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The 12 Best Managed Detection & Response (MDR) Services, Compared and Priced

Buyer's guide compares 12 MDR services, naming Huntress best value, CrowdStrike Falcon Complete for response authority and Expel for transparency.

The article compares 12 managed detection and response providers across response authority, tool bundling and pricing, highlighting Huntress for published SMB pricing and CrowdStrike Falcon Complete for unilateral containment. It stresses the consolidation landscape: Sophos completed its acquisition of Secureworks in February 2025 for approximately $859 million, and Arctic Wolf closed its purchase of BlackBerry's Cylance endpoint assets the same month. It also warns that only full-response contract tiers isolate hosts and kill processes, while lower tiers only triage or guide.

GBHackersupdated · 7d agofirst · 7d agoIndustry 3 sources1

Rapid7 Named Among Notable Vendors in Forrester MDR Landscape: Why the Future is Exposure-informed, Preemptive MDR

Rapid7 touts its listing in Forrester's Q3 2026 MDR Landscape, arguing MDR must converge with exposure management for measurable risk reduction.

Forrester's Managed Detection and Response Services Landscape, Q3 2026 names Rapid7 among notable providers and predicts MDR services will converge with exposure and posture improvement. Rapid7 pitches its exposure-informed, preemptive MDR built on its own SIEM, combining vulnerability findings and asset risk scoring with detection and response. The service includes unlimited incident response and a human-led, AI-enhanced investigation model. Forrester advises buyers to demand providers prove investigations rather than narrate dashboards.

Rapid7 Blog · 2d agoIndustry

Three smart ways SMBs can improve cybersecurity

Opinion piece urges small and midsize businesses to adopt proactive prevention, threat detection, and 24/7 MDR or XDR services.

This opinion article argues SMBs face outsized cyber risk due to limited budgets, small IT teams, and reactive security postures. It recommends proactive prevention, a defined threat detection and response strategy, and managed detection and response (MDR) or extended detection and response (XDR) services. It cites ransomware costs up to $10,000 per device and an attack every 39 seconds as motivation for adopting vendor-operated 24/7 monitoring.

Help Net Security · 20d agoIndustry

12 Best Ransomware Protection Solutions Compared (2026): Features & Pricing

GBHackers compares 12 ransomware protection solutions for 2026, recommending layered stacks of EDR prevention, managed detection, containment, and guaranteed recovery.

The editorial comparison argues no single product stops ransomware, recommending a layered strategy across prevention, early detection, blast-radius containment, and clean recovery. CrowdStrike and SentinelOne are named best-in-class EDR, Huntress and Sophos MDR for managed 24/7 coverage, ColorTokens for microsegmentation containment, and Rubrik and Acronis for guaranteed recovery. The guide notes ransomware is now professionalized with double extortion and encryption sprints measured in minutes.

GBHackersupdated · 8h agofirst · 5d agoIndustry 14 sources1

The 12 Best Endpoint Detection & Response (EDR) Solutions, Compared and Priced

An editorial scorecard ranks 12 EDR platforms, with CrowdStrike and SentinelOne tied at 8.6/10 and telemetry retention identified as the hidden cost driver.

An editorial comparison scores twelve EDR platforms on detection, response, analyst burden, pricing transparency, and coverage. CrowdStrike and SentinelOne tie at 8.6/10, with Microsoft Defender for Endpoint close behind at 8.5 and described as effectively free in Microsoft 365 E5 estates. The guide argues that telemetry retention, not per-endpoint price, drives real cost, with fully-priced quotes frequently diverging 2-3x from headline rates. Managed detection offerings, including Cynet's bundled 24/7 SOC, factor into the buyer-fit rankings.

GBHackers · 7d agoIndustry 2 sources

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

Performance of Clinical AI System and Physicians and Frontier Language Models in primary care diagnostics

Clinical AI system Doctorina achieved 82.0% primary-care diagnostic concordance versus 57.0% for physicians across 150 synthetic consultations.

