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CategoryAll Vulnerability 6 Industry 4 Ransomware 3 Malware 3 Threat actor 2 Phishing & fraud 1 Policy & legal 1 Research 1

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Efficient Branch-and-Bound Testing and Verification of zkVMs

ZEBRA verifies zkVM constraint systems via branch-and-bound cardinality counting, finding 11 zero-day bugs across five real-world zkVMs and running 51.5x faster than SMT verification.

ZEBRA reduces zkVM correctness to a solution-set cardinality problem requiring that each constraint system admit exactly one valid execution trace, eliminating redundancies like null-row padding and non-deterministic permutations before counting. It lifts analysis from finite-field witnesses to an integer interval lattice, exploiting that constraints across 5 real-world zkVMs use only 14.0% of theoretical connectivity capacity on average, enabling tight interval propagation. A parallel branch-and-bound search produces concrete counterexamples or certifies absence of violations within a bounded region. ZEBRA discovers 11 zero-day bugs (6 independently confirmed, 3 fixed), is 51.5x faster than SMT-based verification, and verifies 16.5 percentage points more instances.

arXiv cs.CRSep 14, 04:35 UTC · 3d agoResearch

ZDI-26-630: NI LabVIEW VI File Parsing Integer Overflow Information Disclosure Vulnerability

ZDI disclosed CVE-2026-18445, an integer overflow in NI LabVIEW VI file parsing that can disclose sensitive information, rated CVSS 3.3.

The Zero Day Initiative published advisory ZDI-26-630 describing an integer overflow vulnerability in NI LabVIEW's parsing of VI files. Exploitation can disclose sensitive information and requires user interaction, such as visiting a malicious page or opening a malicious file. ZDI assigned the flaw a CVSS rating of 3.3.

ZDI Published AdvisoriesSep 9, 05:00 UTC · 8d agoAdvisory 2 sources CVE-2026-184451

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face BlogAug 18, 00:00 UTC · Aug 18, 2026AI tools & infra1

Cl0p Targets 40+ Organizations Through PTC Windchill Flaw

Cl0p claims over 40 organizations including Shell and Philips were breached by exploiting critical RCE CVE-2026-12569 in PTC Windchill and FlexPLM.

Cl0p claims more than 40 organizations were victimized via CVE-2026-12569 (CVSS 9.3), a critical deserialization-based remote code execution flaw in PTC Windchill PDMlink and FlexPLM, affecting releases prior to 11.0 M030; CISA added the flaw to its KEV catalog in June. ReliaQuest found the group deployed a custom web shell that maps vault data, decrypts all credentials in the Windchill keystore, and includes a Java class loader enabling arbitrary code execution, lateral movement, persistence, and large-scale data exfiltration without extra tooling. Named victims include Shell, Philips, Fiserv, Zebra Technologies, Ingersoll Rand, Toast, Mindray, and Apple lens supplier Largan Precision, with stolen data ranging from one gigabyte to multiple terabytes per target. The campaign mirrors Cl0p's earlier mass-exploitation extortion operations against MOVEit, Cleo, GoAnywhere, and Oracle E-Business Suite.

Security AffairsAug 21, 07:15 UTC · 27d agoRansomware in the wildCVE-2026-12569

The long tail of Clop’s PTC hack is just beginning to emerge

Clop mass-exploited CVE-2026-12569 in PTC Windchill and FlexPLM in early June, claiming data theft from dozens of large organizations.

Clop began sending extortion emails in mid-July after exploiting CVE-2026-12569 in PTC Windchill and FlexPLM, likely as a zero-day in early June before PTC's June 17 disclosure and patch. Confirmed victims include Toast and Zebra, while GE, Philips and Shell are among claimed victims. CISA added the flaw, which allows unauthenticated remote code execution, to its KEV catalog on June 25. ReliaQuest said the group used a custom Windchill-specific web shell for credential theft and large-scale exfiltration, echoing its past MOVEit and Oracle E-Business Suite mass-exploitation campaigns.

