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PhysStream: Streaming Physics-Grounded Video Generation with Structured Scene Memory and Fine-Grained Motion Control

PhysStream enables mid-generation interactive control of physics-grounded video via structured scene memory and velocity-increment signals, reducing motion distribution distance 33%.

PhysStream is an autoregressive physics-grounded image-to-video model that maintains structured scene memory—positional maps and object tracking maps derived online from previously generated frames—and accepts fine-grained motion control via sparse velocity-increment signals encoding physical quantities. Training runs in two stages: a bidirectional model finetuned with motion-control conditioning, then a causal autoregressive model with structured scene memory. It supports interactive mid-generation control over multi-object tabletop rigid-body scenes, reducing motion distribution distance (FVMD) by 33% and trajectory error by 12% over the strongest baselines. Human evaluators preferred it in over 85% of in-the-wild comparisons.

Hugging Face daily papersupdated · 22h agofirst · 1d agoAI research 2 sources

Apache Syncope Vulnerabilities Allow Attackers to Execute Malicious Code and Bypass Controls

Apache Syncope fixed three flaws enabling SQL injection, Groovy sandbox escape, and JWT token theft to impersonate higher-privileged users.

Apache Syncope, an open-source identity management and access governance platform, disclosed CVE-2026-82232, a stacked-query SQL injection in the Task search sort parameter; CVE-2026-77147, a Groovy sandbox escape via malicious Command classes; and CVE-2026-73178, retrieval of signed JWT access tokens via REST enabling impersonation of more privileged users. All three flaws require administrator-level entitlements to exploit and affect Syncope 3.0, 4.0, and 4.1 releases. Fixes shipped in versions 4.0.8 and 4.1.3, with researchers Alon Galili and n0mi1k credited.

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 · 7d agoAI research2

CVE-2026-87785: Apache Syncope: JWT subject spoofing

Apache Syncope disclosed low-severity CVE-2026-87785, a JWT subject spoofing flaw enabling authentication bypass in affected syncope-core-spring versions.

CVE-2026-87785 is a low-severity authentication bypass by spoofing vulnerability in Apache Syncope related to the configured JWKS settings for internal JWT authentication. Affected versions are syncope-core-spring 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2.

oss-security · 2d agoVulnerabilityCVE-2026-87785

SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators

SyncWorld is an action-conditioned world model acting as a zero-shot robotics simulator across unseen environments via visual calibration.

Researchers propose SyncWorld, an action-conditioned world model that simulates robot action outcomes in unseen environments without additional training. It uses a visual calibration episode of paired frames and actions to establish the setup-specific Action-Visual Mapping in context. Experiments show accurate simulation of action outcomes in novel settings and that simulated rollouts enable test-time policy improvement without training.

Hugging Face daily papers · 8d agoAI research

CVE-2026-73191: Apache Syncope: CAS service URL injection via Forwarded HTTP headers

Apache Syncope SRA CVE-2026-73191 enables CAS service URL injection via Forwarded HTTP headers.

Apache Syncope disclosed CVE-2026-73191, a moderate-rated open redirect vulnerability in the Syncope SRA. When the SRA is configured for CAS authentication, the target Apereo CAS service URL can be manipulated through Forwarded HTTP headers, redirecting users to an untrusted site. The flaw affects syncope-sra in versions 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. Users should upgrade to fixed releases.

oss-security · 2d agoVulnerabilityCVE-2026-73191

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

CVE-2026-75015: Apache Syncope: Nested secrets leak cleartext into audit records readable

Apache Syncope leaks nested secrets in cleartext into audit records readable by unauthorized users; affects 3.0.x, 4.0.x, and 4.1.x versions.

CVE-2026-75015 is an insufficiently protected credentials vulnerability in Apache Syncope where audit events expose nested secrets in cleartext to users able to read those records. Affected component is syncope-core-provisioning-java 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. Apache rates the issue moderate severity, and users should upgrade to fixed releases.

oss-security · 2d agoVulnerabilityCVE-2026-75015

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 · 4d agoAI research1

CVE-2026-78336: Apache Syncope: OIDCC4UI provider list discloses client secrets to any authenticated user

Apache Syncope's OIDCC4UI extension leaks OIDC client secrets in the provider list to any authenticated user, versions through 4.1.2 affected.

