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Expert-Space Exploration in MoE Reinforcement Learning

ESRL explores MoE expert-routing space during RL, lifting Qwen3-30B-A3B Pass@1 by 3.2 points over GRPO at no extra cost.

ESRL (Expert-Space Exploration Reinforcement Learning) is an architecture-aware framework that treats expert routing in Mixture-of-Experts models as an additional source of rollout diversity. It preserves high-confidence experts as anchors, restricts stochastic routing to a plausible candidate pool, adapts perturbation strength to router entropy, and replays recorded expert paths during policy optimization. ESRL achieves the best performance across top-K, top-1, and shared-expert routing backbones on mathematics, science, and code tasks; on Qwen3-30B-A3B it improves average Pass@1 and Pass@8 over GRPO by 3.2 and 4.5 percentage points respectively, without additional sampling or compute.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research 2 sources

The September 2026 Security Update Review

ZDI's September 2026 Microsoft update review lists two already-exploited Windows EoP zero-days and dozens of critical RCEs across Office, SQL Server, and Windows services.

The review catalogs Microsoft's September 2026 fixes, marking CVE-2026-85880 (Windows ALPC) and CVE-2026-81963 (Windows Update Stack) as already exploited elevation-of-privilege issues. It also lists critical RCE flaws in Office, Word, Excel, PowerPoint, Outlook, SQL Server, Windows DNS, DHCP and Failover Cluster, plus graphics component RCEs. Azure-side fixes include Entra ID, Copilot Studio, Azure AI Language and Azure AD B2C elevation-of-privilege flaws.

Zero Day Initiative Blog · 8d agoAdvisory in the wildCVE-2026-85880CVE-2026-81963CVE-2026-70352+27 CVEs1

Microsoft’s September 2026 Patch Tuesday addresses 964 CVEs (CVE-2026-81963, CVE-2026-85880)

Microsoft's September 2026 Patch Tuesday fixes a record 964 CVEs, including two zero-days actively exploited in the wild.

Microsoft patched a record 964 CVEs in its September 2026 Patch Tuesday release, with 101 rated critical and 824 rated important, making it the largest Patch Tuesday to date. The release includes fixes for two zero-days that were exploited in the wild, with CVE-2026-81963 and CVE-2026-85880 highlighted in the release. Affected products span Windows core components, Office, Exchange, .NET, Visual Studio, Active Directory services (including AD CS and AD FS) and numerous Azure services. Tenable notes the release surpasses July's as the biggest ever.

Tenable Blog · 8d agoVulnerability in the wildCVE-2026-81963CVE-2026-858801

From Intent to Execution Grant: An Execution-Boundary Conformance Profile for High-Risk AI Actions

Researchers specify EBL-Core, an execution-boundary conformance profile binding AI agent intents, policies, and evidence into verifiable execution grants, validated with bounded tests.

The paper defines EBL-Core, a conformance profile deciding whether one fully materialized AI-generated candidate action may receive action-scoped execution authority. It binds a structured intent object, Root and Operational Policies, typed evidence, and a verifiable Decision Derivation through an Execution Release Contract, with lifecycle rules for Redemption and Revocation. Evaluation included 34 static vectors, 15 lifecycle checks, and 100 trials of 32 concurrent Redemption attempts yielding exactly one winner per trial. The authors state these bounded results demonstrate executability of the specified subset, not production readiness or complete mediation.

arXiv cs.CR · 6d agoAI safety & security1

Microsoft Patches Record 974 Vulnerabilities, Including Two Exploited Zero-Days

Microsoft's September 2026 Patch Tuesday fixes a record 974 CVEs, including two Windows zero-days exploited in the wild for privilege escalation.

Microsoft patched 974 vulnerabilities, its largest Patch Tuesday ever, including CVE-2026-85880, a heap buffer overflow in Windows ALPC allowing AppContainer sandbox escape to System, and CVE-2026-81963, a link-following flaw in the Windows Update Stack enabling local privilege escalation. Both were exploited as zero-days before the patch. ZDI's Dustin Childs says 20 of the fixed flaws are wormable, enabling unauthenticated remote code execution. The release also covers 723 Windows flaws and 222 Office bugs, plus fixes in Exchange, SharePoint, SQL Server, Azure and Exchange Server RCE (CVE-2026-55007).

