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CategoryAll Vulnerability 207 Exploit / PoC 43 Ransomware 38 Malware 16 Industry 14 Policy & legal 11 Advisory 8 Threat actor 5 Tools 3 AI safety & security 2 Phishing & fraud 2 AI tools & infra 2 AI industry 1 AI research 1

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VC-Attention: Value Smoothing and Softmax Casting for Low-bit Attention

VC-Attention is a training-free low-bit attention method for diffusion transformers, achieving 1.46-1.59x kernel speedups on datacenter GPUs with higher fidelity.

VC-Attention is a training-free low-bit attention framework for diffusion transformers that pairs V-Smooth value smoothing via lightweight online clustering with ExpCast-FP8, which maps log-domain scores directly to E4M3 FP8 probability codes and eliminates the FP32 softmax exponential. It is implemented for B200, B300, H200, RTX PRO 6000, and RTX 5090 GPUs. Across Wan2.2, LongCat-Video, HunyuanVideo-1.5, and MiniMax-H3, it improves fidelity over low-bit baselines and speeds attention 1.46-1.59x over BF16 FlashAttention-4 on datacenter Blackwell and Hopper GPUs and 2.3-3.6x on workstation cards, with 1.13-1.70x faster end-to-end clip generation.

Hugging Face daily papersupdated 00:45 UTC · 13h agofirst Sep 13, 20:00 UTC · 3d agoAI research 2 sources

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 Sep 15, 17:55 UTC · 1d agofirst Sep 14, 20:00 UTC · 2d agoAI research 2 sources

Microsoft Patch Tuesday, September 2026 Security Update Review

Microsoft's September 2026 Patch Tuesday fixes 974 vulnerabilities, including 113 critical and two actively exploited Windows privilege escalation flaws.

Microsoft's September 2026 Patch Tuesday fixes 974 vulnerabilities, its largest release ever, including 113 critical and 860 important, covering Windows HTTP.sys, Hyper-V, Entra ID, Exchange Server, Office, DNS, and more. Two zero-days are confirmed exploited in the wild: CVE-2026-81963 (Windows Update Stack EoP) and CVE-2026-85880 (ALPC heap overflow), both letting authenticated attackers gain SYSTEM privileges. Notable criticals include an Entra ID authentication bypass (CVE-2026-62916) and multiple Windows DNS Server and Office remote code execution flaws.

Qualys ThreatPROTECTSep 9, 12:23 UTC · 8d agoVulnerability in the wildCVE-2026-81963 CVE-2026-85880 CVE-2026-58599+27 CVEs

OpenVDN/vdn-minimax-h3 — new model trending #12 on Hugging Face

OpenVDN releases VDN-H3, an open hybrid-attention video model on MiniMax H3 that renders a 14.4-second 768p clip in 11.23 seconds on 8 B200 GPUs.

VDN-Minimax-H3 (VDN-H3) adds a frame-wise linear attention branch plus two LoRA adapters to MiniMax H3, distilled into 8-step and 50-step variants. It generates 768p, 14.4-second clips in 11.23 seconds on 8 B200 GPUs (90.5 seconds on one H200) using 8 denoising steps. Weights (about 82 GB total, including the 72 GB H3 base), the optimized inference stack, and training code are fully open-source under the MiniMax H3 Community License, which excludes the EU, UK, Korea, and US.

Hugging Face trending modelsSep 2, 05:03 UTC · 15d agoModel release1

Microsoft releases emergency Windows updates to fix RDS failures

Microsoft released emergency out-of-band Windows updates fixing Remote Desktop Services failures and Hyper-V issues caused by September 2026 security patches.

Microsoft issued out-of-band updates on September 14, 2026 to fix Remote Desktop Services instability introduced by the September security updates, which caused RDP connection and sign-in failures and unresponsive servers. Updates include KB5129194 (Windows 11 26H1), KB5129195 (Windows 11 24H2/25H2), KB5129236 (Windows 10), KB5129235 (Windows Server 2025), and KB5129237 (Windows Server 2022). The Windows 11 updates also fix a Hyper-V Plan9 shared folder issue and some USB Audio Class 1.0 multichannel problems, though remaining USB audio issues await a fix. Admins had previously used Group Policy mitigations or uninstalled the security updates, which removed security protections.