CyberScoopAug 19, 14:30 UTC · 28d agoThreat actor in the wildCVE-2026-125691

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.CLSep 8, 17:56 UTC · 8d agoAI research2

Pegasus Zero-Click Exploit Infects Serbian Student Activist's iPhone

Citizen Lab and SHARE Foundation confirm a Serbian student activist's iPhone was infected with NSO Group Pegasus via a zero-click iMessage exploit.

Forensic analysis found high-confidence infection indicators on the activist's iPhone during December 2025 and January 2026, using an iMessage zero-click exploit the Citizen Lab believes was patched as of iOS 18.4.1, released April 2025. The target was among at least 14 Apple Threat Notification recipients in Serbia's student movement, civil society, and opposition politics documented by the SHARE Foundation. Targeting occurred ahead of key 2026 election cycles; Amnesty Tech also confirmed a new NoviSpy version on another student movement member's device.

Infosecurity MagazineSep 3, 15:25 UTC · 13d agoThreat actor in the wild

Right Tool, Right Job: Native-Language Evaluation, Tokenizer Sensitivity, and Methodological Findings from a French-Only BabyLM

French BabyLM entry METRON-FR (125M GPT-2, 92.47M words) shows tokenizer artifacts dominate child-scale zero-shot evaluation; proposes standard diagnostics.

METRON-FR is a 125M-parameter GPT-2 pretrained on 92.47M French words, submitted to the BabyLM 2026 Strict track, scoring 85.97% on the native Quebec-French QFrBLiMP benchmark and 62.80% on the BabyLM-weighted leaderboard. A cross-lingual GLUE protocol combining French task-data translation with rank-16 LoRA shows relational tasks gain while world-knowledge tasks regress. Bilingual Lexicon Induction reaches p@1 of 68.84%, 18x above chance, and ablations show single-token zero-shot scoring is dominated by tokenizer and template artifacts at child scale.

arXiv cs.AI / cs.LG / cs.CLSep 15, 16:43 UTC · 1d agoAI research

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 papersSep 7, 20:00 UTC · 9d agoAI research1

Pegasus and NoviSpy Used Against Serbian Protesters

Citizen Lab confirmed zero-click Pegasus infected a Serbian student activist's iPhone, part of the largest documented Serbian spyware wave targeting at least 14 people.

The Citizen Lab, with the SHARE Foundation, confirmed a Serbian student protest movement member's iPhone was infected with NSO Group's Pegasus via an iMessage zero-click exploit between December 2025 and January 2026; Apple patched the exploit in iOS 18.4.1. SHARE Foundation has documented at least 14 targeted individuals since early 2026, including student activists, civil society figures, an opposition MP and a local councilor, coinciding with the March 2026 local elections. SHARE and Amnesty Tech also found a new NoviSpy variant on a student activist's Android phone after Serbian authorities seized it during police questioning.

Security AffairsSep 3, 20:17 UTC · 13d agoThreat actor in the wild

Pegasus Zero-Click Spyware Exploit Infects Serbian Student Movement Member's iPhone

Citizen Lab confirms Pegasus zero-click iMessage spyware infected a Serbian student activist's iPhone amid at least 14 spyware targets in Serbia during 2026.

The Citizen Lab, with the SHARE Foundation, confirmed an iMessage zero-click exploit infected a Serbian student protest movement member's iPhone with NSO Group's Pegasus spyware, with high-confidence indicators from December 2025 to January 2026. The exploit was addressed by Apple in iOS 18.4.1, released April 2025. At least 14 people in Serbia, including students, activists, an MP, and a councilor, were targeted with advanced spyware since the start of 2026, coinciding with March 29, 2026 local elections; a new Android spyware similar to NoviSpy was also found on a confiscated device.

The Hacker NewsSep 3, 08:43 UTC · 14d agoThreat actor in the wild

Chinese Routers Sold Worldwide Contain Backdoors

Manufacturer-built backdoor implants were found in ZBT white-label routers sold worldwide, exposing affected devices to potential unauthorized access.

