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Cisco Identity Services Engine Cross-Site Scripting Vulnerability

Cisco patched a reflected XSS in the ISE management interface allowing unauthenticated attackers to execute script via crafted links.

A reflected cross-site scripting vulnerability in the web-based management interface of Cisco Identity Services Engine lets an unauthenticated remote attacker execute arbitrary script in the context of the interface. Exploitation requires persuading a user to click a crafted link due to improper input validation. Cisco has released software updates.

Cisco Security Advisories · 3h agoAdvisory 15 sources

Reflection-aware Generative Novel View Synthesis

Ref-GeNVS is a training-free method for reflection-consistent generative novel view synthesis that treats mirror images as two complementary views.

An arXiv paper proposes Ref-GeNVS, a training-free approach to generative novel view synthesis in scenes containing mirrors. It estimates the mirror plane, reflects camera poses to create virtual views, and applies mirror-gated attention plus reflection injection within a multi-view diffusion model. On synthetic and real mirror scenes, Ref-GeNVS outperforms recent generative NVS methods while requiring no fine-tuning.

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

[AINews] GPT-6 Astra: OpenAI’s biggest LLM launch of all time

OpenAI launched GPT-6 Astra, its new flagship model, claiming state-of-the-art computer use, software engineering, math, and cybersecurity capabilities.

OpenAI launched GPT-6 Astra as its new flagship model, describing it as its most intelligent and aligned model with state-of-the-art computer use, software engineering, and math/science capabilities. Pricing is $10/$50 per 1M input/output tokens standard ($20/$100 fast tier), rolling out first to limited organizations, then ChatGPT Plus/Pro/Business/Enterprise, the API, and AWS. OpenAI claims 99.9% on ARC-AGI-3, 98% on FrontierMath Tier 4, and 100% on ExploitBench. Artificial Analysis scored Astra 67 on the Coding Agent Index and 61 on the Intelligence Index, behind Claude Fable 5.1, and the system card drew attention for reporting decreased chain-of-thought monitorability despite alignment gains.

Latent Space · 12d agoModel release3

Thought without systematicity? Evaluating reasoning models on rule induction tasks

Study finds reasoning models often fail on structurally equivalent variants of tasks they solve, suggesting their reasoning lacks systematicity.

The paper extends rule induction tasks from cognitive science using task isomorphisms such as recombination and substitution to test systematicity in reasoning models. Despite solving tasks correctly, models frequently fail on structurally equivalent variants of the same task. The authors conclude many model behaviors lack systematicity, making it difficult to establish cognitive abilities beyond the specific evaluation contexts.

Hugging Face daily papers · 4d agoAI research

[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

DeepSeek released V4.1-Flash, an open-weight 763B-parameter model with a novel causal encoder-decoder architecture, 1M context, vision input, and MIT license.

DeepSeek launched V4.1-Flash, an open-weight MIT-licensed model using a novel causal encoder-decoder architecture with 763B total parameters and asymmetric active parameters: 8B for prefill and 16B for decode. It supports 1M-token context and text+image input, priced at $0.30 per 1M input and $1.20 per 1M output tokens with a 50% off-peak discount. Artificial Analysis scored it 40 on its Intelligence Index, above DeepSeek V4 Pro 0813, and Vals ranked it the #1 open-weight model ahead of Kimi K3. Baseten shipped day-0 support and Ollama began rolling it out to paid subscribers.

Latent Space · 4d agoModel release 4 sources1

What Matters, When? Diagnosing and Improving Conditional Visual Grounding in Visuomotor Imitation Policies

Researchers diagnose conditional visual grounding failures in visuomotor imitation policies and show targeted interventions substantially improve distractor robustness.

