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Présentation de Meta One : Un service d’abonnement offrant davantage de fonctionnalités et d’IA pour créer, se connecter et se démarquer

Meta launches Meta One subscription bundles with expanded Meta AI usage and creator/business tools, already at 15 million subscriptions and trials.

Meta launched Meta One, a new subscription service across Instagram, Facebook, WhatsApp and Meta AI with more than 50 features and 15 million subscriptions and trials to date. Core and Premium bundles add heavier use of compute-intensive AI features, including image creation/editing and video generation via the Muse models, plus tools like Restyle on Instagram. Pricing starts at EUR 2.49/month for single-product plans, EUR 6.99 for bundled consumer plans and EUR 16.99 for creator/business bundles; the core Meta AI experience remains free.

Meta Newsroom·Sep 15, 15:25 UTC · 1d agoAI industry

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

How a researcher uses Codex and ChatGPT to search for new antimicrobial molecules

OpenAI profiles César de la Fuente's lab using ChatGPT and Codex alongside deep-learning models to accelerate antimicrobial molecule discovery.

OpenAI published a case study on bioengineer César de la Fuente's lab, which uses ChatGPT and Codex for hypothesis brainstorming, code writing, dataset processing, and bridging knowledge gaps across biology, chemistry, and computer science. The lab's deep-learning models scan genome and protein databases for antimicrobial peptide candidates, potentially cutting initial searches from years to hours. Bacterial antimicrobial resistance was associated with about five million deaths in 2021, a toll projected to roughly double by 2050.

OpenAI News·Sep 10, 16:00 UTC · 6d agoAI industry1

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·Sep 4, 17:32 UTC · 12d agoAI research1

Cyberattack on logistics giant Ceva hits retailers and Steam customers across Europe

Cyberattack on Ceva Logistics disrupted eight European warehouses, delaying shipments for Bol, De Bijenkorf, Ajax and exposing Steam hardware buyers' data.

A cyberattack on Ceva Logistics disrupted operations at eight European warehouses, delaying shipments for Bol, De Bijenkorf, Ace & Tate, Ajax and Steam hardware customers. Attackers accessed two Ceva systems processing Bol orders, potentially exposing names, addresses, phone numbers, email addresses and order details. Valve began notifying European Steam customers whose hardware shipping data may have been compromised and is contacting data protection authorities. Ceva, with about 110,000 employees and over 1,700 facilities, has not disclosed the attackers or whether ransomware was involved.

The Record·Aug 11, 15:49 UTC · Aug 11, 2026Data breach in the wild

LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metrics

LexFlip releases 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving tokens, exposing weaknesses in embedding-based meaning preservation metrics.

LexFlip provides 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving 0.93 of tokens, creating dissociation items that break monotone token-overlap metric validation. The seven embedding and BERTScore metrics tested register only 0.022-0.039 of their identical-to-unrelated range on these edits, versus 0.670 for bidirectional NLI. Against FrJudge, with a measured human ceiling of r=0.597, a bare length feature outscores every semantic metric tested.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 15:49 UTC · 12d agoAI research

CEVA Logistics Cyberattack Disrupts European Warehouses and Shipments

Cyberattack on CEVA Logistics disrupted eight European warehouses and exposed customer data of clients including Valve, Ajax, and De Bijenkorf.

CEVA Logistics, part of CMA CGM Group, suffered a July 29 cyberattack that disrupted eight European warehouses and halted shipments of stored goods. Customer data linked to Valve, Ajax, and Dutch retailer De Bijenkorf was exposed, potentially including names, contact details, and online order information; Valve said payment details and passwords were not accessed. No ransomware group has claimed responsibility and the company has not disclosed technical details. A database containing customer lists, shipping records, and banking details was reportedly later offered for sale on a dark web marketplace.

Security Affairs·Aug 12, 20:05 UTC · Aug 12, 2026Data breach 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

US data centers could consume more natural gas than Germany and Japan combined by 2035

BloombergNEF projects US data centers will consume about 18 billion cubic feet of natural gas daily by 2035, exceeding Germany and Japan combined.

A new BloombergNEF report forecasts US data centers will consume roughly 18 billion cubic feet of natural gas per day by 2035, nearly double the estimate from nine months ago. On-site gas plants planned by Meta, Microsoft, Google, and Amazon would use 2.9-3.4 billion cubic feet per day, while grid-connected data centers drive an additional 15 billion cubic feet per day of power-sector gas demand. The added demand would generate about 1 million metric tons of extra greenhouse gas pollution daily, roughly 12% of current US emissions.

