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The Router Within: Eliciting Native Skill Routing from a Frozen LLM

Gavel reads native skill-routing signals from a frozen LLM's forward passes with two linear maps, beating retrieve-and-rerank pipelines by up to 21.9 points on Qwen3-32B.

Gavel (Glance And Verdict from a frozen LLM) elicits skill routing from a frozen agent LLM using two trained linear maps that read mid-layer states, keeping all skill text out of context. A glance step scores the full library against compact per-skill banks built in one forward pass at installation; a verdict step resumes shortlisted skills' forward passes and fuses likelihood and yes/no judgments as a product of experts. It transfers zero-shot to three public benchmarks plus SkillTraj, a new benchmark of 372 simulated agent trajectories. On Qwen3-32B it beats progressive disclosure and retrieve-and-rerank pipelines adding 1.2B–16B external parameters by up to 13.4 points on written tasks and 21.9 when skills are needed mid-rollout.

Hugging Face daily papers·updated Sep 14, 17:58 UTC · 2d ago·first Sep 13, 20:00 UTC · 3d agoAI research 2 sources

Cybercriminals Turn GTA VI Leaks Into Malware Bait

Attackers spread fake 113GB GTA VI builds whose 50KB payload whitelists the entire C: drive in Windows Defender, alongside credential phishing and infostealer campaigns.

Researchers found that a 113GB file claiming to be a playable Grand Theft Auto VI build is 99.99% empty data hiding a tiny malicious payload that excludes the entire C:\ drive from Windows Defender and kills security software, preparing systems for follow-on attacks. Related lures include fake GTA 6 Windows installers using DLL side-loading, a fake 'GTA 6 Mobile' app redirecting to infostealer and ransomware infrastructure, and counterfeit Rockstar Social Club login pages harvesting credentials. The fakes ride genuine leak momentum from the leaker CyberLeek, and Kaspersky separately documented over 19 million attempted downloads of game-themed malware in a year, with GTA, Minecraft, and Call of Duty the most abused brands. No legitimate playable GTA VI build is circulating; the game launches November 19 on consoles.

Security Affairs·Aug 24, 17:27 UTC · 23d agoMalware in the wild

SAFIRE: Safety-Critical Benchmark for Fine-grained Fire and Smoke Understanding in Multimodal LLMs

SAFIRE, an 83K-image fire and smoke benchmark, shows open-source multimodal LLMs average only 61.9% accuracy on safety-critical fire reasoning.

SAFIRE is a large-scale benchmark for fire-smoke understanding in multimodal LLMs with 83K captioned images across 20 scenarios and 193K multiple-choice VQA questions spanning 10 evaluation dimensions from perception to higher-order reasoning. Annotations were built via a GPT-5.4-assisted multi-stage pipeline with MLLM majority voting. Ten open-source MLLMs (8B-38B) average 61.9% accuracy, exposing major gaps in safety-critical reasoning. Adapting vision encoders on 7% of the domain data raises fire-scene classification from 20.1% to 64.5%.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:59 UTC · 9d agoAI research

Two Compromised joyfill npm Packages Run RAT When Imported Into Node.js

The Hacker News·Aug 4, 05:21 UTC · Aug 4, 2026Malware1

Gradium Launches Voice Design: Write a Prompt, Get a Brand New Synthetic Voice in Seconds

Gradium, a Kyutai spinout, launched Voice Design, generating custom synthetic voices from text descriptions in seconds across five languages.

Gradium, a Paris-based voice AI company spun out of Kyutai, launched Voice Design, which generates new synthetic voices from 1-500 character text descriptions in seconds without needing reference audio or speaker consent. The feature is live in the Gradium API and Studio, free on every plan including the free tier, and kept voices run on the standard streaming TTS endpoint at the same latency as catalog voices. Vendor-run blind pairwise listening tests across 7,627 comparisons report a 72.6% win rate, 13.6 points ahead of ElevenLabs at 59.0%, placing first in all five tested languages, with the largest margins on regional accents such as Quebecois French (97%).

MarkTechPost·Sep 9, 07:29 UTC · 7d agoAI industry

Path to Astra: critical capabilities and frontier safeguards

OpenAI says Astra is its first model to meet the Critical cybersecurity capability threshold under the Preparedness Framework, launching with stronger safeguards.