BleepingComputerupdated Sep 15, 08:40 UTC · 2d agofirst Sep 14, 20:52 UTC · 2d agoAdvisory 3 sources2

The September 2026 Security Update Review

ZDI's September 2026 Microsoft update review lists two already-exploited Windows EoP zero-days and dozens of critical RCEs across Office, SQL Server, and Windows services.

The review catalogs Microsoft's September 2026 fixes, marking CVE-2026-85880 (Windows ALPC) and CVE-2026-81963 (Windows Update Stack) as already exploited elevation-of-privilege issues. It also lists critical RCE flaws in Office, Word, Excel, PowerPoint, Outlook, SQL Server, Windows DNS, DHCP and Failover Cluster, plus graphics component RCEs. Azure-side fixes include Entra ID, Copilot Studio, Azure AI Language and Azure AD B2C elevation-of-privilege flaws.

Zero Day Initiative BlogSep 8, 18:32 UTC · 8d agoAdvisory in the wildCVE-2026-85880 CVE-2026-81963 CVE-2026-70352+27 CVEs1

Comprehensive reconstruction of collider events with hypergraph representation learning and graph-conditioned diffusion

VyPER framework reconstructs collider events using hypergraph representation learning and graph-conditioned diffusion, outperforming existing reconstruction techniques across Standard Model processes.

Researchers present VyPER, a geometric learning framework that represents collider events as hypergraphs with a physics-inspired topology for particle event reconstruction. It combines supervised hyperedge classification for assigning measured jets and charged leptons to parent particles with a graph-conditioned diffusion model predicting unmeasured neutrino kinematics, optimized with a joint loss. Evaluated across several proton-proton collision processes, it demonstrates accurate reconstruction across Higgs, electroweak, and top-quark sectors.

arXiv cs.AI / cs.LG / cs.CLSep 16, 17:03 UTC · 20h agoAI research

VU#687587: AOMEI Backupper amwrtdrv.sys local privilege escalation vulnerability allows arbitrary writes to physical disks

AOMEI Backupper 8.4.0 driver flaw CVE-2026-12780 lets unprivileged users write physical disks and execute UEFI code, bypassing HVCI and EDR.

CERT/CC issued VU#687587 for CVE-2026-12780, an incorrect permission assignment (CWE-732) in the amwrtdrv.sys kernel driver shipped with AOMEI Backupper 8.4.0. The driver exposes a world-accessible device object without a security descriptor, allowing any unprivileged user to write arbitrary physical disk sectors; with Secure Boot disabled, an attacker can modify the GPT and inject a UEFI payload that executes before the OS loads, bypassing HVCI, EDR, Windows Defender and Hyper-V isolation. On TPM-only BitLocker configurations the attack can capture Volume Master Key material during pre-boot. AOMEI has shipped patches; users who cannot update should uninstall the software or disable the amwrtdrv.sys service, and enabling Secure Boot adds defense in depth.

CERT/CC Vulnerability NotesSep 10, 17:46 UTC · 6d agoVulnerability CVE-2026-127801

Miles v0.1: Production-Level Post-Training

Radix Ark open-sources Miles v0.1, a full-stack RL post-training framework demonstrated with asynchronous agentic RL on GLM-5.2 744B-A40B across 64 GB300 GPUs.

Miles v0.1 is a full-stack, open-source system for frontier-scale reinforcement-learning post-training, built on slime with rollout engines on SGLang and trainers supporting NVIDIA Megatron-LM and PyTorch FSDP backends plus three weight-synchronization transports. It supports full-parameter RL, LoRA RL, on-policy distillation, supervised fine-tuning, true-on-policy rollout-training alignment, and extends to diffusion models. The end-to-end case study ran fully asynchronous agentic RL on GLM-5.2 744B-A40B for terminal-use coding tasks on 64 NVIDIA GB300 GPUs with a median step time of 263 seconds over the first 30 measured steps. The code is open-sourced on GitHub.

Hugging Face daily papersSep 7, 20:00 UTC · 9d agoAI tools & infra

Windows 11 KB5124008 Update Breaks Active Directory Domain Trust and Blocks User Logins

Microsoft's September Windows 11 cumulative update KB5124008 breaks Active Directory domain trust on domain-joined machines, blocking logins despite valid credentials.