The paper studies why ACT-based visuomotor imitation policies fail when visually similar distractor objects or receptacles are introduced, finding sensitivity depends on both distractor type and manipulation stage. Interventions including distractor augmentation, phase-dependent attention regularization, and appearance-based visual prompting improve target selection while preserving spatial control information, with gains in simulation and on a physical UR3e. The same failure pattern is confirmed in a pretrained vision-language-action policy on a state-conditioned medical instrument-handling task.

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

Re: AI slops from Eve

oss-security commenter argues AI models remain human-built algorithms while reflecting on recent AI-slop incidents in open-source

A reply posted on the oss-security mailing list reflects on recent AI-generated slop incidents, arguing that AI models are still human-developed algorithms running on human-built hardware. The post is personal commentary and contains no CVEs, advisories, or concrete incidents.

oss-securityupdated · 3d agofirst · 5d agoIndustry 12 sources1

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

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

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

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

FBI officials say AI is bolstering adversaries, emphasizing need to focus on cyber basics, patching

FBI officials said AI is accelerating adversary capabilities while its new cyber strategy emphasizes continuous patching, cyber hygiene, and AI-enabled defense.

At the Billington CyberSecurity Summit and ahead of a new FBI cyber strategy, deputy assistant director Jason Bilnoski said AI is boosting the speed and capability of both criminal and nation-state attackers, while stressing that basic controls like MFA would still prevent most attacks. Colleen Ferranti urged a shift from quarterly Patch Tuesday cycles to continuous, risk-based patching as AI accelerates vulnerability discovery. The strategy pledges AI-enabled triage, malware analysis, attribution support, agentic AI adoption, expanded Computer Network Operations, ICS Coordinators in every field office, and a pledge on victim relief and privacy.

CyberScoop · 7d agoPolicy & legal

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 · 21d agoAI research

Decline in Rig Exploit Kit

Rig exploit kit activity dropped roughly 75% after the pseudo-Darkleech and EITest campaigns stopped using EKs, reflecting an overall decline in exploit kit activity.

Rig EK activity fell sharply in 2017: the pseudo-Darkleech campaign disappeared at the end of March, cutting Rig traffic about 50%, and the EITest campaign switched to tech support scams in late April, cutting another 50% in May. Broader causes include a shrinking browser target base, no major EK zero-day in over a year, and community takedowns of domain shadowing infrastructure. Criminals are shifting to malspam, social engineering schemes like fake HoeflerText notifications, and tech support scams.

Palo Alto Unit 42 · Aug 17, 2026Exploit / PoC in the wild1

Characterizing Language Generation in the Limit: Finite Witnesses and a Separation-Width Hierarch

New work characterizes language generation in the limit via finite witnesses, proves a full separation-width hierarchy, and formalizes all results in Lean.

The paper fully characterizes when language generation in the limit is possible for arbitrary families over a countable universe: each target must admit a finite positive witness such that targets activated by any finite sample share an infinite common intersection. It defines positive separation width and proves every level of the resulting hierarchy occurs, with countable families admitting singleton witnesses and unions of families with infinite common cores requiring unbounded finite witnesses. The characterization, a universal normalization, and a diagonal capture lemma are machine-checked in the Lean proof assistant, with the development maintained on GitHub.

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

Coding Is Over. Get over It

A JPMorgan Chase engineer reflects on AI agents outpacing hand-coding, questioning ROI while predicting inference costs will become negligible.

A personal essay by a software engineer with 15+ years at JPMorgan Chase describes how AI coding agents now outperform him and have transformed his workflow. He argues AI ROI is unmeasurable, praises cheap small models such as GPT 5.6 Luna, and cites Claude Code head Boris Cherny's advice to discard AGENTS.md/Claude.md rule files. He contends coding is no longer scarce, worries entry-level jobs will be automated first, and predicts AI's bigger impact lies outside coding.

Hacker News · security · 4d agoAI industryHN 20↑ · 26 comments2

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

New GPUThor Rowhammer Defeats ECC on NVIDIA RTX A6000 to Gain Host Root Access

University of Toronto researchers present GPUThor, a Rowhammer attack that defeats ECC on NVIDIA RTX A4000-A6000 GDDR6 GPUs and achieves host root access.