OpenAI published 'Path to Astra', announcing that Astra is the first OpenAI model to meet the Critical cybersecurity capability threshold under its Preparedness Framework. The company says the model will be released with strengthened frontier safeguards, marking a milestone in frontier capability and safety evaluation.

OpenAI News·Sep 1, 13:00 UTC · 15d agoModel release

Playco cut manual fixes 50% prototyping games with GPT-6 Astra

Game studio Playco used OpenAI's GPT-6 Astra to build three game prototypes, reporting 50% fewer manual fixes than with the previous model.

Playco, a game development company, used OpenAI's GPT-6 Astra model to generate three themed game prototypes from a single grey-box foundation. The company reports the new model cut manual fixes by 50% compared to its previous model workflow. The piece is an OpenAI-published customer story highlighting Astra's use in game prototyping.

OpenAI News·Sep 3, 12:00 UTC · 13d agoAI industry

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·Sep 3, 20:00 UTC · 13d agoAI research

Right Tool, Right Job: Native-Language Evaluation, Tokenizer Sensitivity, and Methodological Findings from a French-Only BabyLM

French BabyLM entry METRON-FR (125M GPT-2, 92.47M words) shows tokenizer artifacts dominate child-scale zero-shot evaluation; proposes standard diagnostics.

METRON-FR is a 125M-parameter GPT-2 pretrained on 92.47M French words, submitted to the BabyLM 2026 Strict track, scoring 85.97% on the native Quebec-French QFrBLiMP benchmark and 62.80% on the BabyLM-weighted leaderboard. A cross-lingual GLUE protocol combining French task-data translation with rank-16 LoRA shows relational tasks gain while world-knowledge tasks regress. Bilingual Lexicon Induction reaches p@1 of 68.84%, 18x above chance, and ablations show single-token zero-shot scoring is dominated by tokenizer and template artifacts at child scale.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 16:43 UTC · 1d agoAI research

LynnReal-Omni: Native multi-modal Video Generation for Agentic Visual Workflows

LynnReal-Omni unifies controllable video generation tasks in a 32B multimodal diffusion transformer, with a 27B Flash variant rendering 540p clips in 377 ms.

LynnReal-Omni is a native multimodal video generation framework built on a 32B shared multimodal diffusion transformer unifying text-to-video, image-conditioned generation, reference guidance, structural control, editing, restoration and long-video generation, accepting heterogeneous inputs like 3D renders and game recordings for agentic visual workflows. A dedicated 27B Flash model enables real-time rendering, producing a 22-frame 540p video in 377 ms on one H100 versus 843 ms for the full model. The work introduces a curated multi-shot audiovisual data pipeline and MSAVP, a 100-prompt, 20-metric evaluation design covering instruction following, plausibility, visual quality, temporal behavior and audio coordination.

Hugging Face daily papers·Sep 13, 20:00 UTC · 3d 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·Sep 4, 16:38 UTC · 12d agoAI research

NIST Seeks Public Input on AI-Ready NVD Modernization

NIST is seeking public comment on modernizing the National Vulnerability Database to support AI-powered vulnerability research.

The US National Institute of Standards and Technology announced it is soliciting public input on modernizing the National Vulnerability Database. The initiative aims to make the NVD AI-ready to support AI-powered vulnerability research and analysis.

Infosecurity Magazine·Aug 12, 12:30 UTC · Aug 12, 2026Policy & legal

From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge

Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.

Researchers used layerwise interventions on hidden states to separate query-routing signals from target knowledge in language models, testing Qwen, Llama, and Gemma on country-continent questions with varied answer types. A pair-conditioned request direction strengthens before interventions alter downstream knowledge, opening a causal window while answer-supporting content is still forming. Trajectories differ by model: Gemma shows a partially overlapping mid-layer routing profile, while Llama has no sustained routing-effect window under the same gates.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:39 UTC · 6d agoAI research1

Show HN: Panel – A research workspace where the agent can build its own panes

Panel is an open-source research workspace where AI agents dynamically build their own panes, posted on Hacker News.

Panel, shared as a Show HN project on GitHub, is a research workspace in which the agent can construct its own panes rather than using a fixed interface. The post received 41 points and 8 comments on Hacker News. It targets agentic research workflows with a dynamically generated UI.

Hacker News · AI·Sep 15, 13:58 UTC · 1d agoAI tools & infraHN 41↑ · 8 comments

Abyssos: Technical Analysis of a New Modular RAT

Zscaler ThreatLabz analyzes Abyssos, a new modular C++ RAT offering credential theft, file exfiltration, and VNC-based remote access.

