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Apple Updates Everything, (Mon, Sep 14th)

Apple patched a record 261 vulnerabilities across iOS 27, macOS Golden Gate 27, watchOS 27, and other platforms, with none flagged as exploited.

Apple's annual OS update shipped iOS/iPadOS 27, macOS Golden Gate 27, tvOS 27, watchOS 27, and visionOS 27 plus bug-fix releases for the 26 and 15 branches, fixing a record 261 vulnerabilities. Notable issues include multiple kernel flaws allowing root privilege escalation (CVE-2026-43689, CVE-2026-43691, CVE-2026-43698, CVE-2026-43786), remote code execution in CUPS (CVE-2026-43692), kernel memory corruption via malicious NFS servers (CVE-2026-43686, CVE-2026-43687), and WebKit memory corruption from crafted web content (CVE-2026-43715). No vulnerabilities are labeled as actively exploited, and Apple does not assign per-CVE severities. Users report iOS 26.7 being downloaded when iOS 27 is intended, and tools like Little Snitch and BlockBlock need updates before upgrading to macOS 27.

SANS Internet Storm Center · 1d agoVulnerabilityCVE-2022-3437CVE-2026-20683CVE-2026-28899+27 CVEs

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 · 9d agoAI research

NOKKI Almost Ties the Knot with DOGCALL: Reaper Group Uses New Malware to Deploy RAT

Unit 42 links NOKKI malware to North Korea's Reaper group, uncovering the Final1stspy dropper that deploys the DOGCALL RAT in politically motivated attacks.

Unit 42 analyzed the NOKKI malware family used in politically themed attacks against Russian and Cambodian speakers since July 2018. The researchers linked NOKKI to the Reaper group, publicly attributed to North Korea, whose custom DOGCALL RAT uses third-party hosting services to upload data and receive commands. A previously unreported family, Final1stspy, was found deploying DOGCALL, sharing a unique base64-to-hex deobfuscation routine with NOKKI droppers. Attacks used malicious Microsoft Word macros that download and execute payloads while opening decoy documents.

Palo Alto Unit 42 · 29d agoMalware

Safety for Whom? Refusing the Right Subset of a Topic, Not the Whole Topic

Multiverse Computing's Hugging Face post argues language models should refuse only the relevant subset of a topic instead of over-refusing whole subjects.

A Hugging Face blog post by Multiverse Computing examines refusal granularity in language models, arguing models should refuse the relevant subset of a topic rather than the entire topic. No full article text was available for additional technical detail.

Hugging Face Blog · 7d agoAI safety & security

The vulnpocalypse rains iBugs down on Apple with record-setting number of patches

Apple's record patch cycle fixes 260+ CVEs across iOS 27 and macOS 27, including CUPS remote code execution, with no active exploitation reported.

Apple patched more than 260 CVEs across its operating systems and software, its largest single patch cycle ever, with iOS 27 fixing 122 flaws and macOS 27 Golden Gate fixing 204. Notable bugs include CVE-2026-43692, a CUPS validation issue allowing remote code execution, and CVE-2026-43689, an iOS privilege-escalation flaw granting root access. Ten CVEs were credited to AI-assisted bug hunting, including CVE-2026-65410 and CVE-2026-65409 found by Calif with Claude and Anthropic Research. None of the vulnerabilities are listed as actively exploited.

The Register · Security · 13h agoVulnerabilityCVE-2026-65410CVE-2026-65409CVE-2026-43689+10 CVEs

What We Learned by Reproducing 2,200 papers from ICML

Hugging Face shares lessons from openly reproducing 2,200 ICML 2026 papers, examining reproducibility and open implementation practices in machine learning research.

Hugging Face published a retrospective on its open reproduction effort covering 2,200 papers from ICML 2026. The post summarizes lessons learned about reproducibility and building open, community-driven implementations of published machine learning research. No detailed article text was available in the feed.

Hugging Face Blog · Aug 13, 2026AI research

With iOS 27, I’m actually using Siri again

Apple's rebuilt Siri, powered by Google Gemini models in iOS 27, finally handles complex multi-step and on-screen-context requests, per TechCrunch review.

