Knowledge catalogue
Got a doodle for your next project laying around? Turn it into working software using @GoogleAIStudio and Nano Banana. Watch us vibe code a weather-responsive outfit selector app from a single, hand-d
arXiv:2604.08879v1 Announce Type: new Abstract: Moving beyond the traditional binary classification paradigm of Multimodal Sarcasm Detection, Multimodal Sarcasm Target Identification (MSTI) presents a
great to see more open evals for an important problem We’re open sourcing the first document OCR benchmark for the agentic era, ParseBench. Document parsing is the foundation of every AI agent that wo
Grok Grok 4.20 Reasoning just took the #1 spot on the BridgeBench reasoning benchmark. 🔥 Beating GPT-5.4, Claude Opus 4.6, Google Gemini and others. Week after week, Grok keeps climbing across benchma
Have you tried the new Claude Code renderer? What has your experience been like? If you haven't, you can enable it with: CLAUDE_CODE_NO_FLICKER=1 claude Today we're excited to announce NO_FLICKER mode
arXiv:2604.08863v1 Announce Type: new Abstract: Recovering analytical solutions of physical fields from visual observations is a fundamental yet underexplored capability for AI-assisted scientific rea
arXiv:2604.05072v2 Announce Type: replace Abstract: Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, ex
arXiv:2604.08826v1 Announce Type: cross Abstract: Large foundation models have become central to modern machine learning, with performance scaling predictably with model size and data. However, traini
arXiv:2604.09408v1 Announce Type: new Abstract: Frontier coding agents solve complex tasks when given complete context but collapse when specifications are incomplete or ambiguous. The bottleneck is n
arXiv:2604.08884v1 Announce Type: cross Abstract: While multimodal large language models (MLLMs) have made significant strides in natural image understanding, their ability to perceive and reason over
arXiv:2604.08966v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have advanced Video Temporal Grounding (VTG), existing methods often couple output paradigms with differe
At Google Cloud, we often see customers asking themselves: 'How can we manage our generative AI costs effectively without sacrificing the performance and availability our applications demand?' This is
arXiv:2604.08883v1 Announce Type: cross Abstract: Inspired by the general Vision-and-Language Navigation (VLN) task, aerial VLN has attracted widespread attention, owing to its significant practical v
A Reddit user on r/ollama conducted a hands-on benchmark comparing Gemma4:e4b (Google's compact ~4.5B effective-parameter edge model) against Gemma3:27B, GPT-4o-mini, and Gemini 2.5 Flash, all run or
arXiv:2603.19275v2 Announce Type: replace-cross Abstract: Automatic summarization of radiology reports is an essential application to reduce the burden on physicians. Previous studies have widely used
arXiv:2604.03906v2 Announce Type: replace Abstract: Geoscientific systems tend to be characterized by pronounced temporal non-stationarity, arising from seasonal and climatic variability in hydrometeo
arXiv:2403.19253v3 Announce Type: replace Abstract: Effective agent coordination is crucial in cooperative Multi-Agent Reinforcement Learning (MARL). While agent cooperation can be represented by grap
This Reddit post from r/StableDiffusion shares ComfyUI inpainting workflows for several modern AI image models, including Z-Image, Qwen Image/Edit, and Flux-series models . Flux Fill is a dedicated in
arXiv:2603.28013v3 Announce Type: replace-cross Abstract: Multi-agent LLM systems are entering production -- processing documents, managing workflows, acting on behalf of users -- yet their resilience
arXiv:2604.08797v1 Announce Type: cross Abstract: Stories are key to transmitting values across cultures, but their interpretation varies across linguistic and cultural contexts. Thus, we introduce mu
arXiv:2506.22832v3 Announce Type: replace-cross Abstract: Training robust and generalizable reward models for human visual preferences is essential for aligning text-to-image and text-to-video generat
arXiv:2604.08970v1 Announce Type: cross Abstract: We study predictive multilingual evaluation: estimating how well a model will perform on a task in a target language when direct benchmark results are
A Reddit post in the r/ollama community seeking volunteers with diverse hardware setups to participate in a collaborative effort to benchmark the **behavioral reliability** of locally-run large langua
arXiv:2604.08956v1 Announce Type: new Abstract: Adapting vision-language models to remote sensing imagery presents a fundamental challenge: both the visual and linguistic distributions of satellite da
arXiv:2502.02345v2 Announce Type: replace Abstract: Subspace inference for neural networks assumes that a subspace of their parameter space suffices to produce a reliable uncertainty quantification. I
arXiv:2604.08741v1 Announce Type: new Abstract: Modern Automatic License Plate Recognition (ALPR) systems achieve outstanding performance in controlled, well-defined scenarios. However, large-scale re
arXiv:2604.09352v1 Announce Type: new Abstract: Monocular Depth Estimation (MDE) is crucial for autonomous lunar rover navigation using electro-optical cameras. However, deploying terrestrial MDE netw
arXiv:2501.15461v4 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have shown great success in various graph-based learning tasks. However, it often faces the issue of over-smoothing as
arXiv:2604.09443v1 Announce Type: cross Abstract: Large language model agents receive instructions from many sources-system messages, user prompts, tool outputs, and more-each carrying different level
arXiv:2604.09514v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled the large-scale generation of highly fluent and deceptive news-like content. While prior wo