TechCrunch · AI·Sep 15, 18:29 UTC · 1d agoAI industry

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·Sep 10, 17:43 UTC · 6d agoAI research

Inside ‘Project Lily’: The Humans Reading Your ChatGPT Chats

404 Media reveals OpenAI's 'Project Lily' has hundreds of contractors reading real ChatGPT user prompts, exposing sensitive personal data despite privacy filters.

404 Media reports that OpenAI employs hundreds of contractors who read real ChatGPT user prompts, including whole conversations, to rate and critique the chatbot's responses across a user base of over 900 million. Prompts are anonymized and run through OpenAI's Privacy Filter model, but the company acknowledged sensitive personal details can still reach reviewers, and 'user memories summaries' may reveal a user's location and personal context. The review work includes training ChatGPT to be less sycophantic and to stop anthropomorphizing itself, following lawsuits linking the sycophantic 4o model to multiple suicides. Anthropic confirmed it also uses human review to improve its models, and OpenAI's 'improve the model for everyone' data-sharing setting is on by default for free, Plus, and Pro users.

404 Media·Sep 14, 14:22 UTC · 2d agoAI safety & security

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

Slim Spider Steals Crypto Custody Secrets From Brazilian Financial Institution

CrowdStrike links previously unseen Slim Spider group to crypto custody secret theft at Brazilian financial institutions since March 2026.

CrowdStrike is tracking Slim Spider, a previously undocumented financially motivated group attacking Brazilian financial institutions since at least March 2026. The actor used custom Bash scripts to steal temporary cloud credentials, exfiltrated digital asset custody secrets, and used Foundry's cast tool to derive Ethereum wallet addresses, while deploying Go-based backdoor MikeDor and an implant impersonating Brazil's SPI instant payment infrastructure. Slim Spider also pivoted to Azure DevOps and Kubernetes clusters and used panels including NEXUS // Scanner, Painel de Emails Entra ID, and Painel Pix for reconnaissance and unauthorized Pix transfers. Separately, Google Threat Intelligence Group and Mandiant disclosed Breeze Comet (CL-CRI-1163), a Portuguese-speaking group since 2024 that breaches Brazilian payment infrastructure to run fraudulent Pix, Boleto, and STR transactions.

The Hacker News·Sep 8, 16:20 UTC · 8d agoThreat actor in the wild

H Company Releases NeoMME: A Family of 260M and 800M Single-Tower Multimodal Encoders That Drop the Vision Tower and Causal Decoder

H Company released NeoMME, 260M/800M single-tower multimodal encoders matching 3.75B ColQwen2.5 on ViDoRe v3 while being 14.4x smaller, under Apache 2.0.

H Company released NeoMME, a family of 262,937,906- and 793,715,032-parameter bidirectional encoders that process text and raw 32x32 image patches in a single tower, pretrained via masked diffusion and released under Apache 2.0 with day-zero Hugging Face Transformers support. NeoMME-Retriever-260M reaches 0.523 nDCG@10 on ViDoRe v3, matching 3.75B-parameter ColQwen2.5 while being 14.4x smaller; the 800M model scores 0.556. Hierarchical token pooling with int8 and binary quantization shrinks late-interaction indexes from roughly 1.5 MB to 6 kB per page while retaining 95.19% of nDCG@10; text-only BEIR retrieval remains a weak spot.

MarkTechPost·Sep 6, 21:06 UTC · 9d agoAI research

Top 10 Best Kubernetes Security Tools in 2026

Top 10 Kubernetes security tools roundup highlights Sysdig and Aqua as specialists plus strong free options Kubescape, Calico, and Falco.

A buying guide ranks ten Kubernetes security tools across admission control, network policy, runtime detection, and posture management. Sysdig leads runtime depth, Aqua leads full lifecycle, Red Hat ACS owns OpenShift estates, and Wiz offers agentless graph correlation. The guide notes this category has cloud security's strongest open-source floor with Kubescape, Calico, and Falco.

Cyber Security News·Sep 15, 06:41 UTC · 1d agoIndustry1

NeoMME: an efficient Multimodal-native and Multilingual Encoder

H Company released NeoMME, an efficient multimodal-native and multilingual encoder, via a post on the Hugging Face blog.

H Company published a Hugging Face blog post introducing NeoMME, described as an efficient multimodal-native and multilingual encoder. The article body was unavailable in the feed, so architecture, benchmarks, and licensing details could not be verified. The post suggests a new encoder release relevant to multilingual multimodal model development.

