Search: “dspm”

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Top 10 Best Data Security Posture Management (DSPM) Tools in 2026

A 2026 scorecard ranks DSPM tools with Wiz and Cyera tied first, documenting consolidation via Palo Alto, Rubrik, Proofpoint, and CrowdStrike acquisitions.

The article ranks ten DSPM platforms: Wiz and Cyera tie at 8.7/10, followed by BigID at 8.5 and Securiti at 8.4, scored on discovery breadth, classification accuracy, access context, remediation, and value. It highlights heavy market consolidation, noting Dig Security was acquired by Palo Alto Networks, Laminar by Rubrik, Normalyze by Proofpoint, and Flow Security by CrowdStrike. Buyers are advised to purchase from current owners and confirm post-acquisition integration state.

Cyber Security News·07:29 UTC · 2h agoIndustry

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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·Sep 11, 07:10 UTC · 5d agoIndustry

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Top 10 Best SaaS Security Posture Management (SSPM) Tools in 2026

Scorecard ranks 2026 SSPM platforms with AppOmni and Obsidian Security leading after CrowdStrike folded Adaptive Shield into its Falcon platform.

The editorial scorecard rates ten SaaS security posture management tools on app coverage (30%), misconfiguration depth, SaaS identity/OAuth risk, shadow-SaaS discovery, and value. AppOmni scores 9.0 for unmatched app coverage across enterprise SaaS suites, and Obsidian Security scores 8.9 for SaaS identity threat detection and ITDR workflows. CrowdStrike now delivers Adaptive Shield's SSPM natively within Falcon, and Zscaler's Canonic Security acquisition signals continued platform consolidation.

Cyber Security News·07:35 UTC · 2h agoIndustry

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Top 10 Best CNAPP (Cloud-Native Application Protection) Platforms in 2026

GBHackers ranks 10 CNAPP platforms for 2026, naming Wiz, Prisma Cloud, and Microsoft Defender for Cloud as category leaders.

The guide describes CNAPP as the umbrella combining CSPM, CWPP, CIEM, and DSPM, arguing that cross-pillar correlation of attack paths is the platform's core value. Wiz is ranked best for graph-based correlation, Prisma Cloud for the broadest module set, and Microsoft Defender for Cloud for Azure economics. It also cites Google's approximately $32 billion agreement to acquire Wiz, announced in March 2025, as buyer leverage and a reason to seek roadmap and neutrality protections in multi-year contracts.

Cyber Security News·Sep 11, 07:21 UTC · 5d agoIndustry1

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TPMSpy: Validation of Measured Boot Systems by Low-Level Tracing of TPM Usage

Researchers present TPMSpy, a platform-agnostic method validating TPM Measured Boot via low-level tracing, finding inconsistent Linux systemd measurements that break remote attestation and LUKS decryption.

An arXiv paper (2609.05011) introduces TPMSpy, a method that analyzes virtualized system–TPM interactions to independently reconstruct and validate TPM Event Logs without relying on the quoting mechanism, applicable to open and closed systems and demonstrated on Linux and Windows. A longitudinal analysis of Linux systems running systemd versions 245–258 (2020–2025) found wide divergence in Measured Boot usage, undocumented behavioral changes, and no common usage pattern. The authors report inconsistent measurement of user-space systemd services, which prevents reliable remote attestation and LUKS disk decryption on affected systems.

arXiv cs.CR·Sep 4, 11:23 UTC · 11d agoResearch

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llm 0.34

Version 0.34 of Simon Willison's llm CLI adds response-duration metrics to log output, plus bug fixes and faster log querying.

The open-source llm command-line tool for interacting with large language models released version 0.34. The headline change adds response duration in milliseconds and human-readable form to llm logs --usage Markdown output, plus a new duration_ms field in llm logs --short. The release includes several contributed bug fixes and a significant performance improvement to llm logs, alongside the related llm-openrouter 0.7.1 release.

