Search: “crispr”

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Biology-in-the-loop: Amortized Adaptive Hit Discovery in CRISPR Screens

Researchers release AssayBench-Loop, a 1,389-screen CRISPR benchmark, and AssayLoop, a framework that learns adaptive hit discovery policies.

The paper introduces AssayBench-Loop, a large-scale benchmark of 1,389 CRISPR screens across five phenotype categories for adaptive hit discovery under budget constraints. It also introduces AssayLoop, which combines AssayFormer, a transformer-based amortized acquisition policy trained across historical screens, with LLM-derived biological priors via an adaptive handoff. On temporally held-out screens, AssayLoop achieves 5.67-fold enrichment over random selection and recovers 27.7% of hits after assaying roughly 5% of the candidate library, outperforming existing adaptive-design methods and standalone LLMs.

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

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AlphaGenome Atlas: A predictive map of every possible DNA letter change in the human genome

Google DeepMind released AlphaGenome Atlas, a free 1-petabyte platform predicting the molecular effects of all ~9 billion possible single-letter DNA variants.

Google DeepMind introduced AlphaGenome Atlas, containing precomputed predictions for the effects of roughly 9 billion single-nucleotide variants across the human genome, spanning hundreds of human and mouse cell types. The 1-petabyte dataset is more than 30 times larger than the AlphaFold Database and includes an AlphaGenome Variant Impact (AVI) score combining AlphaGenome and AlphaMissense predictions for both coding and non-coding regions. External collaborators have already used it to identify and experimentally verify variants in unsolved rare disease research. It is available via a free web portal, the AlphaGenome API, and as a skill in Google Antigravity.

Google DeepMind·Sep 8, 14:00 UTC · 8d agoAI research 2 sources

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HypoEvolve: Genetic Algorithms Enable Multi-Agent LLMs to Discover Scientific Hypotheses

HypoEvolve couples a generational genetic algorithm with specialized LLM agents to generate drug-repurposing hypotheses, beating six baselines on DepMap selectivity (0.171 vs 0.115).

HypoEvolve coordinates specialized LLM agents through a generational genetic algorithm in which scientific judgments and new proposals reshape a hypothesis population. Evaluation centers on drug repurposing, linking mechanistic explanations to target-level biological claims assessed via external measures adapted from DepMap and Open Targets. Across 34 cancer types, HypoEvolve scores highest against six baselines on both measures, with DepMap selectivity of 0.171 versus 0.115 for the strongest baseline, and gains generalize to held-out cancer types.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 17:44 UTC · 2d agoAI research1

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AI Is Learning to Write Genetic Code

AI models generated viable bacteriophage genomes, with 16 designs successfully replicating and some outperforming the original virus at attacking E. coli.

Two AI models generated complete genome designs for bacteriophages modeled on ΦX174, a virus known to infect E. coli. Researchers produced about 700,000 candidate designs, selected 285 promising ones, and synthesized DNA inserted into E. coli, yielding 16 viable viruses. Some of the newly generated viruses proved more effective at attacking E. coli than the original bacteriophage.

Schneier on Security·Aug 21, 16:52 UTC · 26d agoAI research

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Diffs vs. Whole Files: An Empirical Comparison of Iterative Edit-Based and Direct Generation for Flutter/Dart Code Models

Empirical study finds direct whole-file generation beats iterative diff-based editing for Flutter/Dart code models on about 1,790 held-out tasks.

Researchers trained Rainbow-Pony-100M from scratch and fine-tuned Qwen2.5-Coder-0.5B in both direct-generation and diff-based regimes, then evaluated four resulting models on roughly 1,790 Flutter/Dart tasks. Direct generation outperformed diff-based generation on compilation pass rate, bits-per-byte, character-level similarity, and blinded LLM-judge ratings. Diff-based editing is competitive only on short, localized edits in refactoring and error-handling tasks, a property the authors call task locality.

Hugging Face daily papers·Sep 4, 20:00 UTC · 11d agoAI research1

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Reduced-Space Multi-Fidelity Bayesian Optimization of Process Simulation Models

RS-MFBO couples global sensitivity analysis with fidelity-augmented Gaussian processes to slash costly high-fidelity simulation runs in industrial flowsheet optimization.

