abstract: The growing interest in behavior foundation models, combined with recent advancements in generative modeling, has led to an appealing recipe for reinfor
arXiv:2610.19573v1 Announce Type: cross Abstract: Differential Privacy (DP) provides a rigorous framework for quantifying privacy guarantees. While most methods achieve DP by injecting calibrated rand
arXiv:2610.19892v1 Announce Type: cross Abstract: Vision-language models suffer significant accuracy drops under common corruptions. While test-time adaptation (TTA) successfully mitigates these shift
arXiv:2610.18784v2 Announce Type: new Abstract: Long-horizon agents accumulate progress in persistent task state, yet repeatedly process interaction histories describing how that progress was achieved
arXiv:2610.19314v1 Announce Type: new Abstract: Large language model (LLM) evaluators are increasingly used to assess personalized assistants, yet whether they can reliably judge personalization has r
arXiv:2610.19131v1 Announce Type: cross Abstract: Maintenance work orders are the largest written record of how industrial equipment fails, yet in most plants they are close to unusable for analysis.
arXiv:2409.00696v4 Announce Type: replace-cross Abstract: Rating-based human evaluation has become an essential tool to accurately evaluate the impressive performance of large language models (LLMs).
arXiv:2610.17837v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly used for vulnerability analysis, yet existing benchmarks provide limited coverage of exploitation t
arXiv:2610.04561v2 Announce Type: replace Abstract: Differentiable programming connects scientific computation with gradient-based inference, learning and design. Extending these capabilities across a
arXiv:2610.14721v1 Announce Type: new Abstract: Test-Time Discovery (TTD) aims to recognize known classes and detect novel ones from a continuous unlabeled test stream after deployment. Existing TTD m
arXiv:2610.19495v1 Announce Type: cross Abstract: Retrieving useful context for a robot requires matching its task, execution stage, and the continuation that should follow. We introduce Robota-Embed,
arXiv:2610.19708v1 Announce Type: new Abstract: Recent video world models have increasingly adopted 3D memory mechanisms to integrate historical observations into a lightweight and persistent scene re
arXiv:2610.18813v1 Announce Type: new Abstract: Harness self-evolution revises an agent's software scaffolding, including prompts, memory, workflows, and executable components, while keeping model wei
arXiv:2508.16939v2 Announce Type: replace Abstract: Diffusion models achieve state-of-the-art generative performance but remain computationally expensive at inference, often requiring many discretizat
arXiv:2606.13497v2 Announce Type: replace-cross Abstract: This work introduces Spatial Annotations from Robot Demonstrations with Reliability Calibration (SPARC), a risk-aware framework that automatic
Artificial intelligence governance startup nFOX Lab today launched a platform for managing owned large language models and announced plans to open-source Blockhouse, a security sandbox designed to res
arXiv:2610.19557v1 Announce Type: new Abstract: Contrastive learning for time series depends on deciding which pairs of inputs should be treated as similar and dissimilar. Because few augmentations re
arXiv:2610.19860v1 Announce Type: cross Abstract: In sectors such as energy, aquaculture and chemical processing, the effectiveness of both mechanistic and data-driven models is frequently limited by
arXiv:2610.18216v1 Announce Type: cross Abstract: LLM agents can adapt to task feedback by revising the textual context that guides their behavior, without changing their model parameters. However, tu
arXiv:2610.19074v1 Announce Type: new Abstract: Reliable uncertainty quantification remains an important challenge in AI. Hierarchical Bayesian methods provide a principled framework for this by repre
arXiv:2610.15231v1 Announce Type: new Abstract: Generative artificial intelligence (GenAI) models, particularly large language models (LLMs), are increasingly used in educational settings for tasks su
arXiv:2603.13509v2 Announce Type: replace-cross Abstract: Differential-algebraic equations (DAEs) arise in power networks, chemical processes, and multibody systems, where algebraic constraints encode
arXiv:2610.15948v1 Announce Type: new Abstract: Proactive Smart Assistants (PSAs) increasingly use general knowledge, learned patterns from group-level data, patterns from individual user's data, and