Simon Willison·Sep 2, 19:23 UTC · 13d agoAI tools & infra

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12 Best CNAPP Platforms Compared (2026): Features & Pricing

Independent comparison of 12 CNAPP platforms finds identical estates draw quotes 2-3x apart; Microsoft Defender for Cloud is the only fully published per-resource option.

A vendor-independent buyer's guide compares twelve CNAPP platforms including Prisma Cloud, CrowdStrike Falcon Cloud Security, Wiz, Uptycs, Aqua, Zscaler, and Microsoft Defender for Cloud on pricing mechanics, procurement leverage, and capability-per-dollar. It finds quotes swing 2-3x on identical estates because vendors define 'workload' differently. Microsoft Defender for Cloud is highlighted as the only major with fully published per-resource rates.

GBHackers·Sep 15, 06:49 UTC · 1d agoIndustry1

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MetroLLM-Bench: Evaluating Language Models as Transit Kiosk Runtimes

MetroLLM-Bench is a 955-case benchmark testing language models as transit kiosk tool-calling runtimes across six real metro systems.

The benchmark covers 37-414-station metro systems and eleven task categories including routing, fare calculation, disruptions, accessibility, and adversarial input, with 14 deterministic and 8 semantic scoring components. Of 26 models from six vendors, a PEFT-tuned 4B Qwen 3.5 student scored 91.3 on Tier 1, exceeding GPT-5.6 (90.6/90.0), while Muse Glimmer 30B led the composite ranking. A deterministic rule-based baseline reached 84.6, and PEFT gains over base models shrank from +7.03 points at 2B to -0.91 at 27B.

Hugging Face daily papers·Sep 8, 20:00 UTC · 7d agoAI research

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Top 10 Best Cloud Access Security Broker (CASB) Solutions in 2026

2026 CASB guide ranks Netskope first for depth and Microsoft Defender for Cloud Apps for Microsoft estates, as standalone CASB fades into SSE.

Buyer's guide covers ten CASB products across four enforcement modes: API, forward proxy, reverse proxy and log-based discovery. Netskope leads on SaaS activity context depth, while Microsoft Defender for Cloud Apps wins on Microsoft 365 E5 estate economics. The guide argues standalone CASB purchases have largely disappeared into SSE platforms and increasingly overlap with SSPM.

Cyber Security News·Sep 15, 06:24 UTC · 1d agoTools

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VU#431093: TCG TPM 2.0 reference code found vulnerable to information leakage and timing side-channel attacks

CERT/CC discloses two TPM 2.0 reference code flaws allowing RSA key decryption and forged TPM attestations via crafted commands.

CERT/CC published VU#431093 covering two vulnerabilities in the TCG TPM 2.0 reference implementation: CVE-2026-6726 (information leakage via falsified TPM keys) and CVE-2026-6727 (timing side-channel in RSA OAEP decryption). An attacker with privileged access to a TPM command interface could send crafted TPM commands to decrypt ciphertexts for affected TPM-managed RSA keys, including the RSA Endorsement Key, or obtain credentials enabling forged TPM 2.0 attestations. Remediation is tracked in TCGVRT010 and TCGVRT0011.

CERT/CC Vulnerability Notes·Aug 11, 15:12 UTC · Aug 11, 2026VulnerabilityCVE-2026-6726CVE-2026-6727

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Top 10 Best Serverless Security Solutions in 2026

Buyer's guide ranks Palo Alto Prisma Cloud and Aqua top for serverless security; standalone serverless security has largely folded into CNAPP platforms.

A top-ten listicle evaluates serverless security tools across FaaS platforms like AWS Lambda, Azure Functions, and Google Cloud Functions. Prisma Cloud and Aqua lead platform coverage, Snyk owns code/dependency scanning, and Sysdig covers runtime behavior. The guide's main conclusion is that the standalone serverless security category has largely consolidated into CNAPP platforms.

Cyber Security News·Sep 15, 06:48 UTC · 1d agoIndustry

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Up to 3.2x Faster Inference with LFM2.5-DSpark

LiquidAI's LFM2.5-DSpark delivers up to 3.2x faster inference, announced via the Hugging Face blog.