Apple's iOS 27 ships a redesigned Siri built on Google's Gemini models, supporting multi-step instructions, on-screen context, file/message/email lookups, and camera viewfinder queries. Siri AI gets a dedicated app with chat history, plus settings for voice and expressiveness. Apple Intelligence also adds natural-language Shortcuts creation and automatic password rotation in the Passwords app.

TechCrunch · AI · 1d agoAI industry

Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

Hugging Face published a tutorial on training and finetuning multi-vector embedding models using the Sentence Transformers library.

Hugging Face's blog walks through training and finetuning multi-vector embedding models with Sentence Transformers. Multi-vector approaches store multiple vectors per document to support late-interaction retrieval. The post is a practical guide for developers building retrieval pipelines with the library.

Hugging Face Blog · 21d agoAI tools & infra1

Apple Rolls Out Massive Security Update Fixing 273 Vulnerabilities Across Its Devices

Apple's coordinated rollout patches 273 unique vulnerabilities across iOS 27, macOS Golden Gate 27, watchOS and Safari, including remote code execution flaws.

Apple shipped one of its largest coordinated security updates on September 14, 2026, fixing 273 unique CVEs across iOS 27, iPadOS 27, macOS Golden Gate 27, watchOS 27, tvOS 27, visionOS 27, Safari 27 and Xcode 27. Highlights include CVE-2026-65414, a Bluetooth out-of-bounds write enabling remote code execution, and CVE-2026-84607, an AVEVideoEncoder race condition granting kernel privileges to sandboxed apps. macOS Golden Gate 27 covers the broadest set with 210 CVEs, and Apple states none of the flaws were exploited in the wild.

Cyber Security News · 19h agoVulnerabilityCVE-2026-65414CVE-2026-84607CVE-2026-64752+7 CVEs1

Meta Patents AI Glasses to Use Facial Recognition to Identify People, Make Highlight Reels of Your Dinner Party

Meta filed a patent for AI glasses that identify people via facial recognition and auto-generate highlight reels of events like dinner parties.

A newly published Meta patent describes smartglasses that use facial recognition to detect people in frame, capture video clips of their actions, and compile highlight reels. The filing signals Meta's continued, controversial push to combine facial recognition with its AI glasses line. The patent was published Thursday and offers granular detail on Meta's product plans, though it does not confirm a shipping feature.

404 Media · Aug 14, 2026AI industry

Exclusive: NSA to host a hacker reunion in bid to rebuild secretive unit

NSA will host a reunion of former Tailored Access Operations hackers as it moves to rebuild and rebrand the elite unit.

The invitation-only event at Fort Meade, spearheaded by Deputy Director Tim Kosiba, a former TAO technical director, will tour the new TAO building and pitch alumni to return. TAO, credited with contributions to Stuxnet and once grown to over 2,000 personnel, was renamed Computer Network Operations about a decade ago, and the recent reshuffle undid some of those changes after NSA lost roughly 2,100 staff (8% of its workforce) last year.

The Record · 20d agoIndustry

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face Blog · 29d agoAI tools & infra1

Risky Bulletin: Dutch intel services to get extensive new powers

Netherlands proposed a bill granting AIVD and MIVD expanded warrantless tapping, faster hacking powers, and forced data disclosure, citing Russia, China, and Iran threats.

The Dutch government introduced a bill greatly expanding surveillance powers of intelligence agencies AIVD and MIVD, allowing up to one year of tapping without pre-approval and simplified hacking operations against 'foreign adversaries'. Agencies could compel Dutch companies or citizens to provide data under threat of charges, share data with the private sector, and oversight bodies would merge into a new CTT board. The bill follows similar overhauls in Ireland, Germany, and France after Russia's invasion of Ukraine. The newsletter also reports Moonwell hacked for $8.7M, a Cosmos EVM bug exploited for ~$3M, ShinyHunters listing McKesson with claimed hundreds of millions of records, and a pro-Kremlin DDoS claim against Norway's government network.

