ZeroHour
DashboardNewsCVEsExploitsIncidentsAIBriefAnalyticsEntitiesWatchlistIOCsAsk the feedSourcesFeeds & APIKiosk mode

Search: “geo”

40 stories

Searchkeywordsmart
DomainAllCyberAIWindow24h3d7d30dAllIn the wildImportant onlyShow duplicates
CategoryAllMalware 100Vulnerability 66Ransomware 56Policy & legal 52Data breach 49Industry 48Phishing & fraud 41Threat actor 39Exploit / PoC 29AI tools & infra 8Research 5AI industry 5Advisory 4AI research 4
SeverityAllcritical 169high 149medium 91low 82info 19

Smart search ranks by meaning as well as keywords (one row per story, last 45 days).

Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

Paper proposes Generative Marketing Mix Modeling to causally estimate Generative Engine Optimization and Marketing effects on business outcomes.

The authors develop GMMM, a causal inference framework for measuring how often users see and notice a firm's name in generated answers, which standard marketing data ignore. For GEO it combines repeated generated answers with question counts, shares of generative-system usage and notice probabilities; for GEM it uses sponsored placement records with notice probabilities. The framework compares expected business responses under alternative treatment sequences, establishes identification conditions, and is evaluated on simulated product-recommendation answers in English and Japanese.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research

GPT-6 built this earth exploration site in 5 prompts

Hacker News post showcases an interactive earth exploration website that GPT-6 generated from only five prompts.

The item is a Hacker News submission (23 points, 32 comments) linking to earth.ethanplus.ai, an earth exploration website the author says was built by GPT-6 in five prompts. It functions as a community demo of the model's web development and generative capabilities rather than a research or security disclosure.

Hacker News · security · 5d agoAI industryHN 23↑ · 32 comments

BigBear Microsoft 365 phishing service bypassed MFA at 258 organizations

CloudSEK found the BigBear 2.0 phishing-as-a-service platform bypassed MFA at 258 organizations and captured over 5,000 Microsoft 365 credentials.

CloudSEK researchers gained administrator access to the BigBear 2.0 phishing-as-a-service control panel and found it had exfiltrated 5,137 credential records, including 474 completed MFA-bypassed authentications, 1,032 plaintext passwords, and 4,148 session cookies across 3,331 victim IPs in 40+ countries. The Evilginx2-based AitM proxy intercepts credentials and authenticated session cookies, and custom JavaScript interferes with FIDO2/WebAuthn to force weaker authentication. The panel is leased to at least five affiliate operators via Telegram exfiltration bots, and geo-matched residential proxies cover 69 countries to evade detection.

BleepingComputer · 9d agoPhishing & fraud in the wild1

Introducing OlmoEarth embeddings: Custom embedding exports from OlmoEarth Studio for downstream analysis

AllenAI's OlmoEarth Studio adds custom embedding exports to support downstream geospatial analysis workflows.

A Hugging Face blog post from AllenAI introduces OlmoEarth embeddings, a feature allowing custom embedding exports from OlmoEarth Studio for downstream analysis tasks. Only the title was available, so no benchmark or performance details are provided. OlmoEarth is Ai2's open geospatial AI model family.

Hugging Face Blog · Aug 12, 2026AI tools & infra

Amasty patches dozens of Magento extensions, 2 critical

Amasty patched dozens of Magento/Adobe Commerce extensions, including two critical flaws allowing unauthenticated web shell upload and remote code execution.

Extension vendor Amasty released fixes for a large batch of Magento and Adobe Commerce modules, with critical unauthenticated file upload flaws in Advanced Product Reviews and Gift Card that allow attackers to plant web shells and take full control of stores. Dozens of additional high-, medium- and low-severity extensions were also patched. The vendor says the release affects almost every Magento and Adobe Commerce store. A related Order Attributes flaw was previously exploited heavily, with Sansec Shield blocking over 12,000 attempts against 25% of Magento stores in three days.