LiquidAI announced LFM2.5-DSpark on the Hugging Face blog, claiming up to 3.2x faster inference. The release focuses on improved runtime performance for the LFM2.5 model family; further technical details were not available in the provided text.

Hugging Face Blog·Aug 20, 16:52 UTC · 26d agoAI tools & infra

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11 Best CSPM Tools Compared (2026): Features & Pricing

CSPM comparison ranks Wiz first for agentless attack-path analysis; notes Ermetic absorbed into Tenable and Lacework into Fortinet FortiCNAPP.

An editorial comparison of eleven CSPM tools ranks Wiz as the agentless attack-path momentum leader, Prisma Cloud as the breadth benchmark, and Orca as the agentless SideScanning pioneer. It highlights consolidation: Ermetic now powers Tenable Cloud Security and Lacework became Fortinet's FortiCNAPP. The guide recommends starting with free tiers from Defender for Cloud, Prowler, and native cloud tools before buying.

GBHackers·Sep 15, 06:37 UTC · 1d agoIndustry1

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3D Point Splatting for mmWave Radar Novel View Synthesis

Researchers propose 3DPS, a differentiable point renderer for mmWave radar novel view synthesis that outperforms optical-NVS baselines by 1.7x-5.2x.

The paper introduces 3D Point Splatting (3DPS), the first differentiable point renderer for radar, derived from the solid-angle form of the radar equation with ITU-R P.2040 material models and complex phasor splatting. On six outdoor ColoRadar scenes it reaches 0.587 mean Pearson correlation on held-out range-azimuth images, between 1.7x and 5.2x the RadarSplat, Radar Fields, and DART baselines. The same optimized scene produces ADC, complex range profile, and RA outputs via standard FFT pipelines, and training takes about 3 minutes per scene on an RTX 4090.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:52 UTC · 5d agoAI research

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Top 10 Best Cloud Infrastructure Entitlement Management (CIEM) Tools in 2026

2026 CIEM guide ranks Wiz, Prisma Cloud, Okta, Entra Permissions Management and specialists Sonrai, Britive, Tenable/Ermetic for cloud entitlement right-sizing.

Buyer's guide covers ten CIEM products across three market routes: CNAPP-bundled (Wiz, Prisma Cloud), identity-suite (Okta, CyberArk, SailPoint, Saviynt) and specialists (Sonrai, Britive, Tenable/Ermetic). It cites machine identities outnumbering humans 10:1 plus effective-permissions sprawl as core drivers, with JIT elevation as the fix. Notable consolidation includes Tenable acquiring Ermetic and Zscaler acquiring Canonic.

Cyber Security News·Sep 15, 06:30 UTC · 1d agoTools

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OpenBMB Releases MiniCPM5-2B: A 2.52B Dense Model Averaging 53.9 Across 34 Benchmarks and Built to Run On Device

OpenBMB released MiniCPM5-2B, a 2.52B-parameter Apache 2.0 on-device model averaging 53.9 across 34 benchmarks, ahead of Qwen3.5-4B.

OpenBMB released MiniCPM5-2B, a 2,516,756,480-parameter dense LlamaForCausalLM model with grouped-query attention and a 131,072-token context, under Apache 2.0, runnable via vLLM, SGLang, llama.cpp, and Ollama. It averages 53.9 across 34 benchmarks versus 51.1 for Qwen3.5-4B, with strong tool-use (97.1 on tau2-Bench Telecom) and code results (69.1 LiveCodeBench v6, 46.4 SWE-bench Verified). Training combined 400B tokens of deep-thinking SFT, critic-based JustRL II RL teachers, and on-policy distillation merging 16 RL experts; datasets and intermediate checkpoints were published alongside the weights.

MarkTechPost·Sep 7, 19:18 UTC · 8d agoModel release

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New TCG guidance gives buyers a way to test PQC-ready TPM claims

Trusted Computing Group published PTP 1.07-based requirements defining PQC-ready and PQC-upgradable TPM designations to guide buyers assessing quantum-safe hardware.