The study compared Doctorina, eight physicians, and four standalone frontier language models on 150 synthetic Polish-language primary-care consultations. Doctorina achieved 82.0% Top-1 diagnostic concordance versus 57.0% for physicians (25.0-point difference, 95% CI 17.7-32.7) and 97.3% versus 85.0% primary-or-reference-differential concordance. Normalized workup and treatment scores were 89.4 versus 66.9 and 83.7 versus 61.2. Kimi K3 ranked next on diagnosis, while Claude Opus 5 led the closely spaced management estimates among Opus, Doctorina and Kimi.

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

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

The 12 Best Antivirus (Endpoint Protection) Software for Business, Compared and Priced

GBHackers compares 12 business antivirus products on detection, EDR depth, pricing, and platform coverage, ranking CrowdStrike and Bitdefender joint top at 8.8.

The roundup scores 12 enterprise endpoint protection vendors across detection, EDR depth, management, pricing transparency, and platform coverage. CrowdStrike and Bitdefender tie at 8.8, with Microsoft Defender for Endpoint scoring 8.5 and noted as effectively free for Microsoft 365 E5 licensees. The piece also flags that Kaspersky cannot legally be sold in the US and that Panda and Webroot now sit under WatchGuard and OpenText respectively.

GBHackers · 8d agoIndustry 2 sources1

Towards a Deterministic Math Solver for Clinical Language Models

Paper shows handing arithmetic to a deterministic Python solver beats direct model calculation at 32B but not reliably at 7B on MedCalc-Bench.

Researchers test a Program-Solve interface where clinical LLMs write case-specific Python executed by a restricted local solver instead of doing arithmetic directly. On MedCalc-Bench Verified (1,100 cases, 55 calculators), Qwen2.5-32B-AWQ scored 90.53% with solver handoff versus 83.47% with direct arithmetic (+7.05 points), while Qwen2.5-7B gained an unreliable +3.29 points with a confidence interval spanning zero. The authors audited the benchmark against clinical guidelines and flagged 16 of 55 calculators for version, use, or coefficient concerns.

Hugging Face daily papers · 7d agoAI research

Top 10 Best Ransomware Protection Solutions in 2026

A 2026 buyer's guide ranks ten ransomware protection tools by kill-chain role as extortion shifts from encryption to data theft.

The roundup organizes defenses across the ransomware kill chain: prevention-grade EPP/EDR platforms, containment layers, rollback specialists, and immutable recovery. Recommended products include CrowdStrike, Microsoft Defender, Sophos, SentinelOne, Bitdefender, Trend Micro, Halcyon, Huntress, and Malwarebytes. It stresses that many crews now extort on stolen data without encrypting, making exfiltration detection and response speed as important as rollback.

Cyber Security News · 6d agoIndustry1

The 2026 PNPL Competition: Word Classification and Efficient Cross-Subject Generalisation in LibriBrain100

The 2026 PNPL competition releases LibriBrain100, a MEG speech dataset with 32 extra subjects, targeting word classification and cross-subject BCI generalization.

The 2025 PNPL competition on non-invasive speech decoding from MEG achieved F1-macro scores of 95.6% for speech detection and 73.6% for phoneme classification, built on LibriBrain's ~50 hours of single-subject data. The 2026 edition extends this with LibriBrain100, adding 32 subjects (~40 minutes each) plus ~80 hours of within-subject data. Two tracks target within-subject word classification at scale and cross-subject generalization with subject-specific fine-tuning shrinking from ~40 to ~20 to ~10 minutes, aiming at clinically feasible non-invasive BCIs for people with profound paralysis.

Hugging Face daily papers · 13d agoAI research

Attackers impersonate popular AI brands to spread malware

Sophos documented 38 MDR cases where attackers impersonated AI brands like Claude and Perplexity to deliver infostealers and backdoors.

Sophos X-Ops analyzed 12 months of MDR cases and confirmed 38 incidents involving AI. Software impersonation accounted for 30 cases, with Claude impersonated in 26; fake installers used an 'InstallFix' technique delivering mshta commands, in-memory payloads, and process hollowing. Malicious browser extensions posing as AI assistants, including a fake Perplexity extension with 10,000 installs, acted as infostealers. In one case, attackers used a Claude coding agent to develop a Rust remote access trojan communicating over Slack after an SQL injection compromise.