SecurityWeek · 8d agoExploit / PoC in the wildCVE-2026-85880CVE-2026-81963CVE-2026-55007+5 CVEs1

E2A-Bench: Benchmarking Evidence-to-Action Reliability in Financial Chart Reasoning

E2A-Bench, a 969-query financial chart reasoning benchmark, finds VLMs fail evidence-to-action consistency, with fine-tuning amplifying BUY:SELL bias 4-6x.

E2A-Bench is a 969-query benchmark built from 323 HS300 constituents across three input modalities with deterministic OHLCV-derived evidence anchors, evaluating grounding, reasoning-action consistency, evidence-confidence calibration, and directional coverage via UCR, RCI, ECI, and NDR metrics. Testing 20 VLMs showed the lowest-hallucination model ranked near the bottom on coverage with only 6.4% directional coverage, and oracle-aided verification reduced unsupported claims but could collapse coverage. Financial fine-tuning amplified the BUY:SELL ratio by factors of 4.21 to 4.68 across base-fine-tuned pairs.

Hugging Face daily papers · 4d agoAI research

Android 0-day Vulnerability on Google Pixel Devices Actively Exploited in Attacks

Google patched CVE-2026-58704, an actively exploited Android zero-day allowing proximal privilege escalation via the Pixel cellular modem, urging the 2026-09-05 patch.

Google confirmed CVE-2026-58704, a high-severity elevation-of-privilege flaw in the Pixel cellular modem, is being exploited in limited, targeted attacks and shipped emergency fixes in the September 2026 Pixel Update Bulletin. The low-complexity bug requires no user interaction and enables proximal/adjacent privilege escalation with no additional execution privileges, phrasing Google has historically used for spyware-vendor and state-aligned zero-days. The Pixel bulletin patches 110 flaws including 12 critical RCEs, while the broader September Android update addressed roughly 180 vulnerabilities, including Wi-Fi memory-corruption bug CVE-2026-28662.

Cyber Security Newsupdated · 3h agofirst · 11h agoExploit / PoC in the wild 8 sourcesCVE-2026-58704CVE-2026-28662

Phishing 3.0: The Fight Moves to Agent Versus Agent

Agentic AI transforms phishing economics, enabling personalized multi-channel attacks with deepfakes like the $25M Arup deepfake heist.

The article argues phishing has evolved through three stages: from malicious content, to intent-based BEC, to AI-powered multi-channel campaigns where attacker agents autonomously conduct reconnaissance and generate tailored lures. The widely reported Arup case saw a deepfake video call impersonating colleagues convince an employee to approve transfers worth roughly $25 million. An Osterman Research study of 128 security leaders found 88% experienced trust-undermining incidents, while Microsoft 365 EOP and Google Workspace were measured missing hundreds of phishing messages per 100 mailboxes monthly. The author argues defenders must adopt their own agents to match attacker speed.

The Hacker News · 28d agoPhishing & fraud2

ENCP: Episode-Normalized Conformal Prediction for Vision-and-Language Navigation

ENCP calibrates conformal prediction per navigation episode, giving step-level coverage guarantees for vision-language navigation agents despite within-episode dependence.

Episode-Normalized Conformal Prediction (ENCP) rescales a nonconformity score by a VLN policy's residual confidence and calibrates one maximum score per episode, preserving step-level coverage of at least 1−α despite dependence among steps within an episode. Across four VLN policies and three nonconformity scores on R2R and REVERIE, ENCP meets all reported empirical step-coverage targets in seen-to-unseen evaluation. The model-agnostic uncertainty estimates can signal when an agent should defer to a stronger predictor or human assistance.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

Patch Tuesday - September 2026

Microsoft's September 2026 Patch Tuesday fixes 999 CVEs, a record, with two zero-day privilege escalation flaws already exploited in the wild.

Microsoft published 974 own-product vulnerabilities plus 25 non-Microsoft CVEs, totaling 999 — the most CVEs Microsoft has ever released in a single day. Two flaws are exploited in the wild: CVE-2026-85880, an out-of-bounds write in Windows ALPC granting SYSTEM privileges, and CVE-2026-81963, an improper link resolution flaw in the Windows Update Stack also leading to SYSTEM. Chrome's V8 zero-day CVE-2026-85046 was patched in Edge on September 2, but Microsoft had not published a corresponding advisory, leaving uncertainty about other Chromium fixes in Edge. October 14 lifecycle changes end servicing for Windows 11 24H2 Home/Pro, Office 2021, and Exchange Server 2016/2019.