The Trusted Computing Group published requirements establishing PTP 1.07, based on TPM 2.0 Library Specification Version 1.85, as the baseline for a 'TCG PQC-ready TPM', and defined a second designation, 'TCG PQC-upgradable TPM', for chips that can be upgraded to that support. The guidance lets buyers request vendor evidence that TPMs meet end-to-end post-quantum requirements for identities, attestation, and hardware-anchored trust rather than single-algorithm compliance. TCG also announced plans to extend its certification programs to certify TPMs meeting PTP 1.07, noting that 90% of businesses still lack a formal PQC roadmap.

Help Net Security·Aug 25, 00:00 UTC · 22d agoTools

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12 Best CASB Solutions Compared (2026): Features & Pricing

GBHackers' 2026 buyer's guide compares 12 CASB-capable vendors, arguing standalone CASB pricing has dissolved into per-user SSE subscriptions.

The article evaluates twelve CASB-capable platforms including Microsoft Defender for Cloud Apps, Palo Alto Networks' Prisma Access CASB, Netskope, iboss, Forcepoint ONE (Bitglass), Trend Micro Cloud App Security, and Skyhigh Security. It frames purchasing around SSE bundle economics, noting Defender for Cloud Apps ships inside Microsoft 365 E5 while Netskope, Zscaler, and Skyhigh price CASB into per-user SSE tiers. It also flags Saviynt, common on legacy roundups, as an IGA vendor rather than a true CASB.

GBHackers·updated 09:00 UTC · 47m ago·first 07:31 UTC · 2h agoIndustry 11 sources

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

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

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

Hugging Face daily papers·Sep 8, 20:00 UTC · 7d agoAI research

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Top 10 Best Device Control & USB Security Tools in 2026

A 2026 scorecard ranks ten USB and device control tools, placing Safetica, Ivanti DeviceLock and DriveLock at the top.

The article compares ten device control and USB security tools using a weighted scorecard covering control granularity, platform coverage, DLP integration, operability and value. Safetica, Ivanti DeviceLock and DriveLock rank highest, with notes on cross-platform depth, Windows granularity and European compliance fit. The piece highlights ownership changes, including CoSoSys joining Netwrix and Digital Guardian joining Fortra, and stresses device control as part of Zero Trust and DLP strategies.

Cyber Security News·Sep 10, 08:05 UTC · 6d agoIndustry

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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·Sep 8, 17:25 UTC · 7d agoAI research

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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·Sep 2, 20:00 UTC · 13d agoAI research

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Verify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation

TGOPD verifies teacher reliability per prompt before on-policy distillation, outperforming vanilla OPD across math, code, and instruction benchmarks.

Teacher-Gated On-Policy Distillation (TGOPD) estimates teacher reliability from verifier-scored teacher probes and routes each prompt either to dense on-policy distillation or to verifier-grounded GRPO, avoiding misleading updates from confidently wrong teachers under mode-seeking reverse KL. Across 4B and 35B students in mathematics, code, and instruction following, TGOPD outperforms vanilla OPD in all six single-domain settings and achieves higher seven-benchmark averages under multi-domain training. It also raises teacher-node GPU utilization from 9.8% to 78.9% in the measured 4B single-domain run by reusing idle teacher capacity.

Hugging Face daily papers·Sep 1, 20:00 UTC · 14d agoAI research

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

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

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

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

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PlannerForge: LLM Agents for Scenario-Based Testing of Motion Planners in Autonomous Driving

PlannerForge unifies scenario-based testing of autonomous driving motion planners in one LLM-agent framework, outperforming prior baselines.

PlannerForge is an LLM-agent framework that covers the full scenario-based testing pipeline for autonomous driving systems, spanning scenario generation, selection, modification, routing, planner testing, plus new enhancement and benchmarking stages. In evaluations with 10 off-the-shelf LLMs, best-per-task scores range from 0.88 to 1.00, and open-source 20-35B backends such as Qwen3.6:35B match commercial APIs on most tasks. End-to-end chaining retains 83% (commercial) and 78% (open) of seed queries, beats Scenario Factory 2.0 on executable generation, and cost-tuning lifts planner success from 50.4% to 70.2% while cutting collisions from 19.0% to 8.4%.