The paper presents RS-MFBO, a reduced-space multi-fidelity Bayesian optimization framework for high-dimensional, expensive black-box functions. It integrates Global Sensitivity Analysis for dimensionality reduction with a fidelity-augmented Gaussian process and a cost-aware acquisition strategy featuring cooldown and promotion mechanisms. Validation on a plasmid DNA bioprocess (SuperPro Designer) and a green fuel synthesis plant (Aspen HYSYS) shows substantial reductions in high-fidelity evaluations while remaining competitive with single-fidelity baselines.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 16:46 UTC · 1d agoAI research

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Google's AI genome system evaluates every possible one-base change

Google's AlphaGenome AI system predicts functional effects of non-coding DNA variants in humans and mice.

Google's AlphaGenome AI system evaluates genomic sequences to predict gene expression, transcription factor binding, chromatin accessibility, splice site usage, and related genomic features. The system is currently limited to human and mouse sequences and a limited set of well-studied cell types, but its predictions generally match or exceed specialized software tools. Researchers can use it to assess whether non-coding variants are likely significant and generate hypotheses about their function.

Ars Technica · AI·Sep 9, 16:34 UTC · 7d agoAI research

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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 · 12d agoAI research1

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NVIDIA Details BioNeMo Inference Runtime (BioIR): 2.90x Higher Boltz-2 Folding Throughput and 58.5K Residues per GPU-Hour on 8xH100

NVIDIA released BioNeMo Inference Runtime (BioIR), an open-source PyTorch-compatible library delivering 2.90x higher Boltz-2 protein-folding throughput on 8xH100 GPUs.

NVIDIA detailed BioIR, a Python library that accelerates Boltz-2, OpenFold2, and OpenFold3 structure-prediction inference on NVIDIA GPUs while preserving standard PyTorch workflows. On a matched benchmark of 1,000 human dimers on 8xH100 80GB GPUs, BioIR delivered 58.5K folded residues per GPU-hour versus 20.2K for a torch.compile baseline, a 2.90x throughput gain. BioIR already powered the AlphaFold Database expansion, generating about 31 million candidate complexes across 4,777 proteomes, with 1.81 million released as high-confidence predictions. Extrapolated to 1 million targets, estimated folding energy drops from 35 MWh to 11 MWh at 8-GPU TDP equivalents.

MarkTechPost·Sep 10, 21:57 UTC · 5d agoAI tools & infra1

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JSCeal Hides Crypto Malware in V8 Bytecode

Check Point details JSCeal, a crypto-stealing malware delivered as compiled V8 bytecode, and built a decompiler pipeline to expose its capabilities.

JSCeal, tracked by Check Point Research since early 2025, is a cryptocurrency stealer delivered as heavily obfuscated JavaScript compiled to V8 bytecode (.jsc) and run by a bundled Node.js runtime. Check Point, presenting at Black Hat USA 2026, extended the open-source View8 decompiler into a pipeline that recovered readable code from 23 samples, revealing theft of browser credentials and cookies, Telegram sessions, keystrokes, screenshots, HTTPS traffic interception with attacker-controlled certificates, and automated Google account takeover. Targeted overrides rewrite content for Binance, Bybit, and Ledger users. Later samples added AES-256-CBC encryption with externally supplied keys and expanded targeting to macOS.

Security Affairs·Sep 7, 10:19 UTC · 9d agoMalware1

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Breaking the Seal: Static Deobfuscation of JSCeal’s Compiled V8 Bytecode

Check Point's hasherezade details static deobfuscation of JSCeal, a V8-bytecode stealer targeting cryptocurrency applications since March 2024.

JSCeal is an infostealer distributed as compiled V8 bytecode (.jsc) executed by a bundled Node.js runtime, aimed at cryptocurrency applications. Other vendors track the same family under the names WEEVILPROXY or MeadowLocust. Check Point Research has tracked the campaign since early 2024, with activity dating back to March 2024. The write-up presents a static approach to unpacking the bytecode without executing it.