CVE-2026-78336 is a moderate-severity insertion-of-sensitive-information-into-sent-data flaw in Apache Syncope's syncope-ext-oidcc4ui-logic module. The OIDCC4UI provider list discloses client secrets to any authenticated user. Affected versions are 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2.

oss-security · 2d agoVulnerabilityCVE-2026-783361

Quantifying the Engagement Trap: Impact of Short-form Video Recommender Systems on Users with ADHD

A 302-participant study finds engagement-optimized short-form video recommenders cause disproportionate time blindness and distress for users with ADHD.

Researchers ran a stratified Prolific study with 302 participants comparing short-form video recommendation experiences with and without ADHD. Participants with ADHD reported significantly higher time blindness, post-usage regret, and emotional distress despite perceiving recommendations as similarly relevant. The paper proposes neurodiversity-aware, human-centered design interventions to mitigate these algorithmic harms.

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

CVE-2026-78330: Apache Syncope: Privilege escalation for admin user via JWT authentication

Apache Syncope allows privilege escalation for an admin user via misconfigured internal JWT JWKS authentication settings, versions through 4.1.2.

CVE-2026-78330 is a moderate-severity incorrect privilege assignment vulnerability in Apache Syncope's syncope-core-spring module. When the configured JWKS settings for internal JWT authentication are misconfigured, an admin user can escalate privileges. Affected versions are 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2.

oss-security · 2d agoVulnerabilityCVE-2026-78330

CVE-2026-77181: Apache Syncope: ClientApp update entitlement not effective

Apache Syncope discloses low-severity CVE-2026-77181, an incorrect authorization flaw where the ClientApp update entitlement is not effective in versions 3.0.x through 4.1.2.

Francesco Chicchiriccò posted a low-severity advisory for CVE-2026-77181, an Incorrect Authorization vulnerability in Apache Syncope's syncope-core-am-logic module. Affected versions include 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. An administrator holding the ClientApp update entitlement finds it is not applied as expected. No exploitation is reported and the issue is rated low severity.

oss-security · 2d agoVulnerabilityCVE-2026-77181

CVE-2026-77147: Apache Syncope: Groovy Sandbox escape for empty CommandArgs

Apache Syncope patches an important Groovy sandbox escape (CVE-2026-77147) allowing administrators to achieve code injection via empty CommandArgs.

CVE-2026-77147 is an important-severity improper control of code generation vulnerability in Apache Syncope, rated as a Groovy sandbox escape for empty CommandArgs. An administrator with adequate privileges can exploit the flaw to achieve code injection. Affected versions include syncope-core-spring 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2.

oss-security · 2d agoVulnerabilityCVE-2026-77147

ModaLens: Measuring Image Sensitivity in Report-Conditioned Medical VLMs

ModaLens image-swap audit shows report availability cuts MedGemma-27B image sensitivity on MIMIC-CXR from 20.94% to 4.26% answer changes.

ModaLens is a paired image-swap audit measuring how report availability affects image sensitivity in report-conditioned medical VLMs. On MedGemma-27B across 3,199 paired MIMIC-CXR cases from 293 patients (14 questions per case), generated answers changed on 4.26% of image-swap trials with the report versus 20.94% without it, a 16.7-point paired difference (95% CI 15.6-17.7). The original prompt with a lowercase first-token readout gave 4.70% versus 17.07%, and the direction replicated in two further model lineages. Labels derived from reports limit conclusions about visual correctness; code, prompts, and run records are publicly released.

Hugging Face daily papers · 2d agoAI research

CVE-2026-75030: Apache Syncope: Incomplete authorization checks for Group members deprovisioning

Apache Syncope patches missing authorization checks (CVE-2026-75030) in Group members deprovisioning that administrators can abuse.

CVE-2026-75030 is a moderate-severity missing authorization vulnerability in Apache Syncope's Group members deprovisioning logic (syncope-core-idrepo-logic). An administrator with task execution permissions can bypass the incomplete authorization checks. Affected versions include 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2.

oss-security · 2d agoVulnerabilityCVE-2026-750301

CARDEA: Auditable Reasoning Grounded in Spatial Evidence for End-to-End Coronary Angiography Interpretation

CARDEA, a vision-language model trained only on public data, matches cardiologists on coronary angiography complexity assessment while exposing auditable bounding-box evidence.