Risky Business News · 16d agoPolicy & legal

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

Study finds zero-shot time-series foundation models underperform on CGM forecasting; fine-tuned Chronos-Bolt cuts RMSE up to 18.4% and dietary context adds signal.

The paper evaluates time-series foundation models for continuous glucose monitoring forecasting across eight public datasets covering Type 1 diabetes, Type 2 diabetes, and non-diabetes populations. Under a unified protocol, zero-shot foundation models did not consistently outperform baselines like Elastic Net and PatchTST, but lightweight fine-tuning did, with fine-tuned Chronos-Bolt reducing RMSE by 6.5%-18.4% in the T1D cohort and 8.6%-18.2% in the non-diabetes/T2D cohort. A residual-based fusion framework adding dietary context from CGMacros reduced overall RMSE by about 3% and postprandial RMSE by about 15% versus CGM-only baselines.

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

Group of bipartisan lawmakers ask US government to ban several hack-for-hire firms

Bipartisan US lawmakers urged the Commerce Department to add hack-for-hire firms BellTroX, CyberRoot, and Appin/Sunkissed Organic Farms to the entity list.

Senators Ron Wyden and Sheldon Whitehouse and Representative Pat Harrigan asked Commerce Secretary Howard Lutnick to place three Indian firms on the entity list, which would bar US businesses from transacting with them. The letter says BellTroX, CyberRoot, and Sunkissed Organic Farms (formerly Appin) have conducted cyberattacks and targeted espionage against Americans for over a decade, allegedly at the behest of the Qatari government, and used foreign courts to censor reporting on their activities. Appin previously secured a global takedown order against Reuters that was later lifted, and has been linked to hacks of FIFA officials tied to Qatar's 2022 World Cup plans.

TechCrunch · Securityupdated · 5d agofirst · 6d agoPolicy & legal 3 sources1

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 · 7d agoAI research

Risky Bulletin: Russia tells data centers to deploy drone defenses

Russia ordered data center operators to deploy drone strike defenses under a Putin decree allowing temporary state takeover of unprotected critical infrastructure.

The Russian government instructed data center operators to deploy protections against drone strikes under a presidential decree signed by Putin that allows temporary state administration of critical infrastructure operators failing to defend against Ukrainian hacks and drone strikes. Although data centers are not formally critical infrastructure in Russia, the decree applies to them because other sectors depend heavily on cloud services; Russia has more than 180 data centers, over 80% in the European region within range of Ukrainian strikes. The digest also reports a Dropbox breach affecting nearly 5,000 accounts via the Lenovo ID integration, spyware attacks on at least 14 Serbians using NoviSpy or Pegasus, and a password recovery attack targeting hundreds of thousands of X accounts tied to the new X Money service. Other items include a 14-hour compromise of Coder's Cloudflare infrastructure delivering malicious Terraform modules, donor data breaches at Davayte and You Are Not Alone via the Stripe/WooCommerce integration, a $2.5M Aquifer crypto heist, and a TVING breach exposing data of almost 40 million accounts.

Risky Business News · 12d agoPolicy & legal

Studying Image Tokenizers as Visual Languages in Unified Multimodal Models

A controlled pure-autoregressive testbed shows task-specific validation losses rank image tokenizers differently, with I2T loss the most consistent signal.

Researchers built a controlled pure-autoregressive testbed and tracked task-specific validation losses during multimodal continual pretraining across text, image, text-to-image (T2I), and image-to-text (I2T) prediction. They find losses should be analyzed per task because they exhibit distinct scaling behavior and rank tokenizers differently, and that the loss-performance relationship depends on the predicted token space. I2T loss, computed over a shared text vocabulary, correlates consistently with both generation and visual understanding performance after supervised finetuning. Case studies revisit the discriminator, semantic supervision, and vocabulary size as tokenizer design axes.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

DavidAU/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NEO-CODER-MAX-MTP-GGUF — new model trending #8 on Hugging Face

A new Qwen3.8-27B GGUF fine-tune claims ARC-C 735 at 8-bit with thinking tokens cut 2x-10x versus the base model.