Microsoft is investigating community reports that KB5124008, the September 8, 2026 cumulative update for Windows 11 24H2/25H2 (builds 26100.9445/26200.9445), breaks the AD secure channel, causing 'The user name or password is incorrect' errors on interactive logon. Admins reproduced the failure consistently and observed nltest error 1786 (ERROR_NO_TRUST_LSA_SECRET) plus domain controller Event 4625 with status 0xC000006D over NTLM. The problem is suspected in Machine Identity Isolation, a Credential Guard capability that moves machine-account secrets into virtualization-based security, and disabling it via registry value, Group Policy, or Intune baseline restored trust. The September 14 out-of-band update KB5129195 does not address the domain trust issue, and Microsoft's release notes do not list it as a known problem.

Cyber Security News00:29 UTC · 13h agoVulnerability 2 sources

Why Is Video Still So Expensive? A Survey of Inference-Efficiency Mechanisms in Video and Audiovisual LLMs

A survey catalogs inference-efficiency techniques for video and audiovisual LLMs, mapping bottlenecks in sampling, encoding, token reduction, and LLM decoding.

This survey covers inference-efficiency mechanisms for visual and audiovisual video LLMs, reporting reductions in parameters, FLOPs, latency, memory, and token counts. It organizes methods by pipeline stage, covering frame sampling, modality encoding, connector-level token reduction, and LLM prefilling and decoding for systems built since late 2022. The authors compile accuracy-cost comparisons under shared host models and input protocols, identify gaps in audiovisual efficiency and standardized evaluation, and maintain a public repository.

Hugging Face daily papersSep 8, 20:00 UTC · 8d agoAI research

Microsoft Releases Emergency Windows 11 Update Following Patch Tuesday Bugs

Microsoft issued emergency Windows 11 update KB5129195 to fix Patch Tuesday regressions and fully close the CVE-2026-62721 privilege escalation flaw.

Microsoft shipped out-of-band cumulative update KB5129195 for Windows 11 24H2 and 25H2 (builds 26100.9457 and 26200.9457) after the September 8 Patch Tuesday rollup, which addressed over 960 CVEs including two actively exploited flaws, broke Remote Desktop Services, Hyper-V Plan9 folder sharing, and USB audio. The emergency release also strengthens the incomplete fix for CVE-2026-62721, an elevation-of-privilege flaw in the Windows User-Mode Power Service that could let a local attacker gain SYSTEM privileges. Companion patches cover Windows 11 26H1, Windows 10, and Windows Server. Some USB Audio Class 1.0 and AMD Radeon graphics issues remain unresolved.

Cyber Security NewsSep 16, 07:45 UTC · 1d agoVulnerability in the wildCVE-2026-627211

WarmBloodAban/Minimax-h3_Singularity — new model trending #22 on Hugging Face

Community fine-tune Minimax-h3_Singularity enhances MiniMax-H3 video generation with HDR quality, distant face restoration, and improved motion, trending #22 on Hugging Face.

Minimax-h3_Singularity is a community fusion fine-tune of the MiniMax-H3 multimodal video generation model, built from multiple checkpoints and refined with pruning and weight optimization. It supports Text-to-Video, Image-to-Video, Reference-to-Video, and Video-to-Video workflows in ComfyUI, and claims improvements in HDR clarity, distant face restoration, motion fluidity, and fantasy VFX. The authors recommend pairing it with the minimax_h3_ref2v_turbo_4step_v0.1 LoRA for four-step accelerated inference, and an online demo is available via RunningHub.

Hugging Face trending modelsSep 5, 18:51 UTC · 11d agoModel release7· 1 read

SonicWall security advisory (AV26-884)

Canada's Cyber Centre issued advisory AV26-884 warning that SonicWall Network Security Manager On-Prem 4.3.0 and earlier are affected by multiple vulnerabilities.

The Canadian Centre for Cyber Security published advisory AV26-884 on September 4, 2026, flagging SonicWall Network Security Manager (NSM) On-Prem across VMware, Hyper-V, Azure, and KVM deployments, versions 4.3.0 and earlier, as affected by multiple vulnerabilities. The advisory does not list CVE identifiers, exploit details, or in-the-wild exploitation. Administrators are encouraged to review the referenced links and apply updates as they become available.