An untold number of ZBT routers distributed globally as white-label products contain multiple backdoor implants built into the devices by the manufacturer. The implants are pre-installed through the hardware and firmware supply chain rather than injected by attackers after deployment. The scale of affected deployments and whether the implants have been actively abused have not been disclosed.

Dark ReadingAug 27, 19:31 UTC · 20d agoVulnerability

Zing-0.5: Toward Playable Worlds with Real-Time Joint Action and Text Control

Zing-0.5 is a released 5B autoregressive world model enabling real-time keyboard and text control at 24 FPS for roughly $0.009 per stream-minute.

Zing-0.5 is a 5B autoregressive world model designed for playability, combining magnitude-aware keyboard inputs with temporally aligned text instructions in jointly annotated videos. It uses event-scale supervision via distribution-matching distillation from a segment-level teacher and four-step generation with context-preserving streaming for real-time 832x480 inference at 24 FPS. The model scores 81.0 overall and 88.5 consistency across 158 WBench Navigation cases, and the weights, inference code, and Zing-SGLang serving implementation are publicly released.

Hugging Face daily papersSep 14, 20:00 UTC · 2d agoModel release

27.5KB language-agnostic WebGPU syntax highlighter

A developer released gpu-lexer, a 27.5KB language-agnostic syntax highlighter that uses a tiny WebGPU model to label code tokens in the browser.

gpu-lexer splits source into words, whitespace, and symbols, then a small WebGPU model uses local and whole-file context to assign nine token classes, working on languages never seen in training. On held-out files, 12.57% of token labels differ from Shiki, though this measures agreement with Shiki rather than objective correctness. In benchmarks against Shiki 4.4.3, Prism.js, Highlight.js, Sugar High, and Starry Night, it highlighted 10 concatenated copies of three.min.js (5.56M characters) about 10x faster on an Apple M4 Pro in Chrome 152. The author frames it as an experiment, not a grammar-equivalent highlighter.

Hacker News · securitySep 9, 01:14 UTC · 8d agoAI tools & infra HN 21↑ · 5 comments1

Can Edge-Deployable Vision-Language Models Identify Species?

Evaluation of 2-8B VLMs (Qwen3-VL, Gemma3) against BioCLIP on camera-trap species ID shows all models degrade sharply on field imagery.

The study tests whether edge-deployable 2-8B vision-language models carry genuine taxonomic knowledge, comparing Qwen3-VL 2B/4B/8B and Gemma3 4B against the 300M specialist BioCLIP on a 96-species task across clean iNaturalist photos and six LILA.science camera-trap collections. All models degrade 9.6-26.6 percentage points on field imagery, and BioCLIP outperforms every VLM by 33.2-59.2 points on an expanded 200-image sample, suggesting specialized data rather than scale drives the gap. Under open-set prompting, 5.9-9.6% of responses are syntactically valid but taxonomically nonexistent species names, with fabrication rankings replicating across evaluation sets.

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:57 UTC · 6d agoAI research1

Quoting Calif Research

Calif Research demos WeWorm, an AI-built zero-click worm that spreads via WeChat calls on iOS and Android without user interaction.

Calif Research released a demo of WeWorm, described as the first zero-click worm to spread through WeChat calls across iOS and Android; victims need not answer the call and hear nothing even if they do. The team used AI to find the underlying bug and write a remote code execution exploit in about two days, then spent one more week building the worm. The researchers argue AI can now do most of the exploit-development work, with humans supplying judgment on targeting and safe testing.

Simon WillisonSep 10, 00:56 UTC · 7d agoAI safety & security

WeWorm – First 0-Click Worm Spreading Through WeChat Calls Across iOS and Android

Researchers demonstrated WeWorm, a zero-click worm exploiting a memory-corruption flaw in WeChat's VoIP stack to spread via calls across iOS and Android.