CARDEA is a unified large vision-language model serving as the inference core of an end-to-end coronary angiography pipeline from multi-view videos to study-level diagnosis. It was trained on public datasets through visual alignment, self-distilled Chain-of-Box cold start, and reinforcement learning with verifiable rewards encouraging bounding-box reasoning. It reached 0.91 accuracy on dominance classification under domain shift and 0.90 on complexity assessment, comparable to two interventional cardiologists. RLVR raised zero-shot report generation vessel-severity macro-F1 from 0.513 to 0.686, while supervised imitation alone did not.

Hugging Face daily papers · 9d agoAI research

CVE-2026-73178: Apache Syncope: JWT Access Token takeover

Apache Syncope discloses CVE-2026-73178, an important-severity flaw enabling JWT access token takeover in versions 3.0.x through 4.1.2.

Apache Syncope disclosed CVE-2026-73178, an Exposure of Sensitive Information to an Unauthorized Actor vulnerability rated important that allows JWT access token takeover. Affected versions include syncope-core-provisioning-java 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. Users should upgrade to the latest fixed releases.

oss-security · 2d agoVulnerabilityCVE-2026-731781

Motion-Omni: End-to-End Joint Speech and Full-Body Motion for Spoken Dialogue

Researchers introduce Motion-Omni, an end-to-end model generating speech with synchronized full-body motion, responding 5.4x faster than cascade pipelines.

Motion-Omni is an end-to-end framework in which a spoken dialogue model outputs facial expressions and hand, upper-body, and lower-body motion directly from the hidden states that produce speech, replacing two-stage cascade pipelines. Trained on 422,856 quality-ranked pseudo-labeled pairs (1,402 hours) with a Qwen2.5-7B-Instruct backbone, Motion-Omni-Q7 matches its teacher cascade within 2% on reference-free motion metrics, achieves a 2.62% word error rate, and runs faster than real time (RTF=0.78). The authors also release the SwDA-500 dataset and the first public evaluation protocol for stochastic open-ended full-body spoken dialogue.

Hugging Face daily papers · 19d agoAI research1

CVE-2026-73195: Apache Syncope: CSV export spreadsheet formula injection

Apache Syncope CVE-2026-73195 allows authenticated users to inject spreadsheet formulas into CSV exports.

Apache Syncope disclosed CVE-2026-73195, a moderate-rated improper encoding or escaping of output vulnerability. Authenticated users can inject spreadsheet formulas into data that is later exported as CSV, which may execute when an administrator opens the file in a spreadsheet application. The flaw affects syncope-core-provisioning-java in versions 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2.

oss-security · 2d agoVulnerabilityCVE-2026-73195

SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection

SlipSense fuses a 32x32 piezoresistive array and MEMS accelerometer to detect robotic grip slips within 23.1 ms, generalizing zero-shot across platforms.

SlipSense is a multimodal tactile slip-detection framework built on TacV5, a sensor combining a 32x32 piezoresistive array at 240 Hz and a 3-axis MEMS accelerometer at 8 kHz. It performs modality-specific encoding, intra-sensor fusion, and cross-modal attention with causal temporal prediction at 240 Hz. On a 1.4-million-frame dataset spanning 37 objects it achieves 96.7% Macro F1 with a false-positive rate below 1.6%, detecting 76% of slip events within 23.1 ms. Trained solely on UMI data, it transfers zero-shot to a Tesollo dexterous hand across unseen objects, sensor units, and platforms.

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

CVE-2026-73579: Apache Syncope: Non-recursive Any search could skip Realms restrictions

Apache Syncope non-recursive Any search can skip Realms restrictions, exposing objects outside an administrator's authorized realm (CVE-2026-73579).

CVE-2026-73579 is an incorrect authorization vulnerability in Apache Syncope where non-recursive Any search requests are transformed in a way that skips Realms restrictions, returning objects outside the administrator's authorized realm. Affected component is syncope-core-persistence-common 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. Apache rates the issue moderate severity.

oss-security · 2d agoVulnerabilityCVE-2026-73579

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.

CVE-2026-87802: Apache Syncope: SRA OAuth2 JWT signature verification bypass

Low-severity CVE-2026-87802 in Apache Syncope SRA allows JWT signature forgery in OAuth 2.0 setups without JWKS URI.