Sansec (Magento / e-commerce security) · 7d agoVulnerability

GeoJSON Map Viewer

Simon Willison built a GeoJSON map viewer with PNG export using GPT-5.6-Sol, Claude Code for web, and Fable 5.1.

Simon Willison describes building a GeoJSON map viewer that displays boundary files and exports maps as PNGs. GPT-5.6-Sol proactively offered to create the tool, and iterations used Claude Code for web and Fable 5.1. He also notes ChatGPT Work will assemble boundary polygons from government data sources when asked.

Simon Willison · 15d agoAI tools & infra

IT Help Desk Impersonation Lets Hackers Bypass MFA

Arctic Wolf tracks PREY-0058 posing as IT help desk to steal Microsoft 365 sessions via AiTM panels, then extorting executives after SaaS data theft.

Arctic Wolf documented a threat cluster tracked as PREY-0058 that impersonates internal IT help desk staff by phone, luring Directors, VPs, and executives to authentication-themed URLs formatted as victim-organization lure domains. Adversary-in-the-middle panels intercept credentials and MFA approvals, and stolen sessions are replayed through residential proxies such as NodeMaven from IPs matching the victim's geo-location and ASN, defeating impossible-travel alerts. Attackers perform discovery against SharePoint and Entra ID, then harvest data from OneDrive, Exchange, and Box before issuing extortion demands. Defenders are advised to require managed devices, use phishing-resistant MFA like FIDO2, enable Continuous Access Evaluation, and monitor sign-ins, SharePoint SearchQueryPerformed, and MailItemsAccessed events.

Security Affairs · 8d agoPhishing & fraud in the wild1

Mercator ↔ Equal Earth

Simon Willison used GPT-6 Astra (medium) in ChatGPT Work to build an animated D3 transition between Mercator and Equal Earth map projections.

Willison built an animated transition between the Mercator and Equal Earth map projections using D3. The tool was generated by GPT-6 Astra (medium) in ChatGPT Work. Equal Earth is a projection recently voted on at the UN. The post is a vibe-coding demonstration rather than a security or major model event.

Simon Willison · 9d agoAI tools & infra1

To See a World in a Living Context: Unified Indoor-Outdoor Urban World Generation

Researchers introduce HoloWorld, a unified text-driven framework generating coherent indoor-outdoor 3D urban worlds, improving average AQS over SOTA by 7.68%.

HoloWorld is a text-driven 3D generation framework that unifies indoor and outdoor urban world generation using a continuously updated cross-scale world context. It autoregressively generates urban exteriors with consistent spatial organization, grounded in 3D building instances and footprints, then produces building-specific interiors with geometry-constrained layouts that inherit exterior appearance. The authors claim it is the first framework to unify indoor and outdoor generation within one coherent 3D urban world, reporting a 7.68% average AQS improvement over prior SOTA and the highest average RDR score.

Hugging Face daily papers · 19d agoAI research

BigBear 2 PhaaS Campaign Steals 5000+ Microsoft Credentials

CloudSEK researchers found the BigBear 2.0 PhaaS kit, built on Evilginx2, has stolen over 5,100 Microsoft 365 credentials across 461 organizations in 40+ countries.

CloudSEK gained admin access to the BigBear 2.0 phishing-as-a-service panel, an Evilginx2-based adversary-in-the-middle platform operated by someone using the alias 'General Boss'. The team observed 3,331 unique victim IPs across more than 40 countries, 42 VPS nodes mostly on Vultr, and 5,137 credential records across 461 organizations, including 4,148 session cookies, 1,032 plaintext passwords, and 474 completed MFA-bypassed authentications. IT and managed service providers were the most targeted sector, raising supply-chain risk since their compromise can expose client infrastructure and privileged Azure AD access.

Infosecurity Magazine · 8d agoPhishing & fraud in the wild

Google’s AI weather model now uses more raw satellite data

Google launched WeatherNext 3, an AI weather model using raw satellite data that beats ECMWF and now powers Search, Gemini, and Maps.