GPUThor uses non-uniform hammering to bypass Target Row Refresh and overcome SECDED ECC on NVIDIA Ampere workstation GPUs with GDDR6 memory, inducing 72,000 to 377,552 bit flips per gigabyte across RTX A6000, A5000, A4500, and A4000 cards. Triple-bit silent data corruption enables host privilege escalation to root with the IOMMU enabled, reusing GPUBreach page-table corruption techniques, and double-bit DUEs allow escalation when the IOMMU is disabled during a ~10 ms lazy-service window. The attack cut end-to-end escalation time on the A6000 from 21.9 hours to 1.1 minutes. Reported to NVIDIA, Google, Microsoft, and AWS on April 29, 2026; findings were embargoed until August 25, 2026, and no CVE identifier was assigned.

The Hacker News · 8d agoResearch1

Omni-Streaming Thinking

Omni-Streaming Thinking fixes premature cross-modal commitment in streaming omni-modal models via pending claims verified against modality-specific evidence, beating baselines by over 10%.

The paper identifies 'premature cross-modal commitment', where streaming models keep relaying early visual interpretations even after audio contradicts them. OST generates evidence-linked pending claims with future verification intervals, stores audio and visual evidence separately, and refutes claims when contradictory evidence appears. Built on a frozen Qwen3-Omni-30B-A3B-Instruct backbone with lightweight adaptation, it outperforms open baselines by more than 10% relative on five streaming and audio-visual benchmarks. On the new OST-DiagBench it reaches d-prime 2.95 versus at most 1.38 for open baselines, while reducing vision-induced auditory hallucinations.

Hugging Face daily papers · 2d agoAI research1

Hackers exploit Tencent app flaw to deploy GrayRabbit malware

UNC3569 actively exploits one-click RCE in Tencent Sogou Input Method to deploy the GrayRabbit backdoor, patched in version 16.3.0.3498.

Gen Digital reports that China-aligned UNC3569 is actively exploiting CVE-2026-51990, a one-click RCE chain in Tencent Sogou Input Method for Windows, which has hundreds of millions of installations in China. The chain abuses unvalidated command-line argument injection via the sgbiz: URI handler, unrestricted URL navigation in a CEF-based webview, and an unsandboxed outdated Chromium 80 engine to gain code execution and install the GrayRabbit backdoor. The analyzed malware is a mature 64-bit variant with RC4-encoded C2 config supporting reverse shells, file transfer, and reflective plugin loading. Tencent patched the argument validation in version 16.3.0.3498, but the browser engine remains outdated and unsandboxed.

BleepingComputerupdated · 2d agofirst · 3d agoExploit / PoC in the wild 2 sourcesCVE-2026-519903

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 · 6d agoAI research1

The Future of Deepfakes and the Decline of Reality (With Hany Farid)

GetReal cofounder and PhotoDNA developer Hany Farid discusses deepfake detection and how AI-generated media is blurring perceptions of reality.

404 Media's podcast episode features Hany Farid, cofounder of deepfake detection company GetReal and developer of the PhotoDNA perceptual hashing algorithm, discussing deepfakes and AI-generated images. The conversation reflects on how the technology has evolved since 2017 and speculates on where detection and perceptions of reality are headed. The episode is part of 404 Media's interview series for subscribers.

404 Media · Aug 17, 2026AI safety & security

RenderFormer-V2: Neural Rendering with Heterogeneous Scene Primitives

RenderFormer-V2 is a transformer-based neural renderer handling caustics, volumetric scattering and out-of-distribution materials without per-scene training or specialized code.