Help Net Security · 26d agoThreat actor in the wild

OracleZoom: On-Policy Self-Distillation Inspired Reference-Constrained Recursive Image Super Resolution

OracleZoom enables recursive extreme-scale image super-resolution via reference-constrained on-policy distillation, reducing hallucinations at deep zoom scales.

OracleZoom tackles recursive super-resolution, where repeated feeding of predictions back into the same model leaves deeper-scale outputs unsupervised as required source resolution grows geometrically. The framework trains on its own trajectory while carrying the last ground-truth evidence beyond the supervision boundary, combining direct and cross-scale supervision, a no-reference quality objective, a KL-constrained pretrained latent prior, and EMA consistency. Across seven datasets it achieves state-of-the-art SR quality across zoom scales, averaging 0.713 CLIPIQA with larger gains at deeper scales and significantly reduced hallucinations. Code, data, and models are publicly released.

Hugging Face daily papers · 10d agoAI research

Top 10 Best Cloud Detection & Response (CDR) Solutions in 2026

Editorial scorecard ranks ten 2026 cloud detection and response platforms; Sysdig, Wiz, and CrowdStrike lead, with Wiz's Gem Security acquisition highlighted.

The editorial scorecard rates ten CDR platforms on real-time detection (30%), cloud telemetry depth, response automation, correlation, and value. Sysdig earns the best real-time detection score for its Falco- and eBPF-powered runtime telemetry, Wiz (8.7) folds acquired Gem Security's real-time CDR into its security graph, and CrowdStrike (8.7) leads response automation. Specialists Stream.Security, Skyhawk Security, Sweet Security, and the open-source Falco project are also assessed.

Cyber Security News · 11h agoIndustry

MP-Bench: Evaluating Voice Agents as a Multiparty Conversation Participant

MP-Bench is the first benchmark for voice agents in multiparty conversations, finding real-time agents near chance on turn-taking.

MP-Bench is the first benchmark designed to objectively evaluate conversational speech systems as active participants in multi-party conversations. It assesses agents on turn-taking awareness and response appropriateness, with comprehension-based question-answering as a complementary evaluation. Benchmarking 12 voice agents shows real-time agents score at or below 22% on multiparty comprehension and remain near chance on multiparty turn-taking.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research2

Top 10 Best Patch Management Software in 2026

Roundup ranks 2026 patch management software, favoring Automox, Action1's free tier and Tanium, and warns buyers to vet patching platform security.

This buyer's guide ranks ten patch management tools for 2026, placing Automox first for cloud-native patching, Action1 for a genuinely free small-estate tier and Tanium for patching hundreds of thousands of endpoints. It contextualizes the category with the 2021 Kaseya VSA ransomware supply-chain incident and the 2020 SolarWinds Orion compromise, arguing the security of the patching platform itself must be part of evaluation. It also notes Ivanti products have repeatedly appeared in CISA's Known Exploited Vulnerabilities catalog.

Cyber Security News · 7d agoIndustry

DriveZero: End-to-End Driving Beyond Human Demonstrations

DriveZero pairs a frozen vision-foundation-model perception stack with a PPO-trained closed-loop RL teacher to beat replay experts on nuPlan.

DriveZero is an end-to-end camera-only autonomous-driving planner that separates perception and action. Its DriveVFM perception backbone consolidates frozen vision foundation models (DINOv3, SigLIP2, SAM, Depth Anything V2) from raw images without task annotations, while DriveRL trains a privileged PPO teacher policy through closed-loop rollouts in interactive worlds built from real driving logs. The planner distills this teacher, achieving a 93.57 mean nuPlan score across Val14, Test14-hard and Test14-random splits and beating the Log-Replay expert on all three. It also sets state of the art on NAVSIMv1, NAVSIMv2 and closed-loop HUGSIM without human trajectory supervision.

Hugging Face daily papers · 11d agoAI research

Large Language Models Develop Belief State Geometry In-Context

Probing six open-source LLMs on HMM-generated data shows belief states are linearly decodable (R² 0.83–0.99), suggesting in-context learning approximates Bayesian prediction.