Check Point Research·Aug 31, 13:38 UTC · 16d agoMalware in the wild1

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Deepmind's AlphaGenome Atlas maps every possible DNA change in the human genome

DeepMind's AlphaGenome Atlas precomputes impact predictions for ~9 billion human DNA variants in a 1-petabyte dataset; its AVI score beats CADD in benchmarks

Google DeepMind released the AlphaGenome Atlas, precomputing functional-effect predictions for roughly 9 billion human genome variants (about 27,000 prediction values per variant) in a one-petabyte dataset more than 30 times the size of the AlphaFold database. The accompanying AlphaGenome Variant Impact Score (AVI), a small neural network combining AlphaGenome, AlphaMissense and evolutionary conservation features (18 inputs versus CADD's 150+), outperformed existing tools on clinically classified variants, ranking causal variants in the top 50 candidates for 29.5% of solved GREGoR cases versus 12.5% for CADD. A GREGoR epilepsy case illustrates the impact: AVI elevated a previously unclear DNM1 splice variant that lab experiments confirmed as likely disease-causing. The atlas is available for noncommercial use via web portal, API and a Google Antigravity skill, with a commercial version planned through Google Cloud.

The Decoder·Sep 9, 13:40 UTC · 7d agoAI research

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Google DeepMind Releases AlphaGenome Atlas With Precomputed Molecular Effect Predictions and AVI Scores for 9 Billion Human DNA Variants

Google DeepMind launched AlphaGenome Atlas, precomputing molecular effect predictions and AVI impact scores for ~9 billion human single-nucleotide variants in a 1-petabyte catalogue.

Google DeepMind released AlphaGenome Atlas, a 1-petabyte catalogue of precomputed molecular effect predictions for roughly 9 billion possible single-nucleotide variants in the human genome. It introduces the AlphaGenome Variant Impact (AVI) score, combining AlphaGenome regulatory predictions with AlphaMissense, plus per-variant feature attributions and over 2,500 recurrent DNA sequence motifs. DeepMind reports best-in-class AVI performance on variant pathogenicity and rare disease benchmarks. Early users at the Broad Institute, University of Exeter, and Stowers Institute demonstrated rare-disease variant reprioritization and 22% more non-coding associations across 54,000+ UK Biobank genomes.

MarkTechPost·Sep 8, 19:00 UTC · 7d agoAI research2

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DianShi-RxnDB: A Large-Scale, Fine-Grained Organic Reaction Data Platform Built via a Fully Automated Pipeline for Researchers and AI Agents

Researchers release DianShi-RxnDB, a database of roughly 24 million organic reaction instances extracted automatically from USPTO and EPO patents since 1976.

DianShi-RxnDB is built by a fully automated pipeline integrating patent text, images, and reaction schemes, yielding about 24 million reaction instances, of which 14.8 million (61.7%) pass automated qualification checks. Manual evaluation of 1,300 sampled instances showed 92.95% field-level accuracy, and comparisons with Pistachio found advantages in deduplicated record counts and granularity. The platform offers a web research workbench and a Model Context Protocol (MCP) service enabling AI agents to perform composable structured retrieval.

Hugging Face daily papers·Sep 5, 20:00 UTC · 10d agoAI research

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A Princeton Researcher Proposes Recurrent Looped Transformer (RLT) that Carries Decoder State across Every Token, Fixing 96 Blocks per Token with Unbounded Temporal Depth

Princeton researcher Yifan Zhang proposes Recurrent Looped Transformer, carrying full decoder state across every token for unbounded temporal depth.

Yifan Zhang's technical report defines the Recurrent Looped Transformer (RLT), pairing a causal encoder with a recurrent decoder whose final output and layerwise sliding-window attention cache carry into every subsequent token with no prompt-response boundary reset. The reference configuration ties 48 encoder and 48 decoder layers, executing 96 logical blocks per token while the state path grows to 48t blocks after t tokens at fixed per-token compute. The report details RL replay contracts that rebuild all states under current parameters and exact prefix snapshots for multi-turn serving, but explicitly reports no measured efficiency, reasoning quality, or scaling results.