Canadian Centre for Cyber SecuritySep 8, 14:01 UTC · 8d agoAdvisory

Ambient @ EgoLongQA 2026: Distilling Long-Video perception into a Sub-2B Model

Ambient team wins EgoLongQA 2026 sub-2B division by distilling an agentic long-video perception pipeline into a 2B vision-language model.

Ambient's entry to the EgoLongQA track of the Wearable-AI Challenge at ECCV 2026 placed first in the <=2B parameter division with 0.8279 on the held-out test set. The system distills the junior perception module of a tool-using agentic pipeline into a 2B student, reaching 89% of the pipeline's accuracy with 1.1% of its parameters and lifting a 27.1% base model to 81.4%. To meet the division limit, the multilingual embedding table is pruned from 248,320 to 143,469 rows, reaching 1.9985B parameters with provably identical logits on retained rows.

Hugging Face daily papersSep 9, 20:00 UTC · 7d agoAI research

Microsoft’s September 2026 Patch Tuesday addresses 964 CVEs (CVE-2026-81963, CVE-2026-85880)

Microsoft's September 2026 Patch Tuesday fixes a record 964 CVEs, including two zero-days actively exploited in the wild.

Microsoft patched a record 964 CVEs in its September 2026 Patch Tuesday release, with 101 rated critical and 824 rated important, making it the largest Patch Tuesday to date. The release includes fixes for two zero-days that were exploited in the wild, with CVE-2026-81963 and CVE-2026-85880 highlighted in the release. Affected products span Windows core components, Office, Exchange, .NET, Visual Studio, Active Directory services (including AD CS and AD FS) and numerous Azure services. Tenable notes the release surpasses July's as the biggest ever.

Tenable BlogSep 8, 18:07 UTC · 8d agoVulnerability in the wildCVE-2026-81963 CVE-2026-858801

Repeat-After-Me: Black-Box Adaptive Visual Prompt Injection

Researchers unveil Repeat-After-Me, a black-box visual prompt injection achieving over 80% success on Qwen3.6-27B and 47% on GPT-5.5.

Researchers present Repeat-After-Me, a black-box adaptive visual prompt injection that induces frontier VLMs to reveal PII or make malicious tool calls via injected images. It exceeds 80% attack success rate on Qwen3.6-27B and 47% on GPT-5.5 even when the benign user prompt is unrelated and does not authorize the injected task. In a real-world OpenClaw Discord deployment, a minimally injected image can overwrite TOOLS.md, enabling later remote code execution and secret exfiltration.

arXiv cs.CRSep 3, 22:44 UTC · 13d agoAI safety & security

Microsoft confirms KB5002914 Excel update breaks copy and paste

Microsoft confirms KB5002914 Office security update silently breaks copy-paste, autofill, and formula dragging in Excel 2016 through 2024.

Microsoft confirmed the September 2026 KB5002914 security update breaks copy-and-paste, autofill, and formula dragging in Excel 2024, 2021, 2019, and 2016. Failures occur silently with no beep or error message, leaving the destination unmodified. Uninstalling KB5002914 via OfficeC2RClient or Oarpmany restores functionality while Microsoft investigates.

BleepingComputerupdated Sep 15, 09:25 UTC · 2d agofirst Sep 15, 08:40 UTC · 2d agoAdvisory 3 sources2

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.CLSep 4, 17:32 UTC · 12d agoAI research1

New NatJack Attacks Hijack TCP Sessions and Spoof DNS by Manipulating NAT Tables

The Hacker NewsAug 7, 10:58 UTC · Aug 7, 2026Exploit / PoC in the wildCVE-2026-56181 CVE-2026-63913

SimpleMemVLA: A Simple but Effective Native-Video Memory for Vision-Language-Action Models

SimpleMemVLA passes full timestamped video history straight to a VLA backbone, setting state of the art on four memory benchmarks.

SimpleMemVLA is a vision-language-action model for long-horizon manipulation that removes the dedicated memory module entirely. It keeps sampled history intact and feeds it to the backbone as timestamped video, with the hidden states of a generated sub-task serving as the only channel into a standard flow-matching action head. Prefilling the shared history prefix during action execution keeps latency close to a single-frame VLA. The system sets a new state of the art on four memory benchmarks and outperforms retrieval, compression and recurrent-state mechanisms, with causal interventions confirming the policy genuinely reads its history.