Google released WeatherNext 3, an AI weather forecasting model that incorporates physical surface information (land/ocean type and elevation) to improve surface temperature and dewpoint calculations, improving point location temperature accuracy by up to 30 percent. Its white paper reports roughly 5 percent better upper-atmosphere accuracy than WeatherNext 2, equating to about six additional hours of forecast lead time, outperforming the ECMWF AI model on these metrics. The model now supplies forecast information across Google Search, Gemini, and Maps, though the paper notes unexplained short-lead degraded results and grid-shaped artifacts in some predictions.

Ars Technica · AI · 8d agoModel release

Creepy crawlies

git.kernel.org spends more CPU rendering commit pages for abusive AI-era scrapers than on all legitimate access including git clones.

Konstantin Ryabitsev reports that abusive crawler 'background radiation' at git.kernel.org consumes more CPU cycles rendering commit HTML than all legitimate access, with 14 cores across five geo-distributed nodes dedicated to scraper traffic. Simon Willison highlights the implications for crawlable web services like Datasette.

Simon Willison · 9d agoAI industry1

Introducing WeatherNext 3, our most advanced and accurate global weather AI model

Google DeepMind launches WeatherNext 3, an AI weather model delivering hourly 5-km forecasts from live satellite data, now integrated across Google products.

WeatherNext 3 ingests live geostationary satellite mosaics and station observations through a Functional Generative Network (FGN) mesh transformer, producing hourly forecasts at 5-km surface resolution versus WeatherNext 2's 25-km, 6-hour grid. Independent live evaluations by Brightband rate it the most accurate global weather model to date. It adds renewable-energy variables such as 100-meter turbine-height wind speeds and solar radiation, and is integrated across Search, Gemini, Maps, Google Maps Platform, and Cloud.

Google DeepMind · 13d agoModel release

Mapping out your unknown: A threat hunter’s guide to GitHub

Datadog Security Labs publishes a threat-hunting guide with audit-log queries to detect GitHub token theft, device code phishing, and source code exfiltration.

Datadog's threat-hunting guide covers GitHub audit log queries for detecting compromised accounts, stolen personal access tokens, and malicious OAuth app authorizations. Attackers typically obtain credentials through phishing, credential stuffing, leaked secrets, or device code phishing, then map private repositories, exfiltrate source code, and pivot into connected cloud and CI/CD environments. The guide maps detections to MITRE techniques like T1078 and T1528 and documents GitHub logging quirks affecting attribution, token metadata, and visibility fields.

Datadog Security Labs · 1d agoResearch in the wild1

[20260806] - Core - XSS through schema.org outputs

Joomla fixed CVE-2026-73336, an XSS in schema.org markup outputs caused by improper escaping, affecting CMS 5.1.0-5.4.7 and 6.0.0-6.1.2.

Joomla security advisory 20260806 describes CVE-2026-73336, a cross-site scripting issue in schema.org markup outputs. Improper escaping flags create an XSS vector in schema.org output; the vendor rates impact and severity as moderate with low probability. Affected versions are 5.1.0-5.4.7 and 6.0.0-6.1.2; fixes ship in 5.4.8 and 6.1.3. The issue was reported by Amin Isayev and Geo (GitHub.com/geo-chen) on 2026-07-21.

Joomla Security Centre · Aug 17, 2026AdvisoryCVE-2026-73336

Real-World Knowledge-Guided Change Data Synthesis for Remote Sensing

Researchers introduce KnowChange, a framework that uses pretrained vision-language models to synthesize realistic change-detection training data for remote sensing.

KnowChange is a knowledge-guided change data synthesis framework that leverages pretrained vision-language models to reason about plausible change locations and class transitions from pre-change scenes and desired change types. It addresses the limited class-transition coverage and inflexibility of handcrafted rule-based synthesis methods, enabling diverse change types in a unified pipeline. Experiments show KnowChange-generated data outperforms existing synthetic datasets in both synthetic-to-real transfer and synthetic data augmentation, despite compact generation scale.