Security firm Calif published WeWorm, a proof-of-concept zero-click worm exploiting a memory-corruption bug in WeChat's VoIP stack to spread through voice calls on iOS and Android without the victim answering. The demo chained a Pixel 10a, an iPhone 17e, and a second Pixel 10a, compromising each device while the call was still ringing and giving full control of the WeChat account. The attacker must already be on the victim's friend list, but compromised contacts become the propagation layer across a platform with over 1.4 billion monthly users. Calif reported the bug to Tencent in July 2026, and Tencent has since mitigated it; full technical details are withheld for a later conference presentation.

Cyber Security NewsSep 8, 12:09 UTC · 8d agoExploit / PoC

Testing race conditions with memory access tracing and stack-based delay injection

Google Project Zero released MAccConc, Linux kernel tooling that traces memory accesses to explore and test race condition interleavings.

A Google Project Zero researcher published MAccConc (Memory Access Concurrency), tooling for exploring possible interleavings of multithreaded test cases in the Linux kernel, available on GitHub. The tools use KCOV with ASAN outline-mode instrumentation to record per-access memory traces, enabling automatic testing of all A-B-A interleavings plus terminal and GUI explorers for manual analysis. The work targets confirming race condition candidates, building reliable regression tests, and enabling concurrency fuzzing, drawing on ideas from SKI and Ned Williamson's sockfuzzer.

Google Project ZeroSep 8, 07:00 UTC · 9d agoResearch2

ZDI-26-588: Fabric.js loadFromJSON Server-Side Request Forgery Vulnerability

ZDI disclosed a server-side request forgery in Fabric.js loadFromJSON (CVE-2026-19504) that can leak sensitive information from affected implementations.

Zero Day Initiative advisory ZDI-26-588 describes a server-side request forgery vulnerability in the Fabric.js canvas library's loadFromJSON function. Exploitation requires interaction with the library and attack vectors vary by implementation, potentially exposing sensitive information. The issue is rated 4.0 on the CVSS scale and tracked as CVE-2026-19504. The advisory does not report exploitation in the wild.

ZDI Published AdvisoriesAug 24, 05:00 UTC · 24d agoVulnerability CVE-2026-19504

Objective vs. Search: Decomposing What Makes a Good Tokeniser

New tokeniser study shows search procedure, not optimisation objective, drives bits-per-byte performance across model sizes, vocabulary sizes, and multilingual settings.

The paper disentangles BPE and UnigramLM along two axes: optimisation objective (compression vs log-likelihood) and search procedure (bottom-up merging vs top-down pruning). Two new algorithms, BottomUpLL and TopDownComp, complete the 2x2 design space, and trained language models are evaluated on bits-per-byte and BLiMP across model sizes, vocabulary sizes, and English-only vs multilingual domains. Bottom-up tokenisers consistently achieve lower bits-per-byte in most settings, while BLiMP shows no consistent relationship with design choice.

arXiv cs.AI / cs.LG / cs.CLSep 16, 17:59 UTC · 14h agoAI research

Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

Hugging Face published a tutorial on training and finetuning multi-vector embedding models using the Sentence Transformers library.

Hugging Face's blog walks through training and finetuning multi-vector embedding models with Sentence Transformers. Multi-vector approaches store multiple vectors per document to support late-interaction retrieval. The post is a practical guide for developers building retrieval pipelines with the library.

Hugging Face BlogAug 26, 00:00 UTC · 22d agoAI tools & infra1

ZDI-26-610: Apple Safari JavaScriptCore B3 ReduceStrength Phase Use-After-Free Remote Code Execution Vulnerability

ZDI details a use-after-free in Apple Safari's JavaScriptCore (CVE-2026-64715) that allows remote code execution after a user visits a malicious page.

The Zero Day Initiative published advisory ZDI-26-610 for a use-after-free in the B3 ReduceStrength phase of Apple Safari's JavaScriptCore. Successful exploitation allows remote attackers to execute arbitrary code, but user interaction is required, such as visiting a malicious page or opening a malicious file. ZDI rates the vulnerability 8.8 on CVSS and assigned CVE-2026-64715. The advisory does not report exploitation in the wild.

