Knowledge catalogue
arXiv:2605.22823v1 Announce Type: new Abstract: Video Large Language Models (Video-LLMs) have made rapid progress on temporal video understanding, yet many fail at a basic perceptual primitive: signed
Today, AI services rely heavily on API keys. To run AI agents, users provide API keys that signify paid tokens, subscriptions, or paid accounts. While API keys are easy to use, it is just as easy to u
As of yesterday, we made everyone within @llama_index research/engineering/product a Member of Technical Staff. Yes all the frontier labs have done this for years. But we didn’t only make these change
arXiv:2605.20293v1 Announce Type: new Abstract: Predictive coding (PC) offers a local and biologically grounded alternative to backpropagation in the training of artificial neural networks, yet to dat
arXiv:2512.07420v2 Announce Type: cross Abstract: The identification and classification of collimated particle sprays, or jets, are essential for interpreting data from high-energy collider experiment
arXiv:2605.20242v1 Announce Type: new Abstract: Efficient discovery of precursor additives is essential for improving the performance of perovskite solar cells, yet the large chemical space makes conv
arXiv:2511.21223v2 Announce Type: replace-cross Abstract: Variational inference (VI) is a cornerstone of modern Bayesian learning, enabling approximate inference in complex models. However, its formul
arXiv:2605.20194v1 Announce Type: new Abstract: Large language models (LLMs) have been increasingly used to analyze text. However, they are often plagued with contextual reasoning limitations when ana
arXiv:2605.20823v1 Announce Type: new Abstract: Open-vocabulary 3D scene graph generation seeks to describe object instances and their relations with flexible natural-language predicates. The central
arXiv:2605.20189v1 Announce Type: cross Abstract: Despite the remarkable success of large language models (LLMs), they still face bottlenecks while deploying in dynamic, real-world settings with prima
Many of the world’s fastest-growing AI startups are choosing to build their future — and the world’s — on Google Cloud because of our complete and open AI stack. We embed AI into every layer of our ar
arXiv:2605.21295v1 Announce Type: new Abstract: Longitudinal passive sensing enables continuous health prediction, yet models often fail under cross-dataset distribution shifts. Traditional ML overfit
arXiv:2504.13109v2 Announce Type: replace Abstract: Flow matching models have emerged as a strong alternative to diffusion models, but existing inversion and editing methods designed for diffusion are
arXiv:2605.20173v1 Announce Type: new Abstract: Production LLM agents combine stochastic model outputs with deterministic software systems, yet the boundary between the two is rarely treated as a firs
arXiv:2605.19518v1 Announce Type: new Abstract: Generating Knowledge Graphs (KGs) remains one of the most time-consuming and labor-intensive tasks for knowledge engineers, as they need to identify sem
arXiv:2605.19892v1 Announce Type: cross Abstract: Dramatic cost reductions driven by private sector innovations have led to a rapid increase in the number of satellites in orbit and a corresponding su
arXiv:2605.19781v1 Announce Type: new Abstract: Modern optimizers, like Muon, impose matrix-wise geometry constraints on their updates. These matrix-wise constraints can be unified under Linear Minimi
Google published exploit code for an unfixed vulnerability in its Chromium browser codebase that threatens millions of people using Chrome, Microsoft Edge, and other Chromium-based browsers. The proof
arXiv:2605.19192v1 Announce Type: new Abstract: Multimodal agents use screenshots, documents, and webpages to choose tool calls. When a false visual claim triggers a click, email, extraction, or trans
Hybrid AI governance has become essential for regulated industries such as banking, where the pressure to move fast with agentic AI collides with strict requirements for data sovereignty, compliance a
arXiv:2605.19386v1 Announce Type: new Abstract: Reconstructing simulation-ready deformable objects is important for vision, graphics, and robotics. Existing physics-driven methods can recover physical
arXiv:2511.14159v2 Announce Type: replace Abstract: Evaluating the robustness of Large Vision-Language Models (LVLMs) is essential for their continued development and responsible deployment in real-wo
arXiv:2605.19107v1 Announce Type: new Abstract: Green hydrogen plays an essential role in decarbonization, with capacity projected to scale to 560 GW by 2030 (vs. 1.39 GW in 2023) in net-zero settings
arXiv:2605.18801v1 Announce Type: new Abstract: Data is fundamental to large language models (LLMs). However, understanding of what makes certain data useful for different stages of an LLM workflow, i
arXiv:2503.22823v3 Announce Type: replace-cross Abstract: In classical information theory, the Doeblin coefficient of a classical channel provides an efficiently computable upper bound on the total-va
arXiv:2603.09473v2 Announce Type: replace Abstract: Equipping robotic systems with the capacity to generate extit{ex novo} hardware during operation extends control of physical adaptability. Unlike mo
arXiv:2505.17726v3 Announce Type: replace-cross Abstract: Recently, multimodal large language models (MLLMs) have emerged as a key approach in achieving artificial general intelligence. In particular,
arXiv:2409.08248v2 Announce Type: replace Abstract: In this paper, we introduce TextBoost, an efficient one-shot personalization approach for text-to-image diffusion models. Traditional personalizatio
arXiv:2605.17954v1 Announce Type: cross Abstract: Modern multimodal large language models (MLLMs) typically keep the language model fixed and train a visual projector that maps the pixels into a seque
arXiv:2605.17673v1 Announce Type: new Abstract: The objective of this work is to propose a novel methodology for the finger knuckle print recognition, which is essentially a digital photo of the finge
arXiv:2605.17903v1 Announce Type: new Abstract: We automatically generate feedback causal fuzzy cognitive maps (FCMs) from text by teaching large-language-model agents to break the text into overlappi
arXiv:2605.18133v1 Announce Type: cross Abstract: LLM-based chatbot agents increasingly process user requests by combining natural-language reasoning with external tools such as web browsing. These ca
arXiv:2605.16295v1 Announce Type: cross Abstract: We present ANVIL, a multimodal generative system that automates the production of analogy-based instructional animations for computer science topics.