Researchers prompted six open-source LLMs with data from 40 hidden Markov models selected for non-trivial belief structure and probed residual-stream activations for belief states (posteriors over hidden states). Belief states were linearly decodable with peak R² values of 0.83–0.99 across HMM/LLM combinations, spanning early to late layers. Patching and steering the probe-identified subspace preserved downstream prediction quality while control interventions degraded performance substantially, establishing functional relevance. The results provide representation-level evidence that in-context learning approximates optimal Bayesian prediction over a context-inferred generative model.

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

Exaforce extends its AI security tool to monitor more than just Claude

Exaforce AI Security extends beyond Claude to monitor OpenAI, Gemini, and Copilot agents using existing SOC telemetry, no new endpoint agents.

Exaforce expanded its June Claude Compliance API integration into Exaforce AI Security, adding monitoring for OpenAI, Gemini, Microsoft Copilot, and OAuth-connected AI apps. The tool inventories AI agents by correlating EDR, cloud, SaaS, and model-provider logs without new gateways or endpoint agents, and can respond by revoking sessions, deactivating API keys, isolating devices, or killing agent processes via existing controls. Analysts note the agentless approach lowers friction but lacks runtime inspection and inline blocking offered by competitors such as Palo Alto Prisma AIRS, SentinelOne Prompt AI Agent Security, and CrowdStrike Falcon Guardian. A March 2026 Cloud Security Alliance survey found 68% of organizations cannot distinguish human from AI-agent activity and 74% report AI agents receive excessive access.

CSO Online · 1d agoTools

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a generative time-aware transformer trained on 559 million MIMIC clinical events to model and forecast patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer designed to represent and forecast the full multimodal patient journey across medical images, time-series signals, categorical events, and clinical text. It was trained on over 559 million clinical events from 431,000 hospital visits covering 299,000 patients in the MIMIC dataset family. The architecture combines bidirectional time integration with a variational latent space to capture continuous patient state evolution and clinical stochasticity. NOAH supports autoregressive forecasting with time control, zero-shot classification, and counterfactual intervention simulation, with evaluations on 15 ICD chapters, 29 comorbidities, and time-to-event prediction.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research2

ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation

ActReview post-trains Qwen3-8B-Base on OpenReview rebuttals to generate actionable peer-review feedback with grounded revision suggestions, benchmarked on 1,000 curated instances.

The paper defines Actionable Peer-review Generation as diagnostic claim generation plus revision suggestion generation and introduces ActReview, a rebuttal-guided post-training framework. From OpenReview review-rebuttal threads the authors build ActReview-40K, aligning reviewer weaknesses with author responses grounded in localized paper evidence, and post-train Qwen3-8B-Base with multi-task SFT followed by GRPO using weakness-specific rubric rewards. They also release ActReview-Bench, a human-curated 1,000-instance benchmark, on which ActReview outperforms prior specialized review-generation models on actionability and grounding while remaining competitive with strong prompt-based LLMs. Human evaluation confirms improved revision usefulness but identifies a remaining gap in technical accuracy.

Hugging Face daily papers · 8d agoAI research

AgentGrad: Intervention-guided Prompt Optimization for Multi Agent Systems

AgentGrad introduces intervention-guided prompt optimization for LLM multi-agent systems, achieving state-of-the-art results with 2.5x faster optimization.

AgentGrad is a prompt optimization framework for LLM-based multi-agent systems that addresses limitations in textual gradient extraction and aggregation. It uses sequential intervention to identify the agent whose prompt modification resolves a given failure, then applies agent-level supervision and semantic gradient clustering to build generalized gradients. Experiments report state-of-the-art performance across five MAS benchmarks and a 2.5x average reduction in wall-clock optimization time versus the next-fastest baseline.

Hugging Face daily papers · 8d agoAI research

"WP2Shell" Critical WordPress RCE Chain (CVE-2026-63030 & CVE-2026-60137)

CISA added the WordPress core pre-auth RCE chain (CVE-2026-63030, CVE-2026-60137) to KEV after confirmed exploitation; WordPress 6.9.5 and 7.0.2 fix the flaws.