RenderFormer-V2 is a learned transformer-based neural rendering model that models global light transport as a sequence-to-sequence transformation, handling caustics, volumetric scattering, environment lighting, textured and displaced surfaces and out-of-distribution materials. It uses a two-stage process: a view-independent stage resolving primitive-to-primitive transport, and a view-dependent stage converting the neural scene representation into pixels. Improvements include combined windowed-attention with a rendering-informed attention sink for scalability, support for heterogeneous primitives like environment maps and participating media, and a surface-reflectance-independent neural material encoding, validated across diverse scenes with extensive ablations.

Hugging Face daily papers · 12d agoAI research

‘Watershed 250’ test program in Texas looks to private sector for water cybersecurity help

White House launches Watershed 250, a six-month Texas pilot using volunteer vendor cyber and AI tools to harden water utility defenses.

The Office of the National Cyber Director and Texas Cyber Command will oversee the six-month Project Watershed 250 pilot to improve water sector cybersecurity through industry-donated red teaming, system hardening and AI tooling. Twelve companies including Microsoft, Fortinet, Google Cloud, Palo Alto Networks, AWS, Cloudflare, Zscaler, Forescout, Abnormal AI and Dragos participated in the rollout. Officials cited recent attacks including an Iranian-backed campaign against 30 water systems in 12 states and a 2024 incident in Muleshoe, Texas. Some water-security professionals criticized the program as lacking dedicated funding.

CyberScoop · 15d agoPolicy & legal1

Diffusion Models and Concept Formation

Paper argues diffusion models implicitly form Cobweb-like concept hierarchies, with a basic level emerging at intermediate noise levels.

The authors draw a formal correspondence between diffusion models and Cobweb, a classic incremental concept-hierarchy learner, noting both are hierarchical Bayesian density models with Gaussian prototypes. Modes of the diffusion model's noisy marginals form a hierarchy whose basic level sits at intermediate noise, where class identity commits. The correspondence is tested on MNIST and Fashion-MNIST via mode-finding. Diffusion is reframed as a cognitive model of concept formation.

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

CISA Adds Two Known Exploited Vulnerabilities to Catalog

CISA added actively exploited PaperCut NG/MF flaws CVE-2026-81578 and CVE-2026-82078 to the KEV catalog, mandating federal patching.

CISA added two vulnerabilities to its Known Exploited Vulnerabilities catalog based on evidence of active exploitation: CVE-2026-81578 (PaperCut NG/MF missing authentication for critical function) and CVE-2026-82078 (PaperCut NG/MF unsafe reflection). Under Binding Operational Directive 26-04, Federal Civilian Executive Branch agencies are required to prioritize and apply these updates. The KEV listing signals observed exploitation of the PaperCut print management platform.

CISA Advisories · 16d agoExploit / PoC in the wildCVE-2026-81578CVE-2026-82078

PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models

PhysBrain 1.5, an 8B physical foundation model, sets open-source state of the art across 28 embodied understanding benchmarks.

The paper presents PhysBrain 1.5, a unified 8B model for understanding physical environments, generating actions, and predicting future states, built from a vision-language model with joint autoregressive next-token prediction over language, end-effector motion, and dense visual targets. Pre-training uses embodied supervision from human interaction videos, followed by supervised fine-tuning on human demonstrations, robot trajectories, and simulated experience. The model averages 72.5 across 28 embodied benchmarks, setting a new open-source state of the art and performing on par with proprietary GPT-6-Astra and Gemini 3.6 Flash, with best open-source results on 14 benchmarks.

Hugging Face daily papers · 2d agoAI research1

When will average people feel AI’s impact?

Interconnects essay argues AI's impact is still a rounding error for average people, comparing looming wage stagnation to Engels' pause.

An Interconnects essay argues that AI currently touches daily life far less than previous industrial revolutions, since its benefits are concentrated in knowledge work and lack tangible consumer goods. The author invokes Engels' pause (1790-1840), when British wages stagnated amid rapid GDP growth, as a warning that popular backlash could kneecap AI's development. He contends the current phase is about building compounding infrastructure, and predicts daily life may look similar even 50 years from now.