Hugging Face daily papersSep 1, 20:00 UTC · 15d agoAI research

Microsoft Patch Tuesday for September 2026 — Snort rules and prominent vulnerabilities

Microsoft's September 2026 Patch Tuesday fixes 973 vulnerabilities, including 113 critical, with two Windows privilege-escalation bugs (CVE-2026-81963, CVE-2026-85880) exploited in the wild.

Microsoft's September 2026 security update addresses 973 vulnerabilities across its product lineup, 113 rated critical, of which 82 are remote code execution flaws. Two vulnerabilities are confirmed exploited in the wild: CVE-2026-81963, an elevation-of-privilege flaw in the Windows Update Stack (CVSS 7.8), and CVE-2026-85880, a heap-based buffer overflow in Windows Advanced Local Procedure Call (CVSS 7.8). Microsoft flags several bugs as more likely to be exploited, including a 9.8 RCE in Windows DNS Server (CVE-2026-69730), an 8.8 RCE in Windows Kerberos (CVE-2026-69676), and a 9.0 EoP in Spring Cloud Azure (CVE-2026-69854). Cisco Talos published accompanying Snort rules to detect exploitation attempts against the prominent flaws.

Cisco TalosSep 8, 22:16 UTC · 8d agoAdvisory in the wildCVE-2026-81963 CVE-2026-85880 CVE-2026-69676+27 CVEs1

NVIDIA NVLink Fusion Expands With NVHBM Custom High-Bandwidth Memory

NVIDIA expands NVLink Fusion with NVHBM custom high-bandwidth memory for hyperscalers building trillion-parameter and agentic AI infrastructure.

NVIDIA announced that NVLink Fusion will expand to support NVHBM, a custom high-bandwidth memory option. The offering targets hyperscalers and AI innovators building next-generation systems where agentic AI and trillion-parameter workloads are mainstream. NVIDIA frames the announcement around co-designing compute, memory, storage, networking, and software as a unified system.

NVIDIA BlogAug 26, 21:05 UTC · 21d agoAI industry

Microsoft shares workaround for Windows domain login issues

Microsoft confirms September 2026 Windows updates trigger domain trust failures via Machine Identity Isolation and shares a workaround for Windows 11 enterprises.

Microsoft confirmed the September 2026 security updates (KB5124008 for Windows 11 24H2/25H2, KB5124012 for 26H1) cause Windows to honor Machine Identity Isolation enforcement settings, breaking domain trust on systems not connected to Windows Server 2025 domain controllers. Admins report valid credentials failing with domain trust and credential errors. The workaround requires disabling Machine Identity Isolation via the same management method that enabled it (Intune, group policy, or registry) and resetting the secure channel with Test-ComputerSecureChannel. Microsoft previously shipped out-of-band fixes for Remote Desktop, Hyper-V, and USB audio issues from the same updates.

BleepingComputerupdated 13:09 UTC · 38m agofirst 08:24 UTC · 5h agoAdvisory 5 sources

Fathom: Per-Query Read Depth for Sparse Decoding over Offloaded KV Cachesnew

Fathom introduces per-query bit-depth scanning of offloaded 4-bit KV caches, making long-context decoding 1.67x faster on Qwen3-8B at one million tokens.

Fathom is a key-scan method for sparse attention over KV caches resident in host memory, where each query adaptively chooses how many bits of each key channel to read using reverse water-filling over variance-weighted channel importance. The 4-bit K cache is stored channel-major as bit planes, so reading a prefix of planes is an exact t-bit quantizer. At one million tokens on Qwen3-8B, decode steps are 1.67x faster in GPU time than 136-bit scans used by Double Sparsity, Loki, and SparQ r=32, and 92-bit scans match the accuracy of 136-bit scans on real coding-agent sessions. The method requires the index to be offloaded to host memory and matches exact top-k decoding on RULER-style tasks.

Hugging Face daily papersSep 14, 20:00 UTC · 2d agoAI research

DeepSeek-v4.1 Flash: Pushing the Limits of KV Cache Compression

DeepSeek-V4.1 Flash is a 552B-parameter multimodal MoE model with 1M-token context achieving 4x KV cache compression for long-horizon agent workloads.