Hugging Face daily papers · 23d agoAI research

Attackers Expose Ongoing AI Tool Use Targeting Organizations in Latin America

Unit 42 documents two AI-assisted intrusion campaigns against Latin American government, utility, and financial organizations using LLM-orchestrated tooling.

Palo Alto Networks Unit 42 tracks two ongoing intrusion clusters, CL-CRI-1131 (Mexican transportation, federal ministries, municipal water utilities) and CL-CRI-1163 (Brazilian financial sector), both using living-off-the-land techniques, SOCKS5 relays, and custom RATs. The attackers appear to orchestrate operations via commercial LLMs like Claude and GPT-4.1, evidenced by iterative batch scripts and AI-generated tunneling tool naming. The Mexican campaign (also reported as Operation Escaneo by CloudSEK) exfiltrated sensitive data via dynamic-DNS infrastructure with rotated multi-SAN TLS certificates between February and June 2026. This signals broader adoption of AI-enhanced operations by diverse threat groups in the region.

Palo Alto Unit 42 · 13d agoThreat actor in the wild1

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

Grouped Value Attention stores grouped values and reconstructs content keys via a learned linear map, cutting KV-cache size about 45-47% versus GQA.

GVA stores only grouped values and reconstructs content keys with a learned linear map absorbed into the query at decode time, while a small shared decoupled RoPE channel preserves positional information via a separately cached positional key. At 350M parameters trained on 30B FineWeb-Edu tokens, the 16-dimensional positional variant scores 44.18 average accuracy across five tasks versus 44.36 for GQA and 43.88 for MLA. Custom decoding kernels are in development with an open-source release planned.

Hugging Face daily papers · 9d agoAI research

SpatialBlock: Enhancing Spatial Intelligence in LVLMs via Synthetic Block-Stacking Problem

Researchers release SpatialBlock-15k, a synthetic block-stacking dataset that improves 3D spatial reasoning in large vision-language models without dense geometric annotations.

The paper addresses limited spatial intelligence in LVLMs by training on structured block-manipulation tasks instead of costly real-scene annotated datasets. SpatialBlock-15k contains 15,000 synthetic problems covering 3D-to-2D projection, viewpoint transformation, and structural combination, with color modulation as visual cues. LVLMs trained on it via direct answering or reasoning-based prediction outperform baselines and generalize to real-world spatial tasks. Code and data are released on GitHub.

Hugging Face daily papers · 10d agoAI research

RelateAnything: Real-Time Open-Vocabulary Relation Prediction From Any Inputs

RelateAnything is a 53M-parameter open-vocabulary relation prediction model running at 20 ms/frame, with 2.3-3.5x higher mean recall than comparable open-vocabulary methods.

RelateAnything predicts scored relations between image regions using any predicate vocabulary supplied at inference as text embeddings, with object labels never required as input, so region sources can change without retraining. Training covers 19,103 predicates using positive-unlabeled supervision; the authors release RA-4M (474k images, 4.3M geometrically verified relations over 10,102 free-text predicates) and the OV-SGG-Bench evaluation suite. The 53M-parameter model runs at 20 ms/frame and achieves 2.3-3.5x the mean recall of the strongest comparable open-vocabulary method across cross-dataset and zero-shot benchmarks. Model, corpus, and benchmark are public.

Hugging Face daily papers · 6d agoAI research1

[20260805] - Core - Improper ACL checks for category webservice endpoints

Joomla fixes CVE-2026-72532, an improper ACL check letting unauthorized users create categories via webservice endpoints, in CMS 5.4.8/6.1.3.

Joomla disclosed an incorrect access control flaw (CVE-2026-72532) in category webservice endpoints, allowing unauthorized users to create categories for inaccessible components. It affects Joomla CMS 4.0.0-5.4.7 and 6.0.0-6.1.2 and is rated moderate impact and severity with low probability. The fix ships in Joomla 5.4.8 and 6.1.3 on 2026-08-18; it was reported by Amin Isayev and Geo.