Interconnects · 7d agoAI industry1

ReCite: Agentic Reasoning for Faithful Citation

ReCite is an agentic citation framework using claim-level reasoning and verification, outperforming large generative models in strict citation accuracy.

ReCite is a decoupled agentic framework that orchestrates location perception, intent-aware query planning, and reflective verification for citation recommendation. Trained on synthesized reasoning trajectories, the agent verifies claim-evidence consistency and triggers self-correction loops when retrieved candidates lack logical support. Experiments show the lightweight framework outperforms state-of-the-art massive generative models in strict citation accuracy, addressing misattribution where cited papers are real but logically unsupportive.

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

NASA AIT-GUI Flaws Could Let Unauthenticated Attackers Issue Spacecraft Commands

Researchers disclosed 9.4-CVSS flaws in NASA/JPL's AIT-GUI allowing unauthenticated attackers to issue arbitrary spacecraft commands via exposed command endpoints.

Cycode disclosed a flaw chain in AIT-GUI, the browser-based operator console for NASA/JPL's open-source AMMOS Instrument Toolkit, tracked as GHSA-p9r8-2q67-fp86 with CVSS 9.4, affecting versions 2.5.1 and earlier. The server binds to 0.0.0.0:8080, issues sessions without credential checks, and lets unauthenticated users issue spacecraft commands via POST /cmd and reach files outside intended directories via /script/run and /seq (CWE-306, CWE-352, CWE-22). Version 2.5.2 adds host binding and same-origin checks but does not add authentication, and a related missing-authentication flaw was published separately as CVE-2026-60112 with CVSS 9.3.

The Hacker News · 27d agoVulnerabilityCVE-2026-601121

Convergent Emergence of In-Context Learning Across Modalities

Controlled experiments show few-shot in-context learning emerges across six modalities including language, genomes, images, and proteins, partially supporting a convergence hypothesis.

The paper tests the Convergent Emergence Hypothesis: that few-shot in-context learning, when it emerges, shares a common cross-modality difficulty profile. A controlled framework instantiated the same task suite across six modalities: language, genome, integer sequences, time series, images, and proteins. Paired-mapping ICL emerged in all six modalities, surpassed controlled baselines, and showed correlated per-task effects in five of them, providing partial support for the hypothesis.

Hugging Face daily papers · 4d agoAI research

Cyble Introduces Major Upgrade to its Executive Monitoring Module

Cyble upgraded Executive Monitoring in Cyble Vision, unifying impersonation, exposure, and mention findings with AI scoring and multi-channel alerting.

Cyble released a major upgrade to Executive Monitoring within its Cyble Vision platform, consolidating Mentions, Impersonations, Exposures, and a new Surface Mentions source (blog and news coverage) into a single findings stream. The release adds AI-generated verdicts and recommendations, per-executive Risk and Reputation scoring for board reporting, and richer onboarding with aliases, reference images, and addresses to cut same-name false positives. Alerting now supports data residency, bulk import, delivery via email, WhatsApp, and SMS, an Access API, and branded executive PDF reports; the upgrade is live with no customer action required.

Cyble · 6d agoTools

ECHO: A Matched-Contrast Benchmark for Context-Sensitive Turn-Taking in Full-Duplex Dialogue

ECHO benchmark pairs identical-overlap Chinese dialogue examples with contrasting contexts, revealing most full-duplex systems bias toward yielding the floor.

ECHO is a paired diagnostic benchmark for Chinese full-duplex turn-taking that matches examples with identical overlap transcripts but contrasting preceding multi-turn contexts, one requiring Yield and the other Keep. It also includes off-talk examples for diagnosing unnecessary yielding and introduces pair accuracy, which grants no credit to constant-action policies. Experiments across multiple full-duplex systems show most exhibit a pronounced Yield bias, performing substantially better on interruptions than backchannels. The benchmark and metadata will be publicly released.