On July 17, 2026 WordPress disclosed CVE-2026-63030, a REST API route-confusion flaw, and CVE-2026-60137, a SQL injection in WP_Query, which chain to unauthenticated remote code execution on default installs of WordPress 6.9.0-6.9.4 and 7.0.0-7.0.1. CISA has added both to the Known Exploited Vulnerabilities Catalog and active exploitation is confirmed. Cloudflare deployed WAF rules at 17:03 UTC on July 17, and patches are available in WordPress 6.9.5 and 7.0.2.

Web discovery (articles for new exploits & KEV entries) · 8d agoExploit / PoC in the wild 2 sourcesCVE-2026-63030CVE-2026-601371· 1 read

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a time-aware generative transformer trained on 559 million MIMIC clinical events to forecast multimodal patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer trained on over 559 million clinical events from 431,000 hospital visits by 299,000 patients across the MIMIC dataset family. It uses bidirectional time integration and a variational latent space to model the stochastic evolution of patient states, natively processing medical images, time-series signals, categorical events, and structured or unstructured clinical records. The model supports autoregressive forecasting with optional time control, zero-shot classification, and counterfactual intervention simulation, with strong probing performance across clinical outcomes, 15 ICD chapters, and 29 comorbidities.

Hugging Face daily papers · 8d agoAI research1

Top 10 Best Mobile Threat Defense (MTD) Solutions in 2026

Roundup of 2026 mobile threat defense tools recommends Zimperium and Lookout for targeted-attack detection and Defender for Endpoint for Microsoft shops.

This guide ranks ten mobile threat defense solutions, recommending Zimperium and Lookout for on-device detection against targeted users such as executives and journalists, and Microsoft Defender for Endpoint mobile for organizations already licensing Microsoft 365 E5. It explains that MDM enforces configuration while MTD detects attacks, and that mobile phishing now arrives via SMS, messaging apps and QR codes rather than email. It also highlights mercenary spyware and zero-click exploits as shifting requirements for high-risk users, referencing Apple's threat-notification program and Lockdown Mode.

Cyber Security News · 7d agoIndustry

PLC-DPO: Posterior Label Correction in Noisy and Ambiguous Preference Optimization

PLC-DPO corrects noisy preference labels during DPO by routing each pair as clean, flip, or tie using calibrated policy-reference margins.

PLC-DPO addresses reversed, weak, or ambiguous preference labels in Direct Preference Optimization by using the calibrated policy-reference margin as online evidence to route each pair's training signal as clean, flip, or tie. This actively corrects supervision direction and strength rather than only filtering suspicious examples. Across 57 dataset-model-benchmark cells, PLC-DPO achieves the best mean win rate of 60.5 versus 55.5 for the next-best method. Injected-noise and tie stress tests plus human disagreement analysis show the routing stays stable and distinguishes flipped from weakly directional pairs.

Hugging Face daily papers · 16d agoAI research

Threat Actors Don’t Want Better Attacks. They Want Repeatable Ones

Opinion piece argues attackers prioritize repeatable playbooks like ClickFix (47% of Microsoft-notified attacks) and living-off-the-land over novel techniques.

The column analyzes why commodity techniques scale: Microsoft observed ClickFix as the top initial access method at 47% of its notifications last year, while Bitdefender found 84% of 700,000 analyzed high-severity incidents involved binaries already present on machines. Verizon's DBIR shows vulnerability exploitation rising to 31% of initial access vectors, up from 20%, and ransomware leak-site rankings show Qilin (roughly 1,600 claimed victims) and The Gentlemen (121 claimed victims in June) competing on throughput. The author argues attackers behave like a generics business, standardizing repeatable procedures rather than investing in novel tradecraft.

The Hacker News · 15d agoIndustry

Modality-Autoregressive World-Action Models

ModAR autoregressively denoises multiple future modalities (point tracks, DINO features, depth) before predicting actions, beating prior world-action models at all data scales.

ModAR is the first world-action model (WAM) to autoregressively denoise multiple future modalities before predicting actions, letting each prediction condition on previously generated modalities. Training from scratch shows WAMs benefit from predicting point tracks, DINO features, and depth maps, while future RGB adds no consistent benefit. ModAR's sequential generation outperforms existing WAM formulations with the highest average success rate at all evaluated data scales. It slightly beats video-model-initialized Flex-π (75% vs 72% success) using roughly 20x fewer training FLOPs and no pretraining, and wins on three real-world bimanual tasks.