Joomla Security Centre · Aug 17, 2026AdvisoryCVE-2026-72532

Building AI to accelerate science and improve lives

Google highlights AI-for-science advances: AlphaGenome Atlas mapping 9 billion genetic variants, WeatherNext 3 weather model, and global health AI tools.

Google detailed AI advances across science and health, including AlphaGenome Atlas, which mapped all 9 billion possible single-letter genetic changes in the human genome and was made openly available. WeatherNext 3 delivers 50% more accurate precipitation forecasts a day or more ahead and is already in products. AlphaFold is used by 4 million researchers in 190 countries, TB chest X-ray screening has processed 25,000+ scans across six nations, and the diabetic retinopathy model has supported 1.15 million screenings. Google also released its AI & Economy ATLAS global usage insights.

Google · AI · 1d agoAI industry

Unfold The World: Factorize 4D Properties in Reinforcing Spatial Reasoning

FactoSR factorizes 4D spatial reasoning into XY, Z, and T reinforcement-learning sub-objectives, boosting VLM performance on VSI-Bench by 5.9% and All-Angles-Bench by 4.5%.

Researchers present FactoSR, a factorized reinforcement learning framework that decomposes world-consistent reasoning into planar correspondence, depth consistency, and temporal reversibility sub-objectives. Optimizing these verifiable constraints turns the ill-posed projection recovery problem into tangible reasoning steps. Evaluations show gains of 5.9% on VSI-Bench and 4.5% on All-Angles-Bench for 3D and 4D reasoning, arguing VLMs' spatial bottleneck stems from training on 2D projections versus latent 3D geometry and temporal continuity.

Hugging Face daily papers · 14d agoAI research

University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK

University of Manchester retrained NVIDIA Earth-2 CorrDiff and StormCast on Isambard-AI to forecast UK air pollution at 2-3 km resolution.

University of Manchester researchers led by professor David Topping adapted NVIDIA's Earth-2 generative AI frameworks to forecast air pollution across the UK. Earth-2 CorrDiff was retrained in two days on a single eight-GPU node of Isambard-AI (5,448 GH200 Grace Hopper Superchips, 21 exaflops) using a year of hourly simulated pollution data, producing a UK-wide model at 2-3 square kilometer resolution. The team added Earth-2 StormCast for time-dependent forecasts that ingest real air quality observations, and demonstrated the workflow runs on the DGX Spark desktop AI system. Open-source training data and workflows are planned so other countries and cities can build similar pollution models.

NVIDIA Blog · 21h agoAI industry

Climate-ModernBERT: Revisiting Corpus Composition for Domain-Adaptive Continued Pretraining

Climate-ModernBERT domain-adapted encoders reach 76.3 average F1 across nine climate benchmarks, 2.8 points above vanilla ModernBERT-Base.

The authors continue pretraining ModernBERT-Base on three climate corpora - academic text, climate-filtered web data, and synthetic documents - and compare joint mixtures against parameter-space merging of specialized checkpoints. The best model achieves 76.3 average F1 across nine climate NLP benchmarks, a 2.8-point improvement over the vanilla baseline. Academic climate corpora provide the strongest adaptation signal, and parameter-space merging outperforms joint multi-source training while preserving complementary corpus information; all variants are released.

arXiv cs.AI / cs.LG / cs.CL · 9d agoAI research

Technical Manual for a Toolkit for Measuring Contextual Individuation in Transformer Language Models

An open methodology toolkit measures whether transformer language models contextualize fixed word forms across domains using bridge forms and layer-wise silhouette analysis.

The manual documents an open toolkit built around 'bridge forms' - identical written words recurring across two or more subject domains with a different sense in each - to test whether transformer language models individuate word occurrences by context beyond the embedding layer. It covers declarative specification of bridge forms, Wikipedia corpus acquisition, occurrence localization, layer-wise representation extraction, domain-pairwise silhouette measurement, and visualization, justifying each choice against failure modes such as sense contamination and subword-tokenization misalignment. It is a methodological and implementation reference and reports no empirical results.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research

Molecular Déjà Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

Audit of 22 frontier models finds widespread verbatim retrieval of published molecular property values, with higher reasoning increasing recall of memorized numbers.