MarkTechPost·Sep 13, 17:02 UTC · 3d agoAI research1

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

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

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

Hugging Face daily papers·Sep 9, 20:00 UTC · 6d agoAI research

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Linux kernel LPEs: ZcopyReaper (CVE-2026-43502) and 20 more

Researchers disclosed CVE-2026-43502 (ZcopyReaper), a Linux kernel local privilege escalation in the RDS zerocopy send path, fixed in v7.1-rc3.

Yuan Tan reported a Linux kernel local privilege escalation in the RDS zerocopy send path, tracked as CVE-2026-43502 and dubbed ZcopyReaper, posted to oss-security. The flaw was introduced in Linux v4.17 and fixed by commit 44b550d88b26, first appearing in mainline v7.1-rc3. The researchers demonstrated local privilege escalation on an openSUSE system running kernel 6.4.0-150600.23.100. The post also references 20 additional Linux kernel LPEs, though CVE ids were not provided in the excerpt.

oss-security·Sep 8, 03:53 UTC · 8d agoVulnerabilityCVE-2026-43502

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Linux Kernel ZcopyReaper Vulnerability Lets Local Attackers Gain Root Privileges

Linux kernel RDS zero-copy flaw CVE-2026-43502 (ZcopyReaper) lets unprivileged local users gain root; fix in 7.1-rc3, public PoC published.

CVE-2026-43502, dubbed ZcopyReaper, is a Linux kernel local privilege escalation flaw in the RDS zerocopy send path, present since kernel 4.17, allowing unprivileged local attackers to gain root. NebuSec researcher Yuan Tan demonstrated root escalation on openSUSE kernel 6.4.0-150600.23.100; the fix landed in commit 44b550d88b26 with Linux 7.1-rc3 the first patched mainline release. Exploitation requires CONFIG_RDS and CONFIG_RDS_TCP but not unprivileged user namespaces, and PoC exploit material is publicly released alongside more than 20 other exploitable 2026 kernel CVEs.

GBHackers·Sep 15, 08:18 UTC · 1d agoExploit / PoCCVE-2026-43502CVE-2026-43501CVE-2026-43074+4 CVEs1

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When Models Edit Too Much: On the Fidelity of Minimal Code Edits

A 400-task BigCodeBench evaluation shows frontier LLMs widely over-edit code; a preservation instruction cuts excess edits and raises Pass@1 by 2.3 points.

Researchers built an evaluation framework from 400 BigCodeBench problems with injected AST-level corruptions, each with a known minimal patch, to measure over-editing in LLM code repair. Even strong models like GPT-5.5 produce unnecessarily large edits despite high Pass@1. Adding a preservation instruction reduced average excess Levenshtein distance from 0.195 to 0.131, cut added cognitive complexity by 26.6%, and raised Pass@1 by 2.3 points. Reinforcement learning post-training gave the best out-of-domain edit-fidelity trade-off, while supervised fine-tuning overfit to seen corruption patterns.

Hugging Face daily papers·Sep 2, 20:00 UTC · 13d agoAI research1

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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·Sep 10, 17:43 UTC · 6d agoAI research

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Top 10 Best Ransomware Protection Solutions in 2026

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

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

Cyber Security News·Sep 10, 08:18 UTC · 6d agoIndustry1

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Mi-Ripple: Restoring Images Degraded by Iterative AI Editing

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

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

Hugging Face daily papers·Sep 9, 20:00 UTC · 6d 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 · 12d agoAI research

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Fly Language Model (FLM) Wires the Full Fruit Fly Connectome Into a Frozen 1.2B LLM, and Its Own Controls Show the Wiring Does Not Help

Researchers wire the full fruit fly connectome (166,700 nodes) into a frozen LiquidAI LFM2.5-1.2B LLM, but controls show no fly-specific benefit.

The Fly Language Model (FLM) couples the complete MaleCNS v1.0 fruit fly connectome (166,700 nodes, 25,582,938 edges) to a frozen LiquidAI LFM2.5-1.2B-Instruct backbone, training only a 278,528-parameter readout (~0.0238% of backbone parameters). The fly readout improved NLL by 0.0222 nats/token (perplexity 3.98 to 3.90) on 32 SmolTalk dialogues, but a direct-input control without the graph beat it in all three seeds. Relabeling node identities removes the gain and the recurrence contracts state differences by 0.6 per token, so the connectome adds no long-range memory. The MIT-licensed code runs locally on Python 3.12, but study artifacts remain private, limiting independent reproducibility.