Hugging Face daily papers · 1d agoAI research

Top 10 Best Cloud Security Posture Management (CSPM) Tools in 2026

2026 CSPM comparison ranks Wiz atop cloud posture tools and recaps Google's pending roughly $32 billion acquisition of Wiz.

An editorial guide rates ten cloud security posture management (CSPM) tools, with Wiz ranked first for agentless visibility and attack-path context, Microsoft Defender for Cloud highlighted for Azure-centric economics, and Palo Alto Prisma Cloud noted for the broadest code-to-cloud module set. The article's biggest market note is Google's agreement to acquire Wiz for approximately $32 billion, described as the largest deal in security history, still progressing through regulatory review. It advises buyers to include roadmap-protection language in multi-year commitments and to press on multicloud neutrality post-close.

Cyber Security News · 5d agoIndustry

K-Bench: a clinically calibrated benchmark for evaluating large language models in high-risk mental health conversations

Clinician-calibrated K-Bench evaluates 125 LLM configurations on 200 high-risk mental health vignettes, exposing wide variation in suicide and violence risk handling.

K-Bench is a clinician-calibrated, protected benchmark evaluating 125 model configurations from 33 base models across 14 providers on 200 multi-turn vignettes covering suicide, self-harm, domestic violence, substance misuse and no-risk presentations. A frozen GPT-4o judge achieved 94.2% exact agreement with clinician consensus across 6,751 eligible comparisons from 151 clinician-rated transcripts. Leading models combined supportive conversation with combined-risk scores above 95, while risk exploration varied substantially among weaker configurations; therapeutic prompting helped weaker models and elevated reasoning produced no average improvement. A continuously updated public leaderboard is hosted at k-bench.ai with protected test materials.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI safety & security

GuardBreaker: Derailing AI-assisted malware analysis with a code comment

ESET names 'GuardBreaker': UAC-0099 embeds a nuclear-weapon question in VBScript comments to trip LLM scanner guardrails during analysis of its MATCHBOIL loader.

ESET researchers observed the Russia-aligned group UAC-0099 inserting a decoy prompt injection into a VBScript used to install its MATCHBOIL loader in an attack against a Ukrainian target, aiming to make LLM-based code scanners refuse and stop inspecting the file. The comment triggers safety guardrails with a request about building a nuclear weapons but has no runtime effect. Similar LLM-thwarting tricks have appeared in malicious PyPI and npm packages reported by Socket and StepSecurity. ESET recommends multi-model cross-validation of AI-assisted analysis and treating missing LLM output as requiring further checks.

ESET WeLiveSecurityupdated · 5d agofirst · 6d agoAI safety & security 3 sources1

Anchoring Clinical Events in Time: UID-Preserving Multimodal Reconstruction and Source-Grounded Adjudication

UID-preserving multimodal framework plus GAVEL LLM judge improves clinical timeline reconstruction, boosting event recovery 43% over prior matching.

The paper introduces a UID-preserving framework linking each narrative clinical event to its source span through text-only estimation, structured-evidence retrieval, timestamped source-row grounding, and joint revision. GAVEL, an LLM judge, compares UID-aligned timelines against narrative and structured records. Across six open-weight models and 40 mixed-critical-care summaries, GLM 5.2 multimodal revision improved temporal agreement without reducing event recovery and performed competitively with clinician annotations, while DeepSeek V3.2 did not benefit from multimodality. The pipeline achieves 43% increased event recovery with occurrence-level provenance.

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

Top 10 Best Server Security Solutions in 2026

Cyber Security News ranks 2026 server security platforms, favoring Trend Micro for hybrid estates, CrowdStrike for detection, Defender for Azure economics.

Cyber Security News published an editorial ranking of ten server security platforms for 2026, favoring Trend Micro for hybrid estates, CrowdStrike for detection quality, and Microsoft Defender for Servers for Azure-centric economics. The guide stresses that server security licensing differs (per server, per core, or per cloud-hour) and flags hypervisor protection as a commonly missed coverage gap.

Cyber Security News · 6d agoIndustry1

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