An arXiv audit tests 22 frontier LLMs across 12 molecular regression benchmarks for verbatim retrieval of published values. More than 50% of the LLMs show verbatim retrieval on five datasets, and identical experiments are flagged 89% more often at a high reasoning level than at the lowest one. Suppressing retrieval moves model prediction errors closer together in relative terms, suggesting predictive capability is not determined solely by memorized values.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research1

GeoNetwork Fixes Unauthenticated RCE Chain Affecting Government Geoportal Backends

GeoNetwork patched two chained flaws (CVE-2026-63219, CVE-2026-58400) enabling unauthenticated RCE in government geospatial metadata catalogs.

Two flaws in the open-source GeoNetwork catalog chain into unauthenticated RCE: a missing authorization check on the formatter upload endpoint (CVE-2026-63219, CVSS 8.6) and an unsafe Saxon XSLT processor configuration allowing Java execution (CVE-2026-58400, CVSS 9.1). Fixes shipped in versions 4.4.12 and 4.2.17 on July 8, 2026, with details published August 31. Ethiack fingerprinted 121 internet-exposed vulnerable deployments across 39 countries, 89% tied to government or military agencies. No exploitation in the wild or KEV listing was reported at disclosure.

The Hacker News · 14d agoVulnerabilityCVE-2026-63219CVE-2026-58400CVE-2024-36401+1 CVEs

How much of a problem is AI’s water use?

Analysis finds AI's water footprint growing, with data-center location and cooling technology largely determining the local environmental impact.

The article examines the growing water consumption of AI data centers and argues that real-world impact varies significantly depending on where facilities are sited and which cooling technology they use. It is a contextual analysis of AI's environmental footprint rather than news of a specific incident, breach, or release.

Ars Technica · AI · 20d agoAI industry

NCP-ArchPreview Technical Report: Moving towards Latent Space Language Models through Next Concept Prediction

An 8.9B-parameter latent-space language model using next-concept prediction matches OLMo-3-7B pretraining loss with only 51.3% of the training tokens.

NCP-ArchPreview augments next-token prediction with Next Concept Prediction over a product-quantized concept vocabulary built from hidden states, trained jointly end-to-end. The 8.9B model was trained on 5.73T tokens from the Dolma-3 dataset, the largest latent-space language model demonstration to date. It consumes 51.3% of the tokens to reach OLMo-3-7B's final pretraining loss and outperforms it by 2.45 points on the downstream macro-average, including a 5.99-point GSM8K gain. The learned latent space also enables lightweight domain adaptation via a 17M-parameter VQ module and improves speculative drafting accepted length by 4.17%.

Hugging Face daily papers · 8d agoAI research1

Atlas: Efficient Verifiable Semantic Search

Atlas delivers zero-knowledge proofs for HNSW semantic search, verifying RAG retrieval in under a second on SIFT1M and 2.0 seconds at 100M vectors.

Atlas lets a search provider prove that a query was answered correctly against a committed HNSW index without revealing the index, addressing provider deviations like truncation or bias. It combines offline preprocessing, a fixed-size-state restructuring of HNSW with a correctness proof, and timestep-tagged batching of per-step arguments. The system proves queries in under a second on SIFT1M and 2.0 seconds at 100 million vectors while preserving plaintext HNSW recall, and proven retrieval maintains end-to-end RAG answer quality at lower cost than prior verifiable retrieval systems.

arXiv cs.CR · 6d agoResearch3

IBM releases SOTA Granite Time Series PatchTST-FM-r2 model with commercial-friendly license

IBM released Granite Time Series PatchTST-FM-r2, a claimed state-of-the-art time series foundation model under a commercial-friendly license.

IBM Research announced the release of Granite Time Series PatchTST-FM-r2, published via the Hugging Face blog. The model is presented as state-of-the-art for time-series forecasting and is offered under a license permitting commercial use. No benchmark numbers or model size details were provided in the available text.