A detailed analysis of the DeepSeek-V4.1 Flash technical report describes a 552B-parameter multimodal mixture-of-experts model supporting contexts up to 1 million tokens. Its Causal Encoder-Decoder (CED) architecture activates 8B parameters during prefill and 16B during decode, and reportedly delivers about 420 tokens/s. Joint optimization of architecture (CSA2 cross-layer compression), FP4 KV cache precision, and deployment strategy cuts runtime KV cache to roughly 1/4 and persistent KV cache to about 1/8 of DeepSeek-V4-Flash at the same sequence length, targeting storage and bandwidth bottlenecks in long-horizon agent serving. The author notes all DeepSeek-V4 Pro models were taken offline following the release.

Hacker News · AI01:39 UTC · 12h agoModel release HN 41↑ · 3 comments

Microsoft September 2026 Patch Tuesday Fixes 973 Vulnerabilities and 2 Exploited Zero-Days

Microsoft's September 2026 Patch Tuesday fixes 973 vulnerabilities, including two zero-days already exploited in the wild.

Microsoft's September 2026 Patch Tuesday addresses 973 vulnerabilities across Windows, Office, and Azure components, including two zero-days already exploited in the wild. CVE-2026-81963, an elevation of privilege flaw in the Windows Update Stack, is flagged as an exploited zero-day. The release includes numerous remote code execution and information disclosure fixes for Microsoft Excel and Word, plus patches for the Windows kernel, ALPC, Print Spooler, ReFS, Entra ID, and Azure CLI.

GBHackersSep 9, 05:02 UTC · 8d agoAdvisory in the wildCVE-2026-85880 CVE-2026-85877 CVE-2026-85875+27 CVEs1

HyQuant: Hybrid-Precision Quantization for LLM Attention

HyQuant keeps most LLM attention states low-bit while preserving vertical-line tokens and local windows in high precision, maintaining near-lossless accuracy.

HyQuant is a hybrid-precision quantization framework for LLM attention that quantizes most attention states to low bits while keeping accuracy-critical vertical-line tokens and local-window states in full precision, selected via lightweight attention-pattern signals. In the prefill stage it uses a hybrid-precision attention operator, and in the decode stage it applies the same principle to KV-cache compression with fused dequantization and attention computation. Across diverse tasks, models, and datasets it maintains nearly lossless accuracy; code is available on GitHub.

Hugging Face daily papersAug 27, 20:00 UTC · 20d agoAI tools & infra1

RelightFormer: Feed-forward Generative Transformer for Multiview Object Relighting

RelightFormer is a feed-forward generative transformer for photorealistic single- and multi-view object relighting, trained on a 90K-object dataset.

Researchers introduce RelightFormer, a feed-forward generative transformer adapted from a video foundation model that performs direct image relighting without explicit intrinsic property estimation. The architecture injects target environment maps via a latent illumination module with cross-attention and uses permutation-invariant positional encodings for unordered multi-view inputs. Training relies on the newly constructed Laval Objaverse Dataset (LOD) with 90K objects and 39K unique illuminations, and the model shows state-of-the-art quality with strong zero-shot generalization across single-view, multi-view, and novel-view relighting.

Hugging Face daily papersSep 6, 20:00 UTC · 10d agoAI research

ShallowStream: Index Shallow then Answer Deep for Streaming Video Understanding

ShallowStream builds streaming-video retrieval indexes from shallow MLLM layers, cutting per-frame prefill latency by up to 52.1x.

ShallowStream is a framework for streaming video understanding with multimodal LLMs that uses the model's shallow layers to simultaneously encode frames and maintain an always-on lightweight retrieval index via shallow-layer KV caches, avoiding full-depth prefill for every incoming frame. At query time, shallow-layer attention scores plus a diversity-aware selection strategy retrieve relevant context frames. It reports performance on par with the strongest existing streaming methods while reducing per-frame prefill latency by up to 52.1x and 10-second end-to-end latency by up to 11.9x, with code released on GitHub.