Hugging Face daily papers·Sep 7, 20:00 UTC · 8d agoAI research

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5 useful things you'll learn in my new post-training textbook (shipping now!)

Nathan Lambert's new RLHF and post-training LLM textbook covers PPO, GRPO, GSPO, CISPO and related techniques, freely available online.

Nathan Lambert's book 'Reinforcement Learning from Human Feedback: Aligning and Post-training LLMs' is now shipping from Manning. It covers policy-gradient algorithms including PPO, GRPO, GSPO, CISPO, and RLOO, plus loss aggregation, truncated importance sampling, asynchronous RL systems, and post-training topics like rejection sampling, outcome reward models, and on-policy distillation. The book is freely available online with a 12-hour course, codebase, and exercises.

Interconnects·Aug 10, 13:02 UTC · Aug 10, 2026AI research

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New Guidance Helps Businesses Verify Quantum-Safe Hardware Claims

TCG issued guidance to help businesses verify that trusted platform modules genuinely meet quantum-safe requirements.

The Trusted Computing Group (TCG) published new guidance aimed at proving that trusted platform modules (TPMs) genuinely satisfy essential quantum-safe requirements. The document gives businesses a way to validate vendor claims about post-quantum readiness in hardware security rather than trusting marketing assertions. This is a guidance publication, not an incident or vulnerability disclosure.

Infosecurity Magazine·Aug 24, 16:00 UTC · 22d agoAdvisory

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

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

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

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:32 UTC · 11d agoAI research1

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

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

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

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:59 UTC · 8d agoAI research

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Before You Poll with LLMs: A Deliberative Diagnostic Framework

Deliberative diagnostic shows all five tested frontier LLMs misrepresent human belief shifts after arguments, with GPT-5.1 reversing on outgroup questions.

The Deliberative Polling Diagnostic Framework compares human and LLM persona belief shifts after identical informational interventions, using data from America in One Room (526 personas, 72 questions). All five frontier models tested failed uniquely: GPT-5.1 exhibited partisan reversal (80% on outgroup vs 26% on policy questions), Gemini 2.0 Flash, Claude Sonnet 4.5 and Llama 3.3 70B overshot at 5-7x human magnitude, and DeepSeek V3 showed near-zero change (rigidity). The authors term the underlying signature 'self-sycophancy', conformity to the model's internal persona stereotype rather than reasoning from provided information.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 16:41 UTC · 1d agoAI research

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Lightweight Vision Transformer Compression for On-Device Plant Disease Detection in Resource-Constrained Agricultural Field Conditions

A unified ViT compression pipeline (H-BAC pruning, quantization, distillation) cuts plant-disease models 54.5x to 6.01 MB while keeping 95.13% accuracy.

Researchers combined Hessian-Balanced Adaptive Block Pruning (H-BAC), guided by second-order sensitivity estimation, with quantization and attention-based knowledge distillation to compress Vision Transformers for on-device chilli plant disease detection in India. On a 3-class cross-village, cross-device out-of-distribution dataset, the integrated pipeline reduced model size from 327.42 MB to 6.01 MB (54.5x) at 95.13 +/- 2.32% accuracy, matching the 95.13% FP32 baseline. Ablations also show a directly trained 6.01 MB INT8 student reaches 94.87% accuracy, indicating where pruning and distillation add limited value.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 16:40 UTC · 11d agoAI research

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You Can't Prefer Emotions You Don't Sample: Intensity Undershoot in DPO-Tuned LLMs

Study quantifies DPO-tuned LLMs undershooting requested emotional intensity, tracing the gap to candidate-pool extremity rather than conditioning format.