ZDI Published AdvisoriesAug 24, 05:00 UTC · 24d agoVulnerability CVE-2026-64715

ZDI-26-706: (0Day) CrewAI crewAI Framework Agent Loading Unsafe Reflection Remote Code Execution Vulnerability

ZDI discloses unpatched unsafe reflection RCE vulnerability CVE-2026-92206 (CVSS 8.8) in the CrewAI agent framework.

Zero Day Initiative published ZDI-26-706, an unsafe reflection remote code execution vulnerability in the CrewAI framework, tracked as CVE-2026-92206 with a CVSS score of 8.8. Exploitation requires user interaction: the target must load a malicious agent configuration from the repository. As a 0day advisory, no patch is indicated at publication.

ZDI Published AdvisoriesSep 16, 05:00 UTC · 1d agoVulnerability 11 sources CVE-2026-922062

Updated ToxicPanda Variant Targets 140+ Banking and Crypto Apps

Zimperium reports ToxicPanda 2.0, an updated Android banking trojan now targeting more than 140 banking and cryptocurrency apps.

Zimperium has published analysis of ToxicPanda 2.0, an updated Android banking trojan variant. The new variant expands its target list to over 140 banking and cryptocurrency applications. The report lifts the lid on the updated capabilities of the mobile malware family.

Infosecurity MagazineAug 20, 10:00 UTC · 27d agoMalware

Researchers Build WeChat Zero-Click Worm Hijacking Phones via Calls

Calif researchers built WeWorm, a zero-click worm exploiting a WeChat VoIP memory-corruption RCE that Tencent has now patched.

Calif researchers found a memory corruption flaw in WeChat's VoIP stack in July using LLM-assisted analysis and built working exploits within two days, then integrated them into WeWorm, which they call the first zero-click worm spreading through WeChat calls on iOS and Android. A crafted incoming call yields remote code execution with no user interaction, giving full control of the victim's WeChat account; the attacker only needs to be on the victim's friend list, easily achieved by compromising a contact first. Tencent confirmed the bug and shipped patches in WeChat Android 8.0.77 and iOS 8.0.76, and chaining with other OS bugs could yield full device control.

Infosecurity MagazineSep 9, 15:00 UTC · 7d agoExploit / PoC

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.

The Rosetta system for the AlexandriaX-2026 shared task fine-tunes a LoRA adapter on NileChat-3B for context-aware English-to-dialectal Arabic dialogue translation. The adapter was additionally pretrained on MADAR and PADIC dialect corpora for the unconstrained track. It achieved spBLEU 26.10 (4th, constrained) and 25.09 (5th, unconstrained). External dialect pretraining improved only two of thirteen dialects while slightly degrading overall performance, indicating negative transfer.

arXiv cs.AI / cs.LG / cs.CLSep 9, 16:15 UTC · 7d agoAI research1

BengalSEO Poisons Bing Search Results to Deliver MayaBot and Tech Support Scams

DFIR Report exposes BengalSEO, an India-based SEO-poisoning operation running since 2015, delivering MayaBot malware and tech support scams via Bing results.

The DFIR Report details BengalSEO, a financially motivated cluster operating from Rajasthan, India, since at least 2015, run through two IT service providers: WeConnect Solutions LLC and Garage2Global. The group uses black-hat SEO techniques—backlinks, DOM injection, DOM shuffling, keyword stuffing—to push lure pages to the top of Microsoft Bing results, routing victims through a traffic distribution system to either the custom MayaBot malware (which delivers an XMRig cryptominer and enables C2) or tech support scam call centers. A Vizio decoy page had 2,000 backlinks from 167 unique external domains, and Matomo analytics is used for victim fingerprinting, with the tracking domain appearing in 1,112 urlscan.io results.