Hugging Face daily papersSep 1, 20:00 UTC · 15d agoAI research

Domain-Specific Hallucination Detection in Large Language Models

A multi-signal pipeline detects LLM hallucinations, reaching F1 0.915 on HaluEval and cutting Qwen2.5-0.5B hallucination rates from 85.5% to 37.7% via DPO.

The paper presents a hallucination detection pipeline combining fine-tuned DeBERTa-v3 classification, Monte Carlo Dropout uncertainty, and temperature-scaled calibration. It achieves F1 0.915 and AUROC 0.977 on general-domain HaluEval tasks, with MC Dropout inference raising accuracy to 93.2%. Applying DPO to a Qwen2.5-0.5B generator reduces its hallucination rate from 85.5% to 37.7%, while cross-domain evaluation shows poor general-domain transfer to SciFact (F1 0.52) and PubMedBERT fine-tuning as the strongest adaptation (F1 0.63).

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:45 UTC · 6d agoAI research1

DataFlex-RL: An Evaluation Platform for RLVR Data Policies

DataFlex-RL benchmark of 13 RLVR data policies on Qwen2.5-7B finds none reproducibly beats uniform sampling under matched GRPO training.

DataFlex-RL is an evaluation platform comparing rollout-selection, reweighting, and mixture data policies for RLVR under a common GRPO recipe. Across 13 configurations and 12 matched seeds with Qwen2.5-7B-Base on 12 math, logic, and science benchmarks, uniform GRPO improved domain-balanced accuracy by 7.76 points, but no alternative policy achieved a statistically significant improvement. A corrected 12-seed Llama-3.1-8B-Base extension found no consistent winner, and math-heavy evaluation summaries were negatively correlated (-0.33) with domain-balanced summaries.

Hugging Face daily papersSep 4, 20:00 UTC · 12d agoAI research

RenderFormer-V2: Neural Rendering with Heterogeneous Scene Primitives

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

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

Hugging Face daily papersSep 3, 20:00 UTC · 13d agoAI research

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 papersSep 5, 20:00 UTC · 11d agoAI research

FreeFlow: A Bias-free Hierarchical Transformer for Optical Flow Estimation

FreeFlow is a bias-free hierarchical transformer achieving state-of-the-art optical flow results on Sintel, KITTI-2015, and Spring benchmarks.

FreeFlow replaces task-specific inductive biases like correlation volumes and iterative warping with a single feed-forward encoder-decoder combining window, shifted-window, and reduced-resolution global attention. It reaches 0.68/1.48 EPE on Sintel Clean/Final, 3.23 Fl-all on KITTI-2015, and 3.192 1px on Spring. The architecture scales consistently from small to large variants and remains memory efficient at 1080p inference.

Hugging Face daily papersSep 9, 20:00 UTC · 7d agoAI research

Do Input-Level Defenses Transfer to Observation-Level Attacks on VideoLLMs?

A systematic study shows input-level adversarial defenses provide inconsistent, often near-zero protection against observation-level attacks on video LLMs.

Researchers introduce DefTEval, a controlled framework testing eleven input-level defenses against five attack types across five video LLMs. Harmful-content detection rates are frequently near zero, and defenses fail even when attacks embed harmful signals in every sampled frame. Token compression discards localized safety features and modality fusion down-weights weakened visual signals, with defense outcomes dominated by model architecture rather than the defense method.

arXiv cs.CRSep 8, 06:59 UTC · 9d agoAI safety & security

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.CLSep 7, 17:47 UTC · 9d agoAI research

[AINews] Fal’s H3 Max Live breaks the infinite videogen barrier

Fal post-trained MiniMax H3 into a 'Max' variant with 35x-faster inference, enabling faster-than-realtime AI video generation and infinite streams.

Fal post-trained MiniMax's H3 model into a 'Max' variant and optimized it for its in-house inference engine, achieving roughly 35x the speed of the official endpoint. The optimization enables faster-than-realtime video generation, demonstrated by an infinite interactive AI-generated stream productized by levels.io. The roundup also notes Meta Muse Code's general availability with an SDK, open DeepSeek-V4-Flash-Vision-Exp weights, GLM-5.3-Flash's strong agentic cost/performance rankings, and Tencent's 770B-parameter Hy4 Preview MoE with 49B active parameters.

Latent SpaceSep 1, 04:36 UTC · 16d agoAI industry