arXiv:2610.19517v1 Announce Type: cross Abstract: Vision-language-action (VLA) models connect visual perception and language understanding with robot control, providing a foundation for instruction-co
arXiv:2610.19411v1 Announce Type: new Abstract: A major challenge in wearable device activity recognition is the heterogeneity across datasets in sensor placement, channel count, sampling rate and sub
Small teams, short runway, and constant pressure to ship faster — it’s the reality we see every day among the founders we work with at Google for Startups. When you are building a company from the gro
arXiv:2610.17090v1 Announce Type: cross Abstract: On 6 October 2026 OpenAI published an initial 722 AI-written mathematical manuscripts, organized into 372 problem families, in the public repository g
arXiv:2607.11197v2 Announce Type: replace Abstract: When LLMs exhibit uneven performance across planning tasks, these gaps are often attributed to task difficulty. We argue that this explanation is in
arXiv:2610.15459v1 Announce Type: cross Abstract: LLM-based multi-agent systems (LLM-MAS) use specialized agents that exchange messages to accomplish complex tasks. Their reliance on networked protoco
arXiv:2610.19035v1 Announce Type: cross Abstract: Pluralistic alignment needs to accommodate diverse preferences under limited human feedback. Using AI simulators to label preference comparisons reduc
arXiv:2610.17159v1 Announce Type: cross Abstract: We develop a novel generalization of McDiarmid's concentration inequality and use it to obtain a uniform law of large numbers result and error bounds
arXiv:2508.18564v2 Announce Type: replace Abstract: A recent paper, ``A Graphon-Signal Analysis of Graph Neural Networks'', by Levie, analyzed message passing graph neural networks (MPNNs) by embeddin
arXiv:2610.16996v1 Announce Type: new Abstract: The penetration-resistant design of concrete structures requires the spatiotemporal evolution of the stress field within the target, whereas in design o
arXiv:2602.19503v2 Announce Type: replace Abstract: As drone-based object detection technology continues to evolve, the demand is shifting from merely detecting objects to enabling users to accurately
Google’s Gemini 4 Argon is now generally available (GA), offering coding, knowledge‑work, enterprise‑workflow, and cyber‑defense features via the paid Gemini API, Google AI Pro/Ultra in the Gemini app
arXiv:2610.18169v1 Announce Type: cross Abstract: A scenario-based development approach has become state of the art for automated driving systems. Once a set of scenario classes covering the operation
arXiv:2503.11147v2 Announce Type: replace Abstract: Sharpness-Aware Minimization (SAM) is an optimization method that improves the generalization performance of machine learning models. Despite its ef
arXiv:2607.09316v2 Announce Type: replace-cross Abstract: Thematic indexing -- the practice of assigning structured conceptual labels to sections of text -- is essential to scholarly access in large-s
arXiv:1808.02932v5 Announce Type: replace-cross Abstract: In stochastic multi-armed bandits, rewards are generated by an unknown distribution; the world's reward uncertainty induces the exploration-ex
arXiv:2506.00482v2 Announce Type: replace Abstract: LLM benchmarks are often treated as coherent measurement units, yet they are heterogeneous collections of instances spanning diverse domains, skills
arXiv:2610.17963v1 Announce Type: new Abstract: Brick-and-mortar retailers face many different challenges that involve understanding thoroughly its products catalog and customer preferences. In partic
arXiv:2610.18375v1 Announce Type: new Abstract: A learned representation is useful beyond its source task only if later tasks can make use of what the encoder has already learned. Source-task performa
arXiv:2409.17397v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly being integrated into various medical fields, including mental health support systems. However,
arXiv:2610.18209v1 Announce Type: new Abstract: Cross-domain few-shot action recognition (CD-FSAR) aims to recognise unseen action classes in a target domain from a handful of labelled videos. Despite
Welcome to the first Cloud CISO Perspectives for October 2026. Today, Stephanie Kiel explains the latest on our approach to post-quantum cryptography, and shares a new tool to help CISOs and executive
arXiv:2610.17171v1 Announce Type: cross Abstract: Designing synthesizable materials with targeted properties remains one of the central objectives in materials sciences. Ionic liquids (ILs) are well s