MarkTechPost·Sep 12, 18:51 UTC · 3d agoAI research1

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"They don't care about this": A Systematic Study of TEE Build Reproducibility in the Wild

91% of 115 surveyed TEE deployments across Intel SGX, TDX, and AMD SEV fail to provide reproducible builds needed for verifiable remote attestation.

A systematic study of 115 TEE deployments found 91% were not reproducible and 80% lacked both source code and a reference build, undermining remote attestation guarantees. Interviews with 12 developers of 50 Intel SGX projects confirmed that only one participant treats reproducibility as a development priority. The authors identify technical barriers such as embedded timestamps plus ecosystem-level issues like lack of build-environment control in multi-stakeholder projects, and call for holistic, committed reproducibility practices.

arXiv cs.CR·Sep 10, 11:43 UTC · 6d agoResearch

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Thousands of Hacked WordPress Sites, One Operation: Unmasking StopAndProtect

Check Point uncovers the StopAndProtect ransomware operation infecting thousands of WordPress sites via ClickFix social engineering and PowerShell downloaders.

Check Point Research first observed the StopAndProtect ransomware family in mid-May 2026 and linked its infrastructure to thousands of hacked WordPress sites. The infection chain begins with ClickFix social engineering that prompts victims to run a PowerShell command, followed by two stages of additional downloaders. The research maps the shared infrastructure unifying the operation.

Check Point Research·Aug 18, 13:05 UTC · 29d agoRansomware in the wild

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ActionSplice: In-Flight Action Editing for Interactive World Models

ActionSplice enables in-flight action editing in chunk-autoregressive video world models via a lightweight corrector, avoiding rollback or waiting for the next chunk.

ActionSplice is an inference framework that formulates in-flight action editing for chunk-autoregressive video world models as Counterfactual State Transport (CST), where a lightweight corrector transports the interrupted backbone-native representation toward the matched state induced by the revised action. The world model and sampler remain frozen, and sampling resumes without replaying completed evaluations. Across minWM-Wan Action2V and HY-WM1.5, the retargeting variant CST-R reduces rollback-relative LPIPS by 61.5% and 75.9% versus direct condition swapping, while the temporal-splicing variant CST-T reduces suffix LPIPS by 56.1% and 77.5% with 2.73x and 1.69x pixel-ready speedups over waiting.

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

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Tricky 'SynkLoader' Multitool May Herald Ransomware

Researchers detail SynkLoader, an advanced multilingual multitool that hijacks screens to steal passwords and may precede ransomware attacks.

Dark Reading reports analysis of SynkLoader, an advanced, multilingual malware family functioning as a multitool loader. The family revives an older technique — screen hijacking — to enable effective password theft, alongside several novel features. Analysts assess its activity may be a precursor to ransomware deployments, making early detection valuable for defenders.

Dark Reading·Aug 24, 15:02 UTC · 23d agoMalware

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GentleKiller targets more than 400 security processes across 48 products

ESET details the Gentlemen ransomware gang's in-house GentleKiller EDR-killer framework targeting over 400 security processes across 48 products, supplied to affiliates.

ESET analyzed the Gentlemen ransomware gang's in-house GentleKiller EDR-killer framework, confirmed through an internal data leak from May 2026. The framework has at least eight variants impersonating legitimate security products and abusing vulnerable or malicious kernel drivers, targeting more than 400 process names across 48 security products. Gentlemen emerged in late 2025, became one of the five most active ransomware gangs in Q1 2026, offers affiliates a 90% ransom share, and practices double extortion using Go-based and C-based ESXi encryptors. The suite also reuses outside tools including HexKiller, ThrottleBlood, and HavocKiller, unified by a shared evasion layer that mimics well-known security vendors.

Help Net Security·Aug 24, 04:22 UTC · 23d agoRansomware in the wild

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