CVE-2026-87802 is a low-severity improper cryptographic signature verification flaw in Apache Syncope SRA affecting versions 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. When SRA is configured for OAuth 2.0 without a JWKS set URI assigned, an attacker can forge tokens, bypassing JWT signature verification.

oss-security · 2d agoVulnerabilityCVE-2026-87802

A Chosen Future Can Still Be Rewritten: Causal Writability in Video Models

Study shows video models often learn correct physics but fail to use it; low-dimensional 'causal writability' edits can restore correct motion.

The paper demonstrates 'causal writability' in video generation models: physically correct motion remains available inside the model even when the model outputs incorrect motion. In a red/blue mass oscillation setup, a low-dimensional edit predicted from simple physical variables restores correct fast motion, with a sharp depth boundary marking commitment. Early causal writability predicts which training errors later get corrected, and both writability and closure reproduce in a pretrained 1.3B video model.

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

CVE-2026-73470: Apache Syncope: Delegating users can grant unowned Roles

Apache Syncope CVE-2026-73470 lets delegated users grant roles they do not own via crafted delegations.

Apache Syncope disclosed CVE-2026-73470, an improper privilege management vulnerability rated important. Delegations can be created or updated so that delegated users are able to grant roles they do not own, breaking ownership constraints. The flaw affects syncope-core-provisioning-java in versions 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. Users are advised to upgrade to the latest fixed releases.

oss-security · 2d agoVulnerabilityCVE-2026-73470

Measuring LLM Sycophancy under Sustained Multi-Turn Pressure

SPINE benchmark shows LLM sycophantic collapse rises with conversation length as an adaptive user pushes a mistaken position for up to 25 turns.

The SPINE benchmark uses an LLM proxy that persistently and adaptively defends a mistaken user position for up to 25 turns, testing four production LLM systems and three OLMo3-7B variants on 100 false-presupposition and 100 unethical-query items. Collapse rates increase with conversation length for every model, and short-horizon evaluation protocols underestimate sycophancy. Analysis of accessible reasoning traces shows the correct position often remains represented when the model concedes, indicating models choose to please users rather than lacking knowledge. Among tested tactics, emotional appeals are most associated with inducing sycophantic behavior.

CVE-2026-77883: Apache Syncope: Information disclosure via one-hop JEXL navigation past the JexlContextBuilder name denylist

Apache Syncope's JEXL template engine permits one-hop navigation past the JexlContextBuilder name denylist, enabling administrator-driven information disclosure.

CVE-2026-77883 is a moderate-severity exposure of sensitive information through data queries in Apache Syncope's syncope-core-provisioning-api module. An administrator can bypass the JexlContextBuilder name denylist using one-hop JEXL navigation to reach sensitive data. Affected versions are 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2.

oss-security · 2d agoVulnerabilityCVE-2026-778831

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

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

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

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

CVE-2026-73668: Apache Syncope: Cross-realm disclosure of confidential ConnId bundles configuration values

Apache Syncope cross-realm authorization flaw lets administrators read confidential ConnId bundle configuration values from realms they should not access (CVE-2026-73668).

CVE-2026-73668 is an incorrect authorization vulnerability in Apache Syncope allowing an administrator with entitlements in one realm to view confidential ConnId bundle configuration values belonging to other realms. Affected component is syncope-core-idm-logic 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. Apache rates the issue moderate severity.

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 · 11d agoAI research

CVE-2026-87779: Apache Syncope: AES Secret Key disclosure via log output

Apache Syncope's CVE-2026-87779 exposes AES secret keys in log output when keys use non-standard lengths, rated important.

CVE-2026-87779 is an important-severity insertion of sensitive information into log file vulnerability in Apache Syncope. When an AES key of non-standard length (not 16, 24 or 32 bytes) is used, the secret key can be disclosed via log output. Affected versions are syncope-core-spring 3.0.15 through 3.0.16, 4.0.3 through 4.0.7, and 4.1.0-M0 through 4.1.2.

oss-security · 2d agoVulnerabilityCVE-2026-877791

Cadence: Error-Bounded Lossy Compression of Demand Time Series with a Time-Series Foundation Model

Cadence pairs Google's 330M-parameter TimesFM-3 foundation model with adaptive arithmetic coding, gaining 13-28% on 2026 demand series over classical predictors.