Independent creator DavidAU released a GGUF fine-tune of Qwen3.8-27B built with Unsloth, claiming ARC-C of 735 at 8-bit and 719 at 4-bit, trending #8 on Hugging Face. The 'TURBO' variant cuts thinking tokens by one half to as much as one tenth while retaining output quality and detail. The repo ships both regular and MTP quants and claims gains over the base model across seven benchmarks, using 'Cold Fusion (GAIN + Unsloth)' and 'Fable Fusion 711' training methods.

Hugging Face trending models · 15d agoModel release

Target leakage, not model class, explains reported accuracy in survey-based cardiovascular screening: a leakage-tiered audit of glass-box and tabular foundation models

Audits of 10 classifiers on BRFSS show target leakage, not model class, drives the reported 0.89 AUROC in survey-based cardiovascular screening.

The study benchmarks ten model classes, including glass-box and tabular foundation models, for prevalent myocardial infarction on 442,067 respondents of the 2022 BRFSS across five feature tiers of decreasing leakage risk. Removing two post-diagnostic features costs every model 0.049-0.051 AUROC and collapses performance into a 0.0045-wide band, and the explainable boosting machine matches all alternatives within 0.005 while scoring roughly 104x faster than the strongest foundation model. Frozen models transport within 0.002 AUROC to 2023 data; the authors conclude evaluation practice and feature sets, not model capacity, are the binding constraint.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research1

Nums AI Releases Causilo: A Tabular Foundation Model That Tops TabArena Among Single Models

Nums AI released Causilo, an Apache-2.0 tabular foundation model achieving the highest single-model Elo (1794) on TabArena for classification and regression.

Nums AI released Causilo 1.0.1, a pretrained in-context learning tabular foundation model for classification (up to 10 classes) and regression, with Apache-2.0 code and research-only weights on Hugging Face. It achieved the highest single-model TabArena Elo of 1792.9 overall, beating TabFM (1764.4) and EXAONE Tabular (1758.8), and a maintainer re-run placed it 3rd of 88 including system entries. It also ranked first by CRPS, R² and RMSE on ScoringBench across 101 datasets, and was fastest on fit and predict versus TabICLv2 and TabPFN-3 on an H100 GPU at 8.15 GiB memory. The model was pretrained only on synthetic data, uses cross-attention to keep cost linear in feature count, and version 1.0.1 adds quantile outputs via 999 native quantiles.

MarkTechPost · 5h agoModel release

Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models

Researchers introduce KoNA, a benchmark exposing vision-language models' failures at selective non-compliance, plus fine-tuning that improves refusal and abstention accuracy.

KoNA is a benchmark for evaluating selective non-compliance in vision-language models across five categories: False Premise, Visual Inaccessibility, Universal Unknown, Task Feasibility and Safety. It tests both query-level and component-level non-compliance using paired single and compound queries, and evaluations across diverse VLMs show models often fail to refuse, correct or abstain appropriately, with failures worsening on compound queries. Fine-tuning VLMs on KoNA examples substantially improves non-compliance accuracy while largely maintaining performance on fully answerable tasks.

Hugging Face daily papers · 12d agoAI research1

Studying Image Tokenizers as Visual Languages in Unified Multimodal Models

A controlled autoregressive testbed shows validation losses must be analyzed per task, and image tokenizer choice affects joint multimodal text modeling.

Researchers built a pure-autoregressive testbed to study image tokenizers as the 'visual language' of unified multimodal models, tracking task-specific validation losses during multimodal continual pretraining across text, image, text-to-image (T2I), and image-to-text (I2T) prediction. They found that losses exhibit distinct scaling behavior per task and rank tokenizers differently, and that I2T loss over a shared text vocabulary gives a more consistent loss–performance signal than T2I loss. Better reconstruction does not necessarily yield lower task-specific losses or stronger downstream performance, and tokenizer choice can affect text modeling under joint optimization. Case studies examine the discriminator, semantic supervision, and vocabulary size design axes.