Rapid7 Blog · 7d agoVulnerability in the wildCVE-2026-85880CVE-2026-81963CVE-2026-85046+10 CVEs

Augustinian BabyLM: What Ostensive Definition Can and Cannot Teach a Small Language Model

Study shows visually grounded token embeddings in a small masked LM persist through training and improve object-property knowledge, but escape standard BabyLM benchmarks.

The paper implements ostensive definition for a small DeBERTa masked language model trained on 10M words, seeding visually grounded tokens with embeddings derived from labeled image regions before training. Visual initialization leaves a persistent, seed-replicated advantage on object-property knowledge (COMPS) and a corpus-tailored Visual-Property Swap benchmark covering color, material, size, and shape, but has no effect on most BabyLM grammar benchmarks. Synthetic grounding of previously unseeded words causally transfers the advantage to exactly those words.

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

September 2026 Microsoft Patch Tuesday, (Tue, Sep 8th)

Microsoft's September 2026 Patch Tuesday fixes a record 973 vulnerabilities, including 113 critical and two Windows privilege-escalation flaws already exploited in the wild.

Microsoft patched 973 vulnerabilities this month, its largest Patch Tuesday ever and far above the previous record of 664 set in July 2026, with 113 rated critical. Two Important elevation-of-privilege flaws (CVSS 7.8) are confirmed exploited in the wild: CVE-2026-81963 in the Windows Update Stack (improper link resolution, affects Windows 11 and Server 2025) and CVE-2026-85880 in Windows ALPC (heap-based buffer overflow allowing sandbox escape to SYSTEM, affects Windows 10 and Server 2012-2022). Critical unauthenticated RCEs (CVSS 9.8) were also fixed in Skype for Business Server (CVE-2026-66302), Windows Message Queuing (CVE-2026-69579), and Windows RRAS (CVE-2026-69590). SANS urges prioritizing the two exploited EoP fixes, then patching exposed MSMQ, RRAS, and Skype for Business deployments.

SANS Internet Storm Center · 8d agoVulnerability in the wildCVE-2026-81963CVE-2026-85880CVE-2026-66302+5 CVEs1

ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation

ENEAS adds text prompting and semantic verification to video segmentation to keep tracking targets through occlusion and reject lookalike distractors.

ENEAS is a unified text-promptable method for instance tracking and open-concept semantic discovery in video, designed to fix temporal hallucinations, spatial fragmentation, and semantic misclassification seen in SAM 3-class foundation models. It extends the geometrically robust SeC architecture with a text-prompting adapter and temporal memory, and uses a verification layer combining fast visual embedding matching with conditional VLM refinement for ambiguous candidates. It targets 3D reconstruction pipelines where a single misclassified distractor corrupts the asset. Code and models are open-sourced.

Hugging Face daily papers · 14d agoAI research

Android’s September 2026 Updates Patch 180 Vulnerabilities

Google's September 2026 Android security updates patch 180 vulnerabilities including critical Wi-Fi memory corruption flaw CVE-2026-28662.

Google released September 2026 Android security updates addressing 180 vulnerabilities across two patch levels. The 2026-09-01 level fixes 95 bugs including 23 critical System component flaws enabling RCE, EoP, and DoS. The 2026-09-05 level addresses 85 additional defects in kernel and vendor components including a Wi-Fi memory corruption flaw (CVE-2026-28662) enabling remote code execution without privileges or user interaction.

SecurityWeek · 7d agoAdvisoryCVE-2026-28662

Ask Before You Optimize: Dynamic Pre-Formulation Clarification for Interactive Optimization

Researchers release OR-Clarify, a benchmark testing whether LLM agents ask clarifying questions before formulating optimization models from incomplete requests.

OR-Clarify evaluates pre-formulation clarification in operations research: each task gives a partial problem description, withholds structured hidden slots, and scores agents via bounded interaction with a simulated user, measuring slot recovery, stopping behavior, silent assumptions, and interaction cost. The authors also propose InterOPT, a two-stage framework that identifies formulation-critical gaps to decide when to ask or stop. In choice-based experiments InterOPT substantially outperforms all baselines in exact slot recovery and remains competitive in the open-ended setting.