Zscaler ThreatLabz identified a new malware family tracked as Abyssos in late June 2026. Abyssos is a modular remote administration tool (RAT) written in C++ that supports credential theft, file exfiltration, and remote access via VNC. The malware is under active development, with multiple version numbers and obfuscation passes designed to evade security products. The analysis covers its core features, configuration, obfuscation, and network communication protocol.

Zscaler ThreatLabz·Aug 10, 15:51 UTC · Aug 10, 2026Malware

Import AI 470: No rights for machines; automating environment generation with SPADE; and building better GPU kernels with Hawkeye

METR analysis finds AI accelerating cyber vulnerability discovery, while SPADE self-play environment generation improves Qwen3 reasoning benchmark scores at 30B scale.

Import AI 470 discusses a METR research note reporting differential acceleration from AI: major acceleration in reported cyber vulnerabilities (cURL, OpenSSL, Firefox, Microsoft, NVD, OSV), minor acceleration in mathematics, and no measurable acceleration in AI-research optimization benchmarks. It also covers SPADE, a self-play framework from a multi-university team (University of Washington, Stanford, MIT, CMU, and others) that co-evolves executable training environments and agent capability using Environment Designer and Reasoning Agent roles with hint-based regret rewards. Trained on Qwen3-4B-Instruct-2507, Qwen3-8B, and Qwen3-30B-A3B-Instruct-2507 via GRPO (400 rollouts of 25 environments), SPADE lifted the 30B-A3B game-environment suite average to 58.3, +8.1 over base, and improved tool-use results across backbones. The issue also references Hawkeye for building better GPU kernels.

Import AI·Aug 24, 13:12 UTC · 23d agoAI research

France Establishes New Government-Focused Cyber Incident Response Unit

France created REACTIV, an ANSSI-led interministerial cyber incident response unit for state services, after the DGFiP breach exposed up to 678,000 taxpayers.

ANSSI announced REACTIV (Interministerial Response & Action against Data Breaches) on September 7, a dedicated incident response capability for French state services. It lets ANSSI require ministries to take urgent protective measures for citizens' data and lead centralized technical crisis communications during attacks on state services. The move follows the DGFiP tax authority attack that exposed data of 350,000 to 678,000 taxpayers, after which the Prime Minister ordered an extensive audit of ANSSI. Two suspects aged 16 and 18 from the ZeroBytes hacking group were arrested in late August.

Infosecurity Magazine·Sep 8, 14:30 UTC · 8d agoPolicy & legal

AI for Games in the Foundation Model Era

Survey organizes foundation-model AI for games into six roles and analyzes which capabilities transfer across playing, design, building, runtime adaptation, and testing.

A survey maps foundation-model and learned world-model research across the game lifecycle into six roles: playing/acting, modeling players and games, designing games, building/maintaining games, runtime generation/adaptation, and testing/evaluation. The authors identify cross-role connections such as trajectories training world models and design specifications driving executable implementations. Control schemes, rules, engine interfaces, state representations, and player contexts often remain setting-specific, so downstream claims require validation in the target setting. Evaluation is most standardized for bounded game playing, while persistent state, repeated revision, validated player modeling, and automated testing remain less established.

Hugging Face daily papers·Sep 14, 20:00 UTC · 2d agoAI research

Iran-Linked Hackers Use Fake LinkedIn Job Offers to Deploy NodeRabbit and PollCat RATs

Iran-linked Mirage Kitten targets software engineers with fake LinkedIn recruiter coding tests deploying new NodeRabbit and PollCat RATs.

Kaspersky researchers link the campaign to Mirage Kitten (also tracked as UNC1549, Smoke Sandstorm, Nimbus Manticore), with victims in aviation, aerospace and fintech in Egypt, Ethiopia and Afghanistan. Trojanized npm dependencies (colorized_terminal, pretty-log) bundled in coding-challenge archives launch the Node.js implants across Windows, Linux and macOS. NodeRabbit uses AES-256-GCM-encrypted C2 via Azure, and its third variant persists through a fake GitHub Copilot Helper VS Code extension plus Git post-merge/post-checkout hooks. PollCat is an obfuscated JavaScript RAT that registers with C2 before OTP authentication and inventories tools from 24 security vendors.