Hugging Face daily papers · 8d agoAI research1

SNAP3D: Physically Grounded 3D Parts for Assembly from a Single Image

SNAP3D uses physics simulation feedback to make single-image 3D part generation produce valid, stable assemblies, validated through 3D printing.

The framework improves part-aware 3D generation by resolving inter-part penetration, recovering contact graphs between neighboring parts, and placing parameterized connectors at contact surfaces. Physical simulation feedback refines connector placement, orientation, and dimensions to improve assembly stability while preserving geometry. A physics-based evaluation protocol tests assembly validity and stability under gravity, and results are validated through 3D printing and real-world assembly.

Hugging Face daily papers · 5d agoAI research

CoVeR: Coverage-Based Token Pruning for Multi-View 3D Reasoning in VLMs

CoVeR, a training-free coverage-based token pruner, preserves 93.5% of VLM 3D-reasoning performance using only about 8% of visual tokens.

Researchers introduce CoVeR, a deterministic, training-free selector that chooses visual tokens to cover every region of a multi-view 3D scene using only token coordinates. Unlike learned-importance and voxelization pruners, it enforces an exact per-scene token budget, avoids saturation plateaus, and prevents near-duplicate selections. Experiments across four vision-language models show it surpasses prior state of the art by 3.9 percentage points on average across three 3D reasoning benchmarks.

Hugging Face daily papers · 8d agoAI research

Cross-Model Agreement as a Deployment-Time Reliability Signal for Automatic Polyp Segmentation

Referee-Based Quality Estimation flags unreliable polyp segmentations at inference without ground truth, reaching ROC-AUC 0.960 with SegFormer-B0 referees.

RBQE measures agreement between a primary segmentation model and an independently trained referee on a 1,223-image external benchmark drawn from four public datasets. A cross-architecture SegFormer-B0 referee achieves the strongest signal (ROC-AUC 0.960), beating a Test-Time Augmentation baseline by 0.055 ROC-AUC under an identical protocol. Excluding trivially separable empty-mask cases, ROC-AUC falls to 0.876 (SegFormer-B0) and 0.783 (same-architecture control), but RBQE's margin over baselines widens. Progressive rejection of low-agreement predictions increases mean Dice of retained outputs, supporting selective prediction at the cost of one extra forward pass.

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

Training a coding model to paint watercolours with TRL and OpenEnv

Hugging Face tutorial trains a coding model with TRL and OpenEnv to paint watercolours through generated code.

A Hugging Face blog walkthrough uses the TRL reinforcement learning library and the OpenEnv environment framework to train a coding model. The target task is generating code that produces watercolour-style drawings, serving as a hands-on reinforcement learning training example. No article body was available in the feed, so specifics are limited to the title.

Hugging Face Blog · 13d agoAI tools & infra1

AlayaVista: Streaming World Modeling from Panoramic States to Perspective Video

AlayaVista is a camera-controllable streaming video world model that decouples panoramic scene evolution from perspective synthesis, trained on a 1,318-hour 4K dataset.

AlayaVista builds a 360-degree scene prior from a single perspective image, evolves it as a camera-conditioned panoramic latent state, and maps it to perspective video via a latent viewport renderer plus a perspective refiner. Chunk-autoregressive generation and few-step distillation enable efficient streaming. The authors introduce MUGEN, a real-world panoramic video dataset with 1,318 hours of at-least-4K video and rich semantic and geometric annotations.

Hugging Face daily papers · 3d agoAI research

microsoft/VibeVoice-ASR-Streaming-7B — new model trending #27 on Hugging Face

Microsoft released VibeVoice-ASR-Streaming-7B, an open streaming ASR model with speaker attribution, custom hotwords, and support for 10 languages under MIT license.

Microsoft Research released VibeVoice-ASR-Streaming-7B on Hugging Face, a unified streaming speech recognition model that continuously transcribes who said what as speech arrives. The 7B model supports customized hotwords for domain-specific terms and 10 languages including Chinese, English, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish. Code is available at github.com/microsoft/VibeVoice with a live demo, and a technical report is on arXiv (2609.02812). The model is licensed under MIT.