The Hacker NewsSep 8, 08:43 UTC · 9d agoThreat actor in the wild1

TaichuAI/ZDTaichu5.0-9B — new model trending #30 on Hugging Face

TaichuAI released ZDTaichu5.0-9B, an open multimodal VLM built on Qwen3.5-9B targeting spatial reasoning, embodied AI, and agentic tool use.

TaichuAI released ZDTaichu5.0-9B, a multimodal vision-language model pairing a Qwen3.5-9B language decoder with a C-RADIOv4-H vision encoder, supporting text, single/multiple images, and video with any-resolution input and a 128K-token context. It introduces Entropy-Gated Adaptive Recurrent Reasoning, which allocates extra latent refinement steps to harder tokens. Reported benchmarks include 87.7 on TAU2-Bench, 71.4 on Claw-Eval, 93.7 on IFEval, 48 on ERQA, and 56 on RoboSpatial, leading compared 10B-scale open VLMs on agent and spatial tasks. The weights are available on Hugging Face, GitHub, and ModelScope, where it is trending at #30.

Hugging Face trending modelsSep 4, 02:55 UTC · 13d agoModel release1

Structural Jailbreaks Generalize but Do Not Compound: A cross-provider and multilingual study of Involuntary In-Context Learning

Researchers show IICL structural jailbreaks generalize to Google Gemini, lifting attack success to 80-100% on harm and financial benchmarks; non-English prompts attenuate it.

The study red-teams two Google Gemini models with Involuntary In-Context Learning (IICL), a structural jailbreak reframing harmful requests as the final cell of a data-labeling task. IICL lifts attack success from at most 6.7% to 80-90% on HarmBench and 97-100% on financial abuse (FinProof), an order of magnitude above prior results on OpenAI's GPT-5.4. Against a compounding hypothesis, forcing IICL output into Spanish, Hindi, or Arabic attenuates the attack in 11 of 12 conditions, attributed to a 'relevance curse' producing lower-quality harmful content in lower-resource languages. Findings replicate under an independent non-Google judge (Cohen's kappa 0.86 over 377 paired verdicts).

arXiv cs.CRSep 8, 07:38 UTC · 9d agoAI safety & security

GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation

GE-Act 2.0 is a from-scratch pretrained world-action model for robotic manipulation, with success rising from 17.1% to 44.1% as co-training data scales to 30,000 hours.

Genie Envisioner Act 2.0 (GE-Act 2.0) is a world-action model whose generative and action components are all initialized from scratch on manipulation data, combining a control-oriented autoencoder (CoAE), single-step visual planner (SVP), and inverse dynamics model (IDM) trained jointly via knowledge-aligned selective optimization (KASO). Scaling co-training data from 300 to 30,000 hours raises zero-shot success from 17.1% to 44.1% on G1-OP and 13.4% to 31.1% on G2-90D, despite the latter comprising under 2% of data, suggesting cross-embodiment transfer. Gains span 19/20 and 18/20 skill groups, and skill-specific coverage correlates with zero-shot OOD success (Pearson r=0.80).

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

LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence

LimiX-2, a tabular foundation model built on Contextual Mechanism Networks, outperforms existing tabular models on TabArena, TALENT, and BCCO.

Researchers introduced LimiX-2, a new model in the LimiX family that adopts the Contextual Mechanism Networks (CMNs) paradigm and is pretrained with Context-Conditional Masked Modeling (CCMM) on synthetic datasets generated by structural causal models. Unlike tabular PFNs centered on p(y | x, D_context), CMNs learn mechanism-oriented joint modeling of p(x, y | D_context). Evaluations on TabArena, TALENT, and BCCO show LimiX-2 outperforms current dataset-specific models and tabular foundation models. Its feature attention also encodes direct causal relationships, enabling accurate causal skeleton recovery.

Hugging Face daily papersupdated Sep 15, 17:30 UTC · 1d agofirst Sep 14, 20:00 UTC · 2d agoAI research 2 sources