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

Check Point Vulnerability Lets Remote Hackers Gain Root Access Without Authentication

Check Point patched CVE-2026-91843, a CVSS 9.8 pre-auth stack overflow granting remote root on Security Management and Log Servers.

Check Point released an urgent fix for CVE-2026-91843 (CVSS 3.1: 9.8), a stack-based buffer overflow triggered by an excessively long username during login that lets an unauthenticated remote attacker execute arbitrary code with root privileges. Affected products include Security Management Server, Multi-Domain Security Management Server, and Log Servers across releases from R80 through R82.20, with fixes delivered via LivePatch and urgent Take packages. The vendor reports no observed exploitation in the wild, and administrators are advised to verify patch deployment and restrict SmartConsole Trusted Clients.

Cyber Security News · 1h agoVulnerability 10 sourcesCVE-2026-91843

Who Should Grade My Work? Student Perspectives on Transparent AI-Assisted Writing Assessment in Higher Education

A Saudi university study finds students value ChatGPT writing feedback but treat human instructors as the final grading authority.

Thirteen male undergraduate computing students at a Saudi public university completed handwritten writing tasks that were scored by ChatGPT using a rubric-based prompt, then reflected after being told the score and feedback were AI-generated. Inductive thematic analysis identified four themes: perceived feedback usefulness, awareness of AI's contextual and pedagogical limitations, conditional trust, and reflection on the instructor's institutional role. Participants accepted GenAI feedback for surface-level revision but consistently positioned human instructors as the authority over grading decisions, distinguishing feedback utility from evaluative authority.

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

A Deep Dive Into Attempted Exploitation of CVE-2023

Mirai-like botnet scans exploit TP-Link EOL router flaw CVE-2023-33538 after CISA KEV addition, though observed exploit code is flawed.

Unit 42 observed large-scale automated scans attempting to exploit CVE-2023-33538 in end-of-life TP-Link TL-WR940N, TL-WR740N and TL-WR841N routers after CISA added the flaw to its KEV catalog in June 2025. HTTP GET requests inject commands via the ssid1 parameter at the /userRpm/WlanNetworkRpm endpoint to download and execute an arm7 ELF binary, a Mirai variant related to the Condi IoT botnet. Firmware emulation and reverse engineering showed the observed exploits are flawed and would fail, but the underlying vulnerability is real and successful exploitation requires authentication to the router's web interface. TP-Link confirmed the devices are end-of-life with no patches available and recommends replacing units and eliminating default credentials.

Palo Alto Unit 42 · 28d agoExploit / PoC in the wildCVE-2023-335381

Mi-Ripple: Restoring Images Degraded by Iterative AI Editing

Mi-Ripple is a diagnosis-guided restoration workflow that removes digital ripple artifacts introduced by iterative AI image editing while preserving structure.

Iterative reference-conditioned image editing can introduce grid-like and granular textures known as digital ripple. Mi-Ripple separates periodic lattice artifacts from content-entangled granular texture, then applies selective spectral notching, structure-aware smoothing, and cleaned-reference regeneration. In fourteen notch-only executions, whole-image residual standard deviation was 0.08-0.44 in CIELAB lightness units, and reference cleaning reduced output debris density by 45% in a paired example.

Hugging Face daily papers · 6d agoAI research

Another Blueprint In The Wall: How to Ask Frontier AI Like a Kid?

Six frontier models from OpenAI, Anthropic, xAI, and Google DeepMind converge on one imagined successor architecture when asked under a school-audience framing.

Researchers ran ten independent sessions per model type across six frontier models using a three-stage prompt sequence progressing to a full ASCII backbone architecture. Under school-audience framing, responses repeatedly converged on a shared motif including persistent latent state, adaptive computation, memory, specialist routing, verification, and stopping control, while control runs without the framing produced heterogeneous responses. A GPT-5.6 Sol output closely overlapped an architecture independently sketched by GPT-6 Astra, raising questions about shared design priors or motif propagation between model families. The paper coins 'epistemic jailbreak' for the observed loss of provenance discipline as prompt specificity increases.