Hugging Face daily papers · 13d agoAI research1

Microsoft fixes record 964 flaws, including 2 exploited zero-days

Microsoft's September Patch Tuesday fixes a record 964 CVEs, including two actively exploited Windows privilege-escalation zero-days, CVE-2026-81963 and CVE-2026-85880.

Microsoft's September 2026 Patch Tuesday addresses 964 customer-patchable CVEs (104 Critical, 860 Important), the largest release on record, out of 974 total listed. Two actively exploited zero-days are fixed: CVE-2026-81963, a link-following elevation-of-privilege flaw in the Windows Update Stack, and CVE-2026-85880, a Windows ALPC heap overflow enabling AppContainer sandbox escape, both with CVSS 7.8. Both zero-days were exploited before a patch was available and grant SYSTEM-level access after an initial foothold. The release also includes high-severity RCE fixes for Windows DNS Server, Remote Desktop Services, Exchange Server, SharePoint, and SQL Server.

Malwarebytes Labs · 7d agoExploit / PoC in the wildCVE-2026-81963CVE-2026-858801

SenseNova-U1.5: Towards Native Unified Visual Intelligence

SenseTime releases SenseNova-U1.5, an 8B-MoT encoder-free multimodal model unifying visual understanding, reasoning, and generation with native 4K resolution.

SenseNova-U1.5 is an 8B mixture-of-transformers multimodal model with an encoder-free, VAE-free architecture that understands, reasons about, and generates visual content at native resolutions up to 4K. Post-training optimizes specialized experts for visual aesthetics, bilingual text rendering, infographic generation, and image editing, consolidated through multi-expert on-policy distillation. Evaluations report gains in image fidelity, text rendering, multi-reference editing, and instruction following. The team plans to open-source training code including supervised fine-tuning, reinforcement learning, and on-policy distillation.

Hugging Face daily papers · 7d agoModel release

UltraViolet Cyber Equinox measures detection coverage against MITRE frameworks

UltraViolet Cyber launches Equinox, an AI-automated platform mapping SIEM and EDR detection coverage against MITRE ATT&CK and ATLAS frameworks.

UltraViolet Cyber announced Equinox, a detection engineering platform from its TIDE team that maps existing detections and log sources against MITRE ATT&CK and MITRE ATLAS. It performs coverage analysis in under 30 minutes and recommends vendor or custom detections to fill gaps, with engineers reviewing and backtesting each recommendation. In one customer trial, mapped technique coverage rose from 59 of 222 techniques (26.6%) to 136 of 222 (61.3%) without increasing alert volume.

Help Net Security · 1d agoTools2

Threat Assessment: Egregor Ransomware

Unit 42 assesses Egregor ransomware, a Sekhmet variant likely run by former Maze affiliates using Qakbot, IcedID, and Ursnif for initial access.

Since September 2020, Unit 42 observed Egregor ransomware attacks across the U.S., Europe, Asia-Pacific, and Latin America, coinciding with the Maze team's shutdown announcement. Egregor, a variant of the Sekhmet family, uses commodity malware such as Qakbot, IcedID, and Ursnif for initial access, followed by scripts that modify firewalls, enable RDP, and deploy Cobalt Strike for reconnaissance and exfiltration. A PowerShell script uninstalls the McAfee agent and downloads the Egregor DLL via BITS, executed with the -passegregor10 key. Victims face a three-day ransom deadline before exfiltrated data is published on the Egregor Hall of Shame leak site.

Palo Alto Unit 42 · Aug 17, 2026Ransomware in the wild

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

Training-Free Speech-Centric Omni Understanding with Frozen VLMs

Audio-visual understanding remains challenging because models must jointly interpret spoken content, visual events, and their temporal relationships. Existing omni models typically introduce dedicated audio encoders and rely on expensive audio-video-text training, tightly coupling omni capability to specific VLM backbones and potentially weakening their existing visual and reasoning abilities.…

Hugging Face daily papers · Aug 6, 2026AI research

日本のビジネスパーソンを対象としたWiz調査で 「AI導入加速」はクラウド移行を上回ることが明らかに

Wiz survey of Japanese business professionals finds AI adoption outranking cloud migration and 60% planning AI security investment.