GBHackers·Sep 9, 12:52 UTC · 7d agoThreat actor in the wild1

Encoded Early, Used Late: Where Transformers Begin to Act on an Inferred Partner's Expertise

Probing finds transformers represent an inferred dialogue partner's expertise in early layers long before it causally influences output.

Using ExpertCollab, a corpus of multi-turn research-planning dialogues between model-played personas at four expertise levels, researchers show that a partner's inferred expertise is most decodable in early transformer layers and decays to near chance before the network's midpoint. Counterfactual patching reveals that injecting the expertise difference at peak decodability barely changes a fixed late-layer readout, while injection past the midpoint propagates almost completely. The result bounds where readout or steering of partner-conditioned behavior must intervene, demonstrated on a single model with a synthetic corpus.

Hugging Face daily papers·Sep 6, 20:00 UTC · 10d agoAI research

Decomposition-Guided Diffusion Language Models for Inertial Confinement Fusion Prediction

ICF-DLM, the first language-model-based inertial confinement fusion predictor, cuts peak-timing error from 11.6 to 9.2 steps versus LLaMA-3-8B.

Each National Ignition Facility shot costs roughly one million dollars, motivating accurate AI surrogates for predicting 512-step neutron-rate waveforms from laser pulses and target parameters. ICF-DLM combines physics-typed decomposition into yield, peak timing, and local waveform; bidirectional denoising that defers commitment to peak location; and a physics-driven PPO reward. On ICFBench (50,000 simulations plus 232 experimental shots) it outperforms a matched autoregressive LLaMA-3-8B, classical sequence models, and LLM-based time-series predictors.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:00 UTC · 9d agoAI research

How Fragile Is Safety Alignment at Frontier Scale? A Single-Direction Attack on a 320B MoE

Researchers show directional ablation breaks refusal in GLM-5.3-Flash, a 320B-parameter MoE, cutting refusal by 41–89 points across seven benchmarks.

The study extends directional ablation, a white-box attack that removes an aligned LLM's refusal behavior, from dense models up to ~70B parameters to GLM-5.3-Flash, a 320B-parameter mixture-of-experts model with 288 routed experts, four-wide hyper-connection residual, and block-FP8 quantization. Editing attention, dense, and routed-expert writers jointly removes 0.776 of refusal, with 74% of the effect existing only under the joint intervention; the conventional module-name-based recipe reaches only 0.066 and fails silently on MoE architectures. The attack yields 41–89 percentage-point reductions in refusal across seven harmful benchmarks with no detected capability change, and a category-concentrated refusal residue survives all edits at ranks 1 to 12.

arXiv cs.CR·Sep 9, 06:48 UTC · 7d agoAI safety & security

ReactHuman: A Physics-Grounded Benchmark for Human-Like Reactive Decision-Making in Embodied Multimodal LLMs

ReactHuman benchmark tests whether multimodal LLMs react safely to sudden household hazards; seven evaluated models mishandle roughly one hazard in three.

ReactHuman is the first physics-grounded benchmark for human-like reactive decision-making, placing a multimodal LLM as the brain of a simulated humanoid facing 17 event families of sudden household hazards across over 1,000 bit-for-bit reproducible scenes with annotation-free ground truth from 240 Hz rigid-body simulation, including adversarial objects whose appearance contradicts their physics. A five-metric suite scores each reaction along reasonable, safe, and physically grounded axes, and every committed plan is physically executed. Seven representative MLLMs mishandle roughly one hazard in three, act from fixed dispositions rather than the observed scene, trust appearance over motion, and miss interception points at meter scale; none of these failures shrink with model scale.

Hugging Face daily papers·Sep 8, 20:00 UTC · 8d agoAI research

Researchers open-source a Wi-Fi cyber range for security training

NTNU and Aegean researchers open-source a software-emulated Wi-Fi cyber range using mac80211_hwsim with LLM-assisted scenario building.

Researchers from the Norwegian University of Science and Technology and the University of the Aegean published a design and prototype for a cyber range dedicated to IEEE 802.11 security training, emulating access points and clients with mac80211_hwsim, Linux namespaces, hostapd, wpa_supplicant, dnsmasq, and FreeRADIUS. The platform bundles Aircrack-ng, Wireshark, and custom tools WPAxFuzz and Bl0ck, and can convert plain-language scenario descriptions into deployable definitions via a locally hosted Llama model. A working prototype covering scenario creation and deployment is on GitHub; monitoring, access control, and orchestration zones remain future work.