arXiv:2601.16527v2 Announce Type: replace-cross Abstract: Multimodal LLMs are powerful but prone to object hallucinations, which describe non-existent entities and harm reliability. While recent unlea
arXiv:2511.19162v2 Announce Type: replace-cross Abstract: Bioart's hybrid nature spanning art, science, technology, ethics, and politics defies traditional single-axis categorization. I present BioArt
arXiv:2605.17255v1 Announce Type: new Abstract: Formal theorem-proving benchmarks enable mechanically verifiable evaluation of mathematical reasoning in large language models. However, existing benchm
arXiv:2605.17118v1 Announce Type: new Abstract: Differentiable optimization layers are traditionally integrated in predict-then-optimize frameworks where a neural model estimates parameters that subse
arXiv:2605.16676v1 Announce Type: new Abstract: Metacognition-the ability to monitor one's own knowledge state, spot gaps, and autonomously fill them--remains largely absent from modern AI. Here, we p
At Google Cloud Next ‘26, we unveiled the blueprint for the Agentic Enterprise, sharing our eighth-generation TPUs, Gemini Enterprise Agent Platform, a fully reimagined Agentic Data Cloud, Workspace I
arXiv:2605.18144v1 Announce Type: new Abstract: Nanomedicine research spans delivery chemistry, immunology, imaging, biomaterials, and disease-specific translational science, yet its conceptual design
arXiv:2605.04375v2 Announce Type: replace-cross Abstract: To unleash the full potential of AI for Science, we must untether the agents from a purely digital environment. The agent's ability to control
arXiv:2601.02071v3 Announce Type: replace Abstract: Pharmaceutical three-dimensional (3D) printing is an advanced fabrication technology with the potential to enable truly personalised dosage forms. R
arXiv:2604.01404v2 Announce Type: replace-cross Abstract: How do language models retrieve entity-specific facts from their parameters? We investigate this question by searching for sparse, entity-sele
arXiv:2605.17456v1 Announce Type: cross Abstract: Multiple instance learning (MIL) is the standard approach for whole-slide image (WSI) classification and survival prediction, where attention-based mo
For a quarter century, the Google search box has been one of the most recognizable interfaces in computing: a thin white rectangle, a blinking cursor, a few typed words, and a list of blue links. On T
arXiv:2605.18601v1 Announce Type: new Abstract: Modern interactive video world models have achieved impressive visual fidelity, yet lack fine-grained multi-entity control and cross-entity, cross-world
arXiv:2605.17990v1 Announce Type: new Abstract: We present a real-time gaze tracking system that directly acquires task-relevant latent features using a fully passive optical encoder. Instead of formi
arXiv:2605.17120v1 Announce Type: new Abstract: arly identification of motor impairment in infancy relies on expert visual assessment of spontaneous movement, motivating the development of automated,
arXiv:2402.15058v3 Announce Type: replace-cross Abstract: We combine standard persistent homology with image persistent homology to define a novel way of characterizing shapes and interactions between
arXiv:2605.18549v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) introduce new opportunities for safety monitoring through their Chain of Thought (CoT) reasoning. However, CoT is not alwa
arXiv:2605.17340v1 Announce Type: new Abstract: Time series foundation models rely on large-scale pretraining over diverse datasets across domains, yet their heterogeneity in temporal patterns could h
arXiv:2602.20706v2 Announce Type: replace Abstract: This paper introduces online algorithms with unreliable guidance (OAG), a model for ML-augmented online decision-making that cleanly separates the p
arXiv:2601.09495v3 Announce Type: replace Abstract: With the emergence of massively parallel processing units, parallelization has become a desirable property for new sequence models. The ability to p
arXiv:2509.19590v2 Announce Type: replace Abstract: Evaluations of generative models are now ubiquitous, and their outcomes critically shape public and scientific expectations of AI's capabilities. Ye
arXiv:2605.18732v1 Announce Type: cross Abstract: While scaling laws govern aggregate large language model performance, no scaling law has linked factual recall to both model size and training-data co
arXiv:2605.18537v1 Announce Type: cross Abstract: This paper introduces the Manifold Probe, a supervised method for discovering representation manifolds in superposition. The method generalizes linear
arXiv:2605.18570v1 Announce Type: new Abstract: Cross-domain knowledge alignment is essential for integrating heterogeneous medical systems, yet existing approaches typically treat entity alignment as
arXiv:2605.17169v1 Announce Type: new Abstract: Agentic AI is rapidly proliferating across diverse real-world domains such as software engineering, yet public trust has not kept pace. The central reas
arXiv:2602.08169v2 Announce Type: replace-cross Abstract: Inference-time steering offers a promising way to control language models (LMs) without retraining. However, standard approaches typically rel
arXiv:2603.14462v2 Announce Type: replace-cross Abstract: Honey bee colony losses threaten global pollination services, yet current monitoring systems treat each hive as an isolated unit, ignoring the