Hugging Face Blog · 7d agoModel release

The Frontier AEO Tracker: What Astra Chooses (and every other frontier model, and what you can do about it)

Latent Space launches an AEO tracker scoring 7 frontier models' product recommendations across 161 categories, revealing generational bias flips.

Latent Space built a tracker measuring Answer Engine Optimization by running 6 prompt variations across 7 frontier models with search enabled over 161 product categories, scoring first choices, alternatives, mentions, and anti-recommendations. It found 28 categories with a universally dominant primary choice and observed soft biases, such as models favoring their own lab's coding agents. Analysis of Anthropic's Sol→Astra and Opus→Fable generations showed newer models consulting fewer sources and being less likely to change answers when questions are paraphrased.

Latent Space · 9d agoAI research

Google's new AI model predicts the future from sales data, weather, and discount schedules

Google Research released TimesFM-3, a 330M-parameter multivariate time series forecasting model that tops Gift-Eval, FEV-Bench, and Time benchmarks and is on Hugging Face.

Google Research released TimesFM-3, a 330-million-parameter Transformer-based time series forecasting model trained on more than one trillion real and synthetic data points. It works zero-shot and adds multivariate support, ingesting related series, historical-only covariates, and known future events such as discount schedules and weather forecasts, while filling all future time steps in a single one-shot pass. Google reports first place among pretrained forecasting models on Gift-Eval, FEV-Bench, and Time, ahead of Amazon's Chronos-2, the Toto-2.0 family, and its own TimesFM-2.5. Weights are available on GitHub and Hugging Face, with BigQuery integration planned in the coming weeks.

The Decoder · 4d agoModel release2

Generative Late-Interaction Embeddings For Visual Document Retrieval

GLIE compresses visual document retrieval embeddings to four vectors per page while retaining nearly 80% of uncompressed nDCG@5 accuracy.

Researchers analyzing late-interaction retrieval embeddings found they lie exactly on the unit sphere and concentrate near a manifold of intrinsic dimension five to six. GLIE learns a few k vectors per page that serve as a lightweight index and a basis to regenerate the full embedding set for exact rescoring of top candidates at query time. On ViDoRe v1 with four vectors per page, GLIE retains nearly 80% of uncompressed nDCG@5 versus 70% for the best prior post-hoc method, using a 415K-parameter network trained in under three GPU-minutes on 1,000 pages.

Hugging Face daily papers · 7d agoAI research

[Control systems] GeoVision security advisory (AV26-913)

Canada's Cyber Centre (AV26-913) warns GeoVision GV-LPC2011/LPC2211 firmware 1.13 license-plate cameras are affected by vulnerabilities and urges updates.

The Canadian Centre for Cyber Security issued control-systems advisory AV26-913 on September 11, 2026, noting that GeoVision GV-LPC2011/LPC2211 firmware version 1.13 is affected by vulnerabilities. The bulletin references the vendor advisory GV-LPC-2026-09-01 but provides no CVE identifiers or exploitation details. Administrators are encouraged to review the linked advisories and apply updates as they become available.

Canadian Centre for Cyber Security · 5d agoAdvisory

GoDeep: Annotation-Free Open-Vocabulary 3D Scene Understanding via Language-Space Lifting

GoDeep achieves annotation-free open-vocabulary 3D segmentation by grounding structured image descriptions in language-only embeddings, outperforming CLIP-based lifting on out-of-vocabulary objects.

GoDeep uses a vision-language model purely as a translator, producing structured entity-level image descriptions that are grounded, projected, and aggregated in a general-purpose language-only embedding space, with no 3D training corpus or dedicated 3D encoder required. On ScanNet++ the pipeline is competitive with strong annotation-free baselines, and on a cultural-heritage benchmark a systematic vocabulary correction reverses initial CLIP-based rankings. Language-space embeddings separate genuinely out-of-vocabulary objects more sharply, localize them within scenes, and keep all predictions explainable as discrete text.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research