Conditioning an instruction-tuned LLM on continuous valence-arousal targets yields gain of only 0.26 for valence and 0.13 for arousal on Llama-3.1-8B, far below faithful control of 1.0. The authors attribute undershoot to neutral-heavy preference corpora like EmoBank and candidate pools lacking extreme affect, leaving DPO without extreme exemplars. Uniform target coverage with a hotter candidate pool raises valence gain to 0.40 on Llama-3.1-8B and 0.44 on Qwen3-8B, with modest in-distribution cost; arousal gains remain unstable across seeds.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:47 UTC · 8d agoAI research

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Emergency Department Revisit Quality Review Screening: Exploring Human Decision-Making and Artificial Intelligence Support

A retrospective study found GPT-4 over-flagged emergency department revisit cases while an LLM knowledge-graph screener achieved 83-100% positive predictive value.

In an exploratory retrospective study of 99 emergency department diagnosis pairs from a multihospital health system, clinicians and GPT-4 independently judged whether revisit pairs warranted further assessment. GPT-4 responses correlated poorly with clinicians, flagging 94% of pairs for follow-up, 4.4-13.3 times more than clinicians, though prompt engineering was minimal. An algorithm leveraging an LLM-populated knowledge graph (KGA) achieved 83-100% positive predictive value against at least one clinician rater, suggesting LLM-based screening could broaden revisit quality review without substantially increasing reviewer workload.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 16:37 UTC · 6d agoAI research1

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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·Sep 11, 17:11 UTC · 4d agoAI research2

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Best Practices for Good Endpoint Hardening | Huntress

Huntress outlines endpoint hardening best practices, citing exposed RDP, RMM tool abuse, and ClickFix social engineering as common SMB intrusion paths.

Huntress published defensive guidance on endpoint hardening for small and mid-sized businesses, drawing on observations from its SOC. The post describes common intrusion vectors: internet-exposed RDP brute-forced by automated scanners, phishing emails delivering attacker-controlled remote monitoring and management (RMM) tools, with Huntress reporting a 277% spike in RMM abuse in 2025, and ClickFix attacks using fake CAPTCHA pages that trick users into running malicious commands. Recommended controls include scanning for exposed RDP, SSH, and VPN interfaces, removing unneeded local admin rights, enabling Windows Defender tamper protection, disabling SMBv1, and standardizing on one approved remote access tool, guided by CIS and NIST frameworks.

Huntress·Sep 10, 15:00 UTC · 5d agoAdvisory

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Decomposition-Guided Diffusion Language Models for Inertial Confinement Fusion Prediction

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

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

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:00 UTC · 8d agoAI research

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Graph Machine: Towards Better Pretraining via Edges

Researchers propose Graph Machine, an O(n)-state sparse architecture that replaces 75% of Qwen3-0.6B dense layers with only slight loss change.

The paper introduces the Graph Machine (GM), an architecture that maintains an O(n)-sized state accessed through sparse, dynamic routing via pointer-like edges updated differentiably by a referral mechanism resembling pointer chasing. The authors replaced 75% of dense Transformer layers in Qwen3-0.6B with GM sparse layers and pretrained from scratch on 15.7B tokens. Retrieving 2 of 4,096 tokens per KV head in each sparse layer degrades loss only slightly, while retrieving 4 marginally improves loss over the dense baseline.

Hugging Face daily papers·Sep 1, 20:00 UTC · 14d agoAI research

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RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

RoboSPA introduces a 527K-trajectory benchmark with 280 task variants showing current VLA models struggle with spatial reasoning and long-horizon planning.

RoboSPA is a large-scale robotic manipulation dataset and benchmark for diagnosing embodied reasoning in vision-language-action models, covering fine-grained spatial reasoning and long-horizon procedural planning. It spans 10 task categories and 56 base tasks instantiated across five difficulty levels for 280 variants, with 527K trajectories collected across multiple embodiments and diverse scenes. Diagnostic metrics go beyond binary success rates, and experiments show current VLA models struggle with complex spatial relations, precise low-level execution, and memory-intensive planning.

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

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