Hugging Face Blog·Sep 3, 13:13 UTC · 13d agoModel release

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

Discrete Beckmann Transport Models for One-Step Language Modeling and Reasoning

DBTM achieves one-step text generation via a time-independent transport map trained directly from data, removing pretrained teacher distillation.

Discrete Beckmann Transport Models (DBTM) build a time-independent flow whose autonomous transport map provably carries any point in ambient space to a fixed point on simplex vertices in a single step. The fixed-point property is characterized by a conservation equation whose residual can be minimized directly from data, eliminating the need for a teacher flow, distillation, and time conditioning. A partial-context interpolant extension turns additional function evaluations into refinement steps rather than ODE integration steps. On language modeling and reasoning tasks, DBTM's one- and few-step generation improves quality and accuracy over discrete diffusion and continuous flow baselines.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 17:19 UTC · 2d agoAI research1

AI labs have a data trust problem that their policies haven't solved

Nvidia, Palantir, and Booz Allen restrict Anthropic's Fable over data-retention distrust, exposing gaps in AI labs' customer data policies.

Nvidia limits Anthropic's Fable to non-sensitive work and runs its own Nemotron models for internal tasks, while Palantir blocks Fable deployment until Anthropic grants irrevocable zero-data-retention guarantees, and Booz Allen bans it for proprietary cybersecurity work. John Schulman and researcher Sarah Hooker explain that labs can still extract customer IP from metadata, user traces, and synthetic data even under zero data retention. The trust crisis crystallized around Tristan Buckmaster's accusation that OpenAI's Codex absorbed his Navier-Stokes drafts, though OpenAI later stated his prompts could not have influenced its model.

The Decoder·Sep 15, 17:52 UTC · 1d 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·Sep 7, 17:41 UTC · 9d agoAI research

Recorded FutureがGartner® サイバー脅威インテリジェンス・テクノロジー部門のMagic Quadrant™のリーダーの１社に位置づけられました。

Recorded Future·Aug 5, 00:00 UTC · Aug 5, 2026Phishing & fraud

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·Aug 25, 20:00 UTC · 21d agoAI research

AI Customer Service Bots Can Be Tricked Into Stealing Security Codes and Acting as Victims

DEF CON 34 research shows AI customer-service agents can be manipulated via prompt injection and email tricks to leak OTPs and act as victims.

Inti De Ceukelaire, presenting at Bug Bounty Village during DEF CON 34, demonstrated attacks against AI-powered customer service bots with access to customer profiles, billing data, support inboxes, and refund tools. Techniques include transcript-based phishing from trusted support addresses, From-header identity confusion, email normalization abuse to bypass OTP rate limits, and knowledge-base poisoning via RAG crawlers. He recommends separating untrusted content from system prompts, session-bound authentication, consistent email normalization, server-side tool validation, and least-privilege permissions for AI agents.

Cyber Security News·Sep 8, 08:50 UTC · 8d agoAI safety & security

Domain-Specific Hallucination Detection in Large Language Models

A multi-signal pipeline detects LLM hallucinations, reaching F1 0.915 on HaluEval and cutting Qwen2.5-0.5B hallucination rates from 85.5% to 37.7% via DPO.

The paper presents a hallucination detection pipeline combining fine-tuned DeBERTa-v3 classification, Monte Carlo Dropout uncertainty, and temperature-scaled calibration. It achieves F1 0.915 and AUROC 0.977 on general-domain HaluEval tasks, with MC Dropout inference raising accuracy to 93.2%. Applying DPO to a Qwen2.5-0.5B generator reduces its hallucination rate from 85.5% to 37.7%, while cross-domain evaluation shows poor general-domain transfer to SciFact (F1 0.52) and PubMedBERT fine-tuning as the strongest adaptation (F1 0.63).

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:45 UTC · 6d agoAI research1

Incident response statistics and cases at educational institutions in Brazil

Kaspersky Securelist·Aug 3, 13:00 UTC · Aug 3, 2026Ransomware

Debian developers rejected an LLM ban and left disclosure voluntary

Debian developers voted to encourage voluntary disclosure of AI assistance in contributions rather than banning or mandating labeling of LLM-generated code.

Debian's vote concluded August 28, with project secretary Kurt Roeckx announcing that the winning option encourages contributors to disclose generative AI assistance and stops there, adding no new mandatory review gates. The adopted resolution bars sending confidential material, embargoed security bugs, cryptographic keys and credentials to third-party AI services without explicit authorization, requires prior discussion for bulk automated work, and takes no position on whether model output is copyrightable. The project neither endorses nor prohibits generative AI and retains existing human review and licensing requirements.