Hugging Face daily papersupdated · 6h agofirst · 3d agoAI research 11 sources

StudyBench: Can Self-Evolution Squeeze Textbooks for Olympiad Capability?

Researchers introduce StudyBench, a physics benchmark showing self-evolution gains on textbook problems rarely transfer to olympiad-level questions.

StudyBench is a controlled physics benchmark splitting test data into an Application Set of difficult textbook problems and a Transfer Set of olympiad-level problems. Across three base models, representative self-evolution methods improved on the Application Set but rarely transferred to the harder Transfer Set. A guidance ablation reveals a Guidance Gap, and every method hits a Compute Plateau, indicating the remaining limits are method problems rather than data or compute problems.

Hugging Face daily papers · 15d agoAI research

Conti ransomware crew member sentenced to four years in prison

Ukrainian national Oleksii Lytvynenko sentenced to four years in the US for his role in Conti ransomware attacks on at least 12 companies.

Oleksii Lytvynenko, 44, who pleaded guilty in June to conspiracy to commit wire fraud, was sentenced Thursday to four years in prison by the US Justice Department. He joined the Conti ransomware group in September 2021 as an intruder and malware developer, holding stolen data from 12 victims including eight US-based organizations, and prosecutors said co-conspirators extorted roughly $634,000 in Bitcoin from Tennessee victims including government entities. Conti attacked more than 1,000 organizations before disbanding in 2022, with members rebranding into Zeon, Black Basta, and Quantum/Royal/BlackSuit.

CyberScoopupdated · 5d agofirst · 5d agoPolicy & legal 7 sources1

UniH^3: Unifying Hierarchical Homogeneity and Heterogeneity for All-in-One Medical Image Restoration

UniH3 unifies hierarchical homogeneity and heterogeneity modeling for all-in-one medical image restoration across modalities and degradation types.

UniH3 introduces a Hierarchical Homogeneity Memory module that distills shared anatomical priors from high-quality images, injected via a Homogeneity-Guided Attention mechanism. A Hierarchical Heterogeneity Balancer mitigates inter- and intra-task conflicts during multi-task optimization. It achieves state-of-the-art on MedIR-2D-500K and MedIR-3D-3D benchmarks for both all-in-one and single-task restoration, with code released on GitHub.

Hugging Face daily papers · 6d agoAI research

The hidden risks of shadow AI

UK NCSC guidance warns shadow AI use by employees risks data exposure, lost data control, and attacker exploitation of vulnerable AI agents.

The UK NCSC warns that 'shadow AI'—use of AI tools not captured in organizational approved systems—is widespread, with 71% of employees reporting unapproved AI tool use. Risks include exposure of sensitive company and customer data, loss of visibility and control when data goes to consumer AI services, and new attack opportunities if adversaries exploit vulnerabilities in AI agents with access to corporate systems. The NCSC advises reducing rather than eliminating the risk through positive security culture, understanding employee needs, offering secure alternatives, and following its joint guidance on careful adoption of agentic AI services.

NCSC UK · 9d agoAdvisory

Decomposition Buys Integrity, Not Yield

Study of 600 production deep-research traces finds agent-tree decomposition loses findings at rate N^(1-δ); flat architectures maximize yield.

The paper models multi-agent decomposition as a tree where an agent holding b items retains each with probability r(b); with r(b)=1/b every tree delivers exactly one finding regardless of shape. Analysis of 600 production deep-research traces estimates delta=0.34 retention decay, and 1,012 annotated traces show one brief in sixteen goes off-target per tier, giving an alignment penalty of 0.536. Depth still cuts root context exposure from N to N^(1/k) and is cheaper at scale, with a hazard model over 743,819 production tool calls showing delegation is an opening move rather than a response to filling context.

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