Hugging Face trending models · 13d agoModel release1

Same Cluster, 33 Points More Utilization: What Changed Was the Order

A Dharma AI blog post on Hugging Face claims GPU cluster utilization rose 33 points after changing job ordering.

A community blog post published on Hugging Face, part of a GPU management series by Dharma AI, discusses improving utilization on the same GPU cluster. According to the title, reordering jobs or tasks was the change that produced roughly 33 additional points of utilization. No article body was available for further detail.

Hugging Face Blog · 29d agoAI tools & infra

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 · 13d 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 · 11d agoAI research

XHToken/Spark-X2.5-4B-GGUF — new model trending #30 on Hugging Face

XHToken released GGUF weights of Spark-X2.5-4B, a compact model with 1M-token context and 200+ language support, under Apache 2.0.

The Hugging Face repository provides BF16 GGUF conversions of Spark-X2.5-4B, a compact general-purpose language model for conversation, writing, translation, reasoning, coding, tool use, and agentic workflows. The model uses a hybrid attention architecture, supports a native context length up to 1M tokens, and covers more than 200 languages. Local inference is supported through Ollama and LM Studio via an XHToken llama.cpp fork, with a --think=false flag to disable thinking mode for faster responses. Released under Apache License 2.0; it was trending #30 on Hugging Face at publication.

Hugging Face trending models · 18d agoModel release

CanvasAnneal: Curriculum Reinforcement Learning for Diffusion Language Models

CanvasAnneal injects teacher reasoning traces into diffusion canvases during curriculum RL, improving diffusion LLMs on MATH500, Countdown, and Tau2.

CanvasAnneal is a curriculum-guided reinforcement learning framework for diffusion language models that addresses exploration bottlenecks in standard RL. It warm-starts exploration by injecting teacher-generated reasoning traces into the initial diffusion canvas, then gradually removes this guidance so the model generates reasoning trajectories independently. Across mathematical reasoning and tool-use benchmarks, it improves over standard diffu-GRPO on MATH500, Countdown, and Tau2 and accelerates reward improvement, though gains are task-dependent.

arXiv cs.AI / cs.LG / cs.CL · 4d agoAI research1

Diffusion TV: Experiencing Diffusion Models through Tangible, Embodied Interaction

Researchers present Diffusion TV, a CRT-based installation where antenna manipulation lets audiences physically experience diffusion model denoising.

Diffusion TV is an interactive installation built around a modified CRT television where turning the antenna controls the clarity of AI-generated images and sounds, mirroring the denoising process of diffusion models. Three channels present AI-generated animals from the past, present, and future within a temporal and ecological narrative. The authors frame the work as an embodied, non-verbal alternative to explainable AI that highlights intermediate generative states rather than final outputs.

arXiv cs.AI / cs.LG / cs.CL · 11d agoAI research

Researchers Show How Meta's 'Pervert Glasses' Are Used to Harass Women

University of Sydney researchers detail how pickup artists use Meta Ray-Ban smart glasses to covertly film and harass women, then post the videos on Instagram.

Researchers Joanne Gray, Milica Stilinovic, Marcus Carter, and Ben Egliston analyzed 350 Instagram videos posted between September 2023 and March 2026 showing unsolicited approaches to women filmed with smart glasses. They found a clear correlation between covert filming and harassment severity, arguing ambient capture creates 'borderline' harassment that evades platform moderation mechanisms. Instagram head Adam Mosseri said the platform would remove harassing pickup-line content, though similar videos remain widespread a month later. Meta's safeguards, such as the recording light, were previously criticized as insufficient, and users have modded glasses to disable the light.

404 Media · Aug 12, 2026AI safety & security

Making Knowledge Distillation Cheap Enough to Run at Scale

Hugging Face blog by Multiverse Computing describes techniques making knowledge distillation cheap enough for large-scale training.

A Hugging Face blog post from Multiverse Computing (CAI) presents methods for reducing the cost of knowledge distillation so it can be run at scale. The post is aimed at practitioners compressing large models into smaller, cheaper ones for production use.

Hugging Face Blog · Aug 10, 2026AI research