arXiv:2604.08615v1 Announce Type: cross Abstract: Fine-grained visual understanding and high-level reasoning in real-world open-water environments remain under-explored due to the lack of dedicated be
arXiv:2604.09124v1 Announce Type: cross Abstract: Deploying DNNs on System-on-Chips (SoC) with multiple heterogeneous acceleration engines is challenging, and the majority of deployment frameworks can
arXiv:2604.08788v1 Announce Type: new Abstract: Patient-clinician communication is an asymmetric-information problem: patients often do not disclose fears, misconceptions, or practical barriers unless
arXiv:2604.08559v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-wor
arXiv:2603.13804v2 Announce Type: replace-cross Abstract: Rehearsal-based continual learning (CL) mitigates catastrophic forgetting by maintaining a subset of samples from previous tasks for replay. E
arXiv:2604.09088v1 Announce Type: new Abstract: Memory-efficient transfer learning (METL) approaches have recently achieved promising performance in adapting pre-trained models to downstream tasks. Th
Memory operations, including retrieval, prioritization, compaction awareness, should be native and baked into the harness. 𝐖𝐢𝐭𝐡𝐨𝐮𝐭 𝐭𝐡𝐞 𝐩𝐫𝐨𝐩𝐞𝐫 𝐢𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐡𝐚𝐫𝐧𝐞𝐬𝐬 𝐚𝐧𝐝 𝐦𝐞𝐦𝐨𝐫𝐲, 𝐦𝐞𝐦𝐨𝐫𝐲 𝐚𝐥𝐨𝐧𝐞 𝐢𝐬 𝐩𝐨
arXiv:2411.10636v2 Announce Type: replace-cross Abstract: In this study, we investigate extrinsic gender bias in Bangla pretrained language models, a largely underexplored area in low-resource languag
arXiv:2602.15313v2 Announce Type: replace Abstract: AI Memory, specifically how models organizes and retrieves historical messages, becomes increasingly valuable to Large Language Models (LLMs), yet e
arXiv:2604.08575v1 Announce Type: cross Abstract: Molecular generative models must jointly ensure validity, diversity, and property control, yet existing approaches typically trade off among these obj
arXiv:2604.07956v2 Announce Type: replace Abstract: Industry classification schemes are integral parts of public and corporate databases as they classify businesses based on economic activity. Due to
arXiv:2604.08582v1 Announce Type: cross Abstract: Multivariate Time Series Anomaly Detection (MTSAD) is critical for real-world monitoring scenarios such as industrial control and aerospace systems. M
arXiv:2604.09263v1 Announce Type: cross Abstract: We consider machine learning tasks with low-rank functional tree tensor networks (TTN) as the learning model. While in the case of least-squares regre
arXiv:2604.08923v1 Announce Type: new Abstract: Dimensional Aspect-Based Sentiment Analysis (DimABSA) extends traditional ABSA from categorical polarity labels to continuous valence-arousal (VA) regre
arXiv:2604.08562v1 Announce Type: cross Abstract: Ensuring that Text-to-Speech (TTS) systems deliver human-perceived quality at scale is a central challenge for modern speech technologies. Human subje
arXiv:2604.09258v1 Announce Type: new Abstract: Pretraining is the cornerstone of Large Language Models (LLMs), dominating the vast majority of computational budget and data to serve as the primary en
arXiv:2604.09021v1 Announce Type: cross Abstract: Auditory large language models (ALLMs) have demonstrated strong general capabilities in audio understanding and reasoning tasks. However, their reliab
arXiv:2604.09030v1 Announce Type: new Abstract: This paper presents NTIRE 2026, the 3rd Restore Any Image Model (RAIM) challenge on multi-exposure image fusion in dynamic scenes. We introduce a benchm
Ocr benchmark We’re open sourcing the first document OCR benchmark for the agentic era, ParseBench. Document parsing is the foundation of every AI agent that works with real-world files. ParseBench is
Ollama version 0.20.6 has been released, featuring improved tool calling support for Google's Gemma 4 model. The update focuses on enhancing the reliability and functionality of function/tool calling
This Reddit post from r/ollama discusses integrating Ollama-served Mistral with MemPalace — a free, locally-run AI memory system — via the Model Context Protocol (MCP). MemPalace runs entirely on a us
arXiv:2604.08641v1 Announce Type: cross Abstract: Interpretation is essential to deciphering the language of art: audiences communicate with artists by recovering meaning from visual artifacts. Howeve
arXiv:2509.25214v3 Announce Type: replace-cross Abstract: As increasingly large pre-trained models are released, deploying them on edge devices for privacy-preserving applications requires effective c
arXiv:2604.09303v1 Announce Type: cross Abstract: This paper presents an online intention prediction framework for estimating the goal state of autonomous systems in real time, even when intention is
This Reddit post discusses how open-source AI models have advanced to rival GPT-4-level performance and can be run locally for free using Ollama — a tool that lets users download and manage large lang
arXiv:2603.11178v3 Announce Type: replace Abstract: Standard LLM distillation treats all training problems equally -- wasting compute on problems the student has already mastered or cannot yet solve.
arXiv:2604.08707v1 Announce Type: new Abstract: Monadic second order logic (MSO2) plays an important role in parameterized complexity due to the Courcelle's theorem. This theorem states that the probl
ParseBench is here!📊 We’ve just released ParseBench, an open benchmark + dataset for evaluating document parsing at scale. It includes: • 2,000+ human-reviewed enterprise documents • 167,000 evaluatio
arXiv:2604.09415v1 Announce Type: cross Abstract: We present PhysInOne, a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike exi
arXiv:2604.08987v1 Announce Type: new Abstract: As Large Language Models (LLMs) advance toward embodied AI agents operating in physical environments, a fundamental question emerges: can models trained