Help Net Security·Aug 31, 00:00 UTC · 16d agoAI policy1

HVNC Backdoor Targets LATAM Organizations with Fake Tax and DocuSign Lures

A custom HVNC backdoor is targeting Latin American financial organizations via fake DocuSign and NFe tax-document lures, giving attackers hidden persistent remote access.

ANY.RUN researchers analyzed a multi-stage phishing campaign delivering a custom HVNC backdoor to banking and financial organizations in Latin America. The chain starts with fake DocuSign and NFe tax-document pages that serve per-visitor ZIP archives, followed by an LNK dropper, an NSIS loader, and a 64-bit backdoor masquerading as Windows Update Assistant. The implant provides hidden remote desktop control, keystroke monitoring, Firefox data theft, Startup-folder persistence, and EDR-aware behavior, communicating over TCP/27015.

ANY.RUN·Sep 8, 10:24 UTC · 8d agoMalware in the wild

OpenVDN/vdn-minimax-h3 — new model trending #12 on Hugging Face

OpenVDN releases VDN-H3, an open hybrid-attention video model on MiniMax H3 that renders a 14.4-second 768p clip in 11.23 seconds on 8 B200 GPUs.

VDN-Minimax-H3 (VDN-H3) adds a frame-wise linear attention branch plus two LoRA adapters to MiniMax H3, distilled into 8-step and 50-step variants. It generates 768p, 14.4-second clips in 11.23 seconds on 8 B200 GPUs (90.5 seconds on one H200) using 8 denoising steps. Weights (about 82 GB total, including the 72 GB H3 base), the optimized inference stack, and training code are fully open-source under the MiniMax H3 Community License, which excludes the EU, UK, Korea, and US.

Hugging Face trending models·Sep 2, 05:03 UTC · 14d agoModel release1

Why metaphor may dictate your security strategy

Cisco Talos·Aug 6, 18:00 UTC · Aug 6, 2026Vulnerability1

Beneath the Surface of Chains-of-Thought: A Mechanistic Interpretation of Reasoning Operations in LLMs

Study shows LLM reasoning operations like planning and deduction are geometrically separable in hidden states, with separability peaking in middle layers.

Researchers investigate whether functional reasoning operations — problem formulation, goal decomposition, deduction — have corresponding geometric structure in LLM hidden representations. They find operations are separable in held-out representations with separability peaking in middle layers, ruling out lexical and positional confounds; token-wise operation alignment becomes more distributed across layers, and identical surface tokens are represented differently depending on their surrounding chunk. Attention-masking interventions show chunk-onset operation-aligned representations depend on preceding reasoning context; code is released on GitHub (naver-ai/beneath-cot).

Hugging Face daily papers·Sep 3, 20:00 UTC · 12d agoAI research1

Security Affairs newsletter Round 594 by Pierluigi Paganini – INTERNATIONAL EDITION

Weekly Security Affairs newsletter aggregates top stories including Cisco FMC exploitation, Qilin ransomware, Chrome zero-days, and Berlin leak.

Pierluigi Paganini's Security Affairs newsletter Round 594 (International Edition) rounds up the week's security headlines. Topics include attackers exploiting a critical Cisco FMC flaw to deploy Qilin ransomware, SonicWall mass exploitation linked to a UK council attack, multiple CISA KEV additions, Chrome zero-days used by four nation-state actors, a $320 million Liquid Network theft, and a Berlin ransomware data leak. It also covers AI security items such as agent sandbox failures and distillation campaigns by Chinese AI firms.

Security Affairs·Sep 13, 14:23 UTC · 3d agoIndustry in the wildCVE-2026-42016CVE-2026-42018CVE-2026-82329+1 CVEs1

Safety for Whom? Boundary-Aware Self-Distillation for Controlled LLM Safety Refusal

A self-distillation safety framework tunes narrow-boundary refusals in Qwen3-8B, raising target-domain refusal to 84.75% while cutting over-refusal from 15.20% to 5.20%.

The paper formulates narrow-boundary safety, where deployments need refusals within specific topics rather than whole subjects, and proposes an offline self-generated framework with controlled topic generation, escalating retries, and harmful-benign boundary pairs. On political persuasion with Qwen3-8B, the method raised target-domain refusal from 9.47% to 84.75% and cut the mean unsafe-response rate across three broader benchmarks from 26.26% to 0.14%. Verified target-model responses reduced over-refusal from 15.20% to 5.20%, and boundary-pair data cut comply-side over-refusal on held-out pairs from 32.94% to 4.16%. Results show data composition controls the safety-usability trade-off and alignment should be evaluated on both sides of the refusal boundary.