A Wiz survey of Japanese business people found that accelerating AI adoption now outranks cloud migration as a priority. At the same time, more than 80% feel behind in preparing for AI-driven cyber-attacks, and 60% plan to invest in AI security. The findings highlight a preparedness gap as organizations adopt AI faster than they secure it.

Wiz Blog · 22d agoIndustry

Ambient @ EgoLongQA 2026: Distilling Long-Video perception into a Sub-2B Model

Ambient team wins EgoLongQA 2026 sub-2B division by distilling an agentic long-video perception pipeline into a 2B vision-language model.

Ambient's entry to the EgoLongQA track of the Wearable-AI Challenge at ECCV 2026 placed first in the <=2B parameter division with 0.8279 on the held-out test set. The system distills the junior perception module of a tool-using agentic pipeline into a 2B student, reaching 89% of the pipeline's accuracy with 1.1% of its parameters and lifting a 27.1% base model to 81.4%. To meet the division limit, the multilingual embedding table is pruned from 248,320 to 143,469 rows, reaching 1.9985B parameters with provably identical logits on retained rows.

Hugging Face daily papers · 7d agoAI research

Hierarchical NeRF with JAX3D for Volumetric Rendering, Novel-View Synthesis, and 3D Reconstruction

MarkTechPost tutorial implements a hierarchical NeRF in JAX using jax3d volume-rendering primitives for novel-view synthesis and 3D reconstruction.

The tutorial builds an end-to-end hierarchical Neural Radiance Field using JAX, Flax, Optax, and jax3d's volume-rendering functions (sample_along_rays, volume_rendering, sample_piecewise_constant_pdf). It implements positional encoding, skip connections, separate coarse and fine networks, and view-direction conditioning with hierarchical importance sampling. Training uses JAX JIT compilation, Adam optimization, exponential learning-rate decay, and gradient clipping. Evaluation covers PSNR, depth and opacity visualization, 360-degree rendering, and marching-cubes geometry extraction.

MarkTechPost · 3d agoAI research

Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models

Researchers release Explainability Assistant, an open-source conversational XAI tool using LLM function calling, lifting intent-parsing accuracy from 76.8% to 94%.

The paper introduces the Explainability Assistant, an open-source conversational XAI system for interpreting energy consumption forecasting models such as genetic-programming symbolic regressors. It uses LLM function calling instead of rigid custom grammars, achieving 94% intent-parsing accuracy versus 76.8% for prior work TalkToModel, and adapts to different ML problem types without task-specific fine-tuning. Comparative evaluation with energy domain specialists against a traditional XAI dashboard showed improved usability, with all experts preferring the conversational interface.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

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

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 · 16h agoAI industry

Curriculum Learning as Transport: Understanding Curricula with Wasserstein Geodesics

Researchers model curriculum learning as Wasserstein transport over difficulty distributions, finding curriculum benefits are strongly task- and budget-dependent with no dominant strategy.

The framework represents curricula as trajectories of training distributions over discrete difficulty levels, decoupling ordering, matched exposure, endpoint smoothness, and pacing. Across a calibrated suite of 12 tasks and 33 difficulty axes under fixed training budgets, no single strategy dominates, though easy-to-hard ordering improves hard-level performance relative to exposure-matched static sampling. Endpoint smoothness and pacing substantially affect where along the difficulty spectrum a curriculum is effective, and the transport view supports extensions to learned pacing and structured difficulty spaces.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research1

CARDEA: Auditable Reasoning Grounded in Spatial Evidence for End-to-End Coronary Angiography Interpretation

CARDEA, a vision-language model trained only on public data, matches cardiologists on coronary angiography complexity assessment while exposing auditable bounding-box evidence.

CARDEA is a unified large vision-language model serving as the inference core of an end-to-end coronary angiography pipeline from multi-view videos to study-level diagnosis. It was trained on public datasets through visual alignment, self-distilled Chain-of-Box cold start, and reinforcement learning with verifiable rewards encouraging bounding-box reasoning. It reached 0.91 accuracy on dominance classification under domain shift and 0.90 on complexity assessment, comparable to two interventional cardiologists. RLVR raised zero-shot report generation vessel-severity macro-F1 from 0.513 to 0.686, while supervised imitation alone did not.