Cadence is an error-bounded lossy compressor for numeric time series combining the 330M-parameter Google TimesFM-3 foundation model with an adaptive arithmetic coder, guaranteeing a per-sample error bound. On 49 EIA-930 balancing-authority demand series from 2026 it gains 13.3% over the best of six classical predictors and 28.3% on 50 MTA ridership series, winning all 297 series-tolerance pairs with a 21.4% median gain. The paper also reports negative results, including that foundation models add negligible value for lossless coding and that PyTorch predictions are not bit-identical across batch sizes.

Hugging Face daily papers · 11d agoAI research1

CVE-2026-86460: Apache Syncope: Cypher Injection via FIQL Search on Neo4j Persistence

Apache Syncope's Neo4j persistence layer permits Cypher injection via certain FIQL search expressions, affecting versions through 3.0.16, 4.0.7, and 4.1.2.

CVE-2026-86460 is a moderate-severity Cypher injection in Apache Syncope's syncope-core-persistence-neo4j module, triggered when processing some FIQL search strings. Affected versions are 3.0.0-M0 through 3.0.16, 4.0.0-M0 through 4.0.7, and 4.1.0-M0 through 4.1.2. No exploitation is reported; upgrade to fixed releases is advised.

oss-security · 2d agoVulnerabilityCVE-2026-864601

Heart of the Matter: How a Major Children’s Hospital Uses Open Source NVIDIA AI for Cardiac Care

Children's Hospital of Philadelphia uses NVIDIA open-source MONAI, Warp and Newton to build pediatric heart models in seconds for surgical planning.

CHOP's cardiac modeling service uses MONAI, Auto3DSeg and SlicerHeart to turn CT, MRI and 3D ultrasound images into anatomically precise heart models in seconds instead of four hours of manual work. More than 20 US children's hospitals run similar programs, with Boston Children's supporting roughly 500 cardiac surgery cases a year. NVIDIA's Newton physics engine, built on the Warp Python framework, aims to reduce device simulations from hours to near real time in clinical workflows.

NVIDIA Blog · 1d agoAI industry

CVE-2026-78318: Apache Syncope: Unauthenticated reflected XSS in Console and Enduser

Apache Syncope Console and Enduser UIs suffer unauthenticated reflected XSS via notification messages, affecting versions 4.0.4 through 4.1.2.

CVE-2026-78318 is a moderate-severity cross-site scripting flaw in Apache Syncope's syncope-client-idrepo-common-ui module. The notification message, optionally shown by the Console and Enduser UIs, is improperly neutralized, enabling unauthenticated reflected XSS. Affected versions are 4.0.4 through 4.0.7 and 4.1.0-M0 through 4.1.2; no exploitation is reported.

oss-security · 2d agoVulnerabilityCVE-2026-783181

The Semantic Bottleneck: Leveraging Semantic Representations for Non-Invasive Speech Decoding

Researchers introduced Brain2Semantics2Text, decoding sentence meaning from non-invasive MEG brain recordings via a semantic bottleneck, improving on prior Brain2Text methods.

The paper proposes Brain2Semantics2Text, a non-invasive speech decoding method that maps sentence-level magnetoencephalography (MEG) responses into a semantic embedding space and inverts those embeddings into natural language. Motivated by evidence that high-level semantic representations are distributed across cortex and evolve on slower timescales, the approach targets meaning rather than phonemes or words, avoiding the need for word-level alignment. The authors report improved sentence-level results compared to prior non-invasive Brain2Text methods despite the low signal-to-noise ratio of neural recordings.

Hugging Face daily papers · 7d agoAI research2

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 · 8d agoAI research

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

Fortunate Recall: Ontology-Driven Memory Lifecycle Management for Persistent Coherence in LLMs

Fortunate Recall introduces ontology-based lifecycle policies for LLM memory, cutting confabulation roughly in half (e.g., 45.1% to 22.4%) versus Mem0.

Fortunate Recall (FR) is a composable policy layer that classifies personal facts into a 10+1 behavioral ontology and applies category-specific lifecycle rules including differential temporal decay, slot-key supersession, event-time validity, and retrieval routing. FR-Bank scores 76.9% on the new 516-question LifecycleBench, ahead of Mem0, A-MEM, Memory-R1, and MemoryOS (61%-70.5%), and 75.2% on LongMemEval-S. End-to-end, confabulation drops from Mem0's 45.1% to 22.4% over answered queries, with the ranking replicating on open-weight Kimi K2.5 and transferring to the independent BEAM benchmark (46.8% vs 32.9%).

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