Help Net Security·Aug 24, 04:21 UTC · 23d agoTools1

Stampli cuts launch hours by 68% using ChatGPT Work

AP automation firm Stampli used OpenAI Codex and ChatGPT Work to cut product launch production hours by 68%.

Stampli, an accounts-payable automation company, compressed weeks of launch production into days using Codex and ChatGPT Work. Facing a fixed deadline with design resources committed elsewhere, the team reported a 68% reduction in launch hours. The piece is an OpenAI customer adoption case study.

OpenAI News·Aug 20, 00:00 UTC · 27d agoAI industry

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·Sep 9, 20:00 UTC · 7d agoModel release

GPT-6 Astra, Looped Transformers, and Hidden Reasoning

OpenAI released GPT-6 Astra, its strongest model to date, with standout 3D rendering and computer-use performance and 99.9% on ARC-AGI-3.

Sebastian Raschka reviews OpenAI's GPT-6 Astra, calling it the best model he has used, with disproportionate gains in 3D rendering, animation, and computer use through the Codex/ChatGPT harness. The model scores 99.9% on ARC-AGI-3 versus 7.8% for GPT-5.6 Sol and leads the Artificial Analysis Coding Agent Index, though gains on independent aggregate indices are more incremental. The article also explains looped transformer/recurrent depth architecture rumors, speculation that Astra hides its chain-of-thought reasoning, and recent research insights on the topic.

Hacker News · AI·Sep 9, 14:37 UTC · 7d agoModel releaseHN 84↑ · 12 comments2

One resignation turned the embers of AI fear into a wildfire

Interconnects argues a frontier-lab researcher's safety resignation went viral via media coordination, reigniting AI existential-risk discourse.

The essay analyzes why researcher Jacob Coxon's resignation over AI safety risks went viral, aided by a Wall Street Journal exclusive, advocacy-group amplification, and Daniel Kokotajlo's same-day Joe Rogan appearance. It notes Evan Hubinger's >10% extinction-risk figure and criticizes existential-risk discourse for conflating very different meanings of the term. The author assigns near-zero probability to complete extinction but argues concrete risks such as cyberattacks on critical infrastructure and bio-risks merit debate. It also rejects recursive self-improvement forecasts, proposing 'lossy self-improvement' where models excel at math and code but remain limited elsewhere.

Interconnects·Sep 10, 15:28 UTC · 6d agoAI safety & security

Hackers Use Fake LinkedIn Job Offers to Infect Developers With New Cross-Platform RATs

Iran-linked Mirage Kitten uses fake LinkedIn job challenges to deliver new cross-platform RATs NodeRabbit and PollCat to developers in fintech, aviation, and aerospace.

PolySwarm documented a campaign by Iran-linked Mirage Kitten (UNC1549) that uses fake recruiter personas and technical hiring challenges on LinkedIn to deliver the newly documented RATs NodeRabbit and PollCat, which run on Windows, Linux, and macOS. A challenge archive bundles a fake npm package (colorized_terminal 2.1.0) in node_modules that loads NodeRabbit, while a React-based challenge delivers PollCat with an attacker-controlled OTP screen. NodeRabbit persists through a malicious Visual Studio Code extension and Git post-merge/post-checkout hooks; PollCat persists via scheduled tasks, cron, and LaunchAgents. Victims were observed in fintech, aviation, and aerospace, with confirmed targets in Egypt, Ethiopia, and Afghanistan.

Cyber Security News·Sep 9, 14:07 UTC · 7d agoMalware in the wild

Show HN: LLM Attention Visualization

A developer released a browser-based tool that visualizes which past tokens influence each LLM output token using aggregated, value-weighted attention scores.

A Show HN project presents a React application built on Transformers.js that renders per-token attention influence by aggregating attention weights scaled by value-vector magnitudes across all attention heads and layers. To expose internal tensors, the author instrumented the ONNX computation graph, hosted a modified model on Hugging Face, and pre-generated prompts to avoid long model downloads in the browser. Demos with a 600-million-parameter model show how verbatim copying draws heavily on source tokens and how single outputs blend information from multiple phrases.

Hacker News · AI·Sep 8, 16:59 UTC · 8d agoAI tools & infraHN 41↑ · 9 comments