Hugging Face daily papers · 10d 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

Ambient @ EgoProactive 2026 : Proactive Egocentric Assistance with Visually Grounded Supervision

ECCV 2026 challenge winner reformulates egocentric intervention timing as single-token classification, boosting macro-F1 by 0.249 over free-form generation.

The paper describes the winning submission to the EgoProactive track of the ECCV 2026 Wearable AI Challenge, ranking first in the large-model division and second in the <=2B division. The method reformulates intervention timing as single-token yes/no classification, improving macro-F1 by 0.249 and G-mean by 0.30 over free-form generation. Supervision generated by a tool-calling video agent transferred better than a narration-only dataset that was four times larger and ten times cheaper, suggesting visual grounding matters more than annotation volume.

Hugging Face daily papers · 7d agoAI research

Saving Jet Fuel

Tutorial optimizes flight paths to cut jet fuel costs using open-source Scikit-decide planning framework and OpenAP aircraft performance models.

A technical walkthrough demonstrates wind-aware flight path optimization using Scikit-decide, an open-source framework for reinforcement learning and automated planning, paired with OpenAP fuel-consumption models built by Dr. Junzi Sun at TU Delft and NOAA wind data. A Boeing 787-9 flying EWR to FCO can require roughly $68K in fuel, and adjusted routing could save thousands. The post uses Python 3.12, DuckDB with spatial extensions, and QGIS for map rendering.

Hacker News · AI · 22h agoAI tools & infraHN 45↑ · 19 comments

Top 10 Best Cloud Infrastructure Entitlement Management (CIEM) Tools in 2026

2026 CIEM guide ranks Wiz, Prisma Cloud, Okta, Entra Permissions Management and specialists Sonrai, Britive, Tenable/Ermetic for cloud entitlement right-sizing.

Buyer's guide covers ten CIEM products across three market routes: CNAPP-bundled (Wiz, Prisma Cloud), identity-suite (Okta, CyberArk, SailPoint, Saviynt) and specialists (Sonrai, Britive, Tenable/Ermetic). It cites machine identities outnumbering humans 10:1 plus effective-permissions sprawl as core drivers, with JIT elevation as the fix. Notable consolidation includes Tenable acquiring Ermetic and Zscaler acquiring Canonic.

Cyber Security News · 1d agoTools

Offensive Security Investments Surge as AI Threats Increase

Omdia's Theresa Lanowitz discusses surging offensive security investment and both the promise and risks of agentic AI in pentesting and red teaming.

In a Dark Reading News Desk interview, Omdia analyst Theresa Lanowitz discusses why organizations are increasing offensive security spending as AI-driven threats grow. She weighs the potential and the risks of applying agentic AI to penetration testing, red teaming, and related offensive security practices.

Dark Reading · 19d agoAI industry

One Symptom, Three Levers: A Critical Review of On-Policy Self-Distillation

A review paper frames on-policy self-distillation collapse as governed by three levers: token weighting, privileged information, and guidance decay.

The paper critically reviews On-Policy Self-Distillation (OPSD), where a language model trains on its own generations scored token-by-token by a teacher conditioned on privileged information such as reference solutions or environment feedback. It identifies collapse, the progressive narrowing of producible reasoning paths, as the dominant failure mode and analyzes it through three levers: signal weighting, the nature of privileged information, and teacher dynamics. The review is restricted to mathematical reasoning, reports no new experiments, and offers a shared vocabulary separating settled findings from disputed ones.

Hugging Face daily papers · 22d agoAI research

GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation

GE-Act 2.0 is a from-scratch pretrained world-action model for robotic manipulation, with success rising from 17.1% to 44.1% as co-training data scales to 30,000 hours.

Genie Envisioner Act 2.0 (GE-Act 2.0) is a world-action model whose generative and action components are all initialized from scratch on manipulation data, combining a control-oriented autoencoder (CoAE), single-step visual planner (SVP), and inverse dynamics model (IDM) trained jointly via knowledge-aligned selective optimization (KASO). Scaling co-training data from 300 to 30,000 hours raises zero-shot success from 17.1% to 44.1% on G1-OP and 13.4% to 31.1% on G2-90D, despite the latter comprising under 2% of data, suggesting cross-embodiment transfer. Gains span 19/20 and 18/20 skill groups, and skill-specific coverage correlates with zero-shot OOD success (Pearson r=0.80).

Hugging Face daily papers · 13d agoAI research