Hugging Face daily papers·Sep 2, 20:00 UTC · 13d agoAI safety & security1

OpenAI's millennium proof dispute raises the question of whether researchers can trust AI labs

Mathematician Tristan Buckmaster accused OpenAI of pressuring him and possibly training on his drafts amid OpenAI's race to claim a Navier-Stokes millennium proof.

OpenAI published a blog post and Sam Altman defended the team behind its AI-generated proof of the Navier-Stokes Millennium Problem after mathematician Tristan Buckmaster accused the company of academic misconduct. Buckmaster and co-author Levent Alpöge, who works at Anthropic, allege OpenAI pressured Buckmaster, sidelined Alpöge, and may have trained on drafts they entered into OpenAI's systems. OpenAI acknowledges it cannot rule out that de-identified data from their product usage helped improve its models. Mathematician Terence Tao warned the episode could discourage researchers from sharing work, reversing centuries of open science.

The Decoder·Sep 9, 10:27 UTC · 7d agoAI industry1

VDiff-Bench: A Challenging Benchmark for Fine-Grained Image Difference Identification

VDiff-Bench, a 1,756-question benchmark, shows multimodal LLMs struggle with fine-grained image-difference identification, scoring as low as 8.7% on low-level changes.

VDiff-Bench is a multiple-choice benchmark of 1,756 four-way questions over image pairs covering 10 change categories including position, motion, color, texture, OCR/text and illumination, with curated hard negatives. Evaluation of 11 state-of-the-art open- and closed-source MLLMs shows fine-grained visual comparison remains brittle: 7-8B-scale open-source models score 52.5-70.6% on semantic changes but only 8.7-33.3% on low-level changes like noise and texture. Notably, Grok 4.3 shows a sharp performance drop on noise and texture differences, falling behind large open-source models like Kimi K2.5 and K3.

Hugging Face daily papers·Sep 4, 20:00 UTC · 11d agoAI research

Srsly Risky Biz: America's Drivers Licence Breach is a National Security Disaster

Dark web service Nexus sold 153 million US and Canadian driver's licenses, linked to identity verification firm IDScan under FBI investigation.

Krebs On Security reported that a dark web service called Nexus sold access to 153 million US and Canadian driver's licenses, claiming over a year of continuous exfiltration from a major identity verification company, with roughly 400,000 new licences added in a single day. Krebs verified the data as genuine and linked the incident via circumstantial evidence to identity verification firm IDScan, whose licences of senior US officials including Secretary of War Pete Hegseth appeared in the database; the FBI is investigating and IDScan has confirmed a breach inquiry. The article argues the data has national security implications, citing how Chinese APT espionage (Anthem, Equifax, Marriott, OPM) and Bellingcat investigations exploited leaked databases. Class action suits are being prepared, and the piece calls for stricter oversight of identity verification firms.

Risky Business News·Sep 10, 03:32 UTC · 6d agoData breach in the wild

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·Aug 28, 20:00 UTC · 18d agoAI research

Seemplicity Response Options accelerates vulnerability mitigation

Seemplicity launched Response Options, giving vulnerability teams compensating controls and targeted changes instead of waiting on full remediation cycles.

Response Options presents multiple remediation paths per vulnerability finding, including compensating controls and targeted configuration changes alongside full patches. Each option carries a Readiness Indicator showing whether it can deploy immediately or needs review, while AI Analysts pre-select a recommended option with visible reasoning. The capability is available now to all Seeplicity customers and targets shrinking the time from disclosure to exploitation.

Help Net Security·Sep 3, 00:00 UTC · 13d agoTools

Competence-Gated Pooling of Language Models and Priors for Event Forecasting

Paper proposes a competence gate pooling language model forecasts with external priors, improving Brier score from 0.0771 to 0.0732 across 2,357 binary questions.

The paper defines a language model's relative competence as its marginal value beyond an available external forecast, and derives conditions under Brier loss where model disagreement improves that forecast. A competence gate estimates domain-level source weights from resolved outcomes, shrinks uncertain estimates toward a global weight, and recalibrates the pooled forecast. Across 2,357 resolved binary questions and five language models, it improves the external baseline from 0.0771 to 0.0732 Brier and beats global forecast combinations, though it defers to the market on ForecastBench. Across four Qwen models, verbal confidence failed to identify when the model outperformed the external forecast, while outcome-estimated competence supported better abstention.

Hugging Face daily papers·Sep 9, 20:00 UTC · 6d agoAI research

The Roboguard Revolution is Short

404 Media·Aug 10, 13:04 UTC · Aug 10, 2026Industry

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