πŸš€ WELCOME TO METAMESH.BIZ +++ OpenAI's GPT-5.6 can diagnose every security flaw but can't actually hack anything (the cybersecurity equivalent of a food critic who can't cook) +++ Chinese GLM-5.2 matching US models at bug-hunting while export controls continue their theatrical performance +++ THE ARMS RACE IS NOW ABOUT WHO CAN FIND BUGS THEY CAN'T EXPLOIT +++ β€’
πŸš€ WELCOME TO METAMESH.BIZ +++ OpenAI's GPT-5.6 can diagnose every security flaw but can't actually hack anything (the cybersecurity equivalent of a food critic who can't cook) +++ Chinese GLM-5.2 matching US models at bug-hunting while export controls continue their theatrical performance +++ THE ARMS RACE IS NOW ABOUT WHO CAN FIND BUGS THEY CAN'T EXPLOIT +++ β€’
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πŸ“° NEWS

OpenAI says GPT-5.6 Sol and Terra were capable of identifying vulnerabilities but were unable to execute autonomous, end-to-end attacks against hardened targets

πŸ”¬ RESEARCH

When Does Combining Language Models Help? A Co-Failure Ceiling on Routing, Voting, and Mixture-of-Agents Across 67 Frontier Models

"Multi-model LLM systems such as routing, voting, cascades, fusion, and mixture-of-agents are used to beat single-model accuracy. We show that their gain is capped by a quantity the field rarely reports. For any policy whose output is one member model answer, accuracy cannot exceed one minus beta, wh..."
πŸ“° NEWS

Clean GitHub repo tricks AI coding agents into running malware

πŸ“° NEWS

Researchers say Z.ai's GLM-5.2 matches latest US models at finding security bugs, as critics question the US' lax approach in restricting Chinese open models

πŸ”¬ RESEARCH

Prompt Injection in Automated RΓ©sumΓ© Screening with Large Language Models: Single and Multi-Injection Settings

"Large language models (LLMs) are increasingly used to screen and rank job applicants, creating incentives for candidates to strategically manipulate algorithmic hiring systems. We study prompt injection in automated rΓ©sumΓ© screening, defined as subtle self-promotional text that introduces no new qua..."
πŸ”¬ RESEARCH

Reinforcement Learning without Ground-Truth Solutions can Improve LLMs

"Reinforcement learning with verifiable rewards (RLVR) for training LLMs typically rely on ground-truth answers to assign rewards, limiting their applicability to tasks where the ground-truth solution is unknown. We introduce a \textbf{R}anking-\textbf{i}nduced \textbf{VER}ifiable framework (RiVER) t..."
πŸ“° NEWS

How Claude Code and Codex Sandbox Untrusted Code

πŸ”¬ RESEARCH

CARVE: Content-Aware Recurrent with Value Efficiency for Chunk-Parallel Linear Attention

"Recurrent models must forget in order to remember, yet the state of the art decides what to erase without consulting what is stored -- the gate sees only the arriving token, not the memory it is about to modify. This memory-blind gating is one of three coupled defects in the leading delta-rule archi..."
πŸ“° NEWS

Cerberus – a local firewall for AI agents' tool calls

πŸ”¬ RESEARCH

Empowering GUI Agents via Autonomous Experience Exploration and Hindsight Experience Utilization for Task Planning

"Multimodal web agents can assist humans in operating repetitive GUI tasks, where effective task planning is essential for decomposing complex tasks into executable actions. While small open source MLLMs are cost efficient and privacy preserving compared with commercial large models, they suffer from..."
πŸ› οΈ SHOW HN

Show HN: Autonomous CAD design and OpenFOAM optimization loop using local LLMs

πŸ”¬ RESEARCH

Hallucination in World Models is Predictable and Preventable

"Modern generative world models render increasingly realistic action-controllable futures, yet they frequently hallucinate: rollouts remain visually fluent while drifting from the ground-truth dynamics. We hypothesize that hallucination concentrates in low-coverage regions of the state-action space,..."
πŸ“° NEWS

Ford hired AI and sacked humans. It backfired badly

πŸ’¬ HackerNews Buzz: 111 comments πŸ‘ LOWKEY SLAPS
πŸ”¬ RESEARCH

Beyond the Hard Budget: Sparsity Regularizers for More Interpretable Top-k Sparse Autoencoders

"Sparse autoencoders (SAEs) have become a leading tool for interpreting the representations of vision foundation models, decomposing their polysemantic activations into a larger set of sparse, more monosemantic features. The Top-$k$ SAE, a now-standard variant, enforces sparsity architecturally throu..."
πŸ”¬ RESEARCH

Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy

"Building persistent embodied agents in unstructured environments demands unified orchestration of heterogeneous tools spanning both cyber (APIs, IoT) and physical (manipulation, navigation) domains, coupled with autonomous recovery from physical failures that inevitably arise over extended operation..."
πŸ“° NEWS

Sources: Google told Meta around March it couldn't offer all the Gemini capacity Meta wanted to buy, disrupting and delaying some of Meta's internal AI projects

πŸ”¬ RESEARCH

Ask, Don't Judge: Binary Questions for Interpretable LLM Evaluation and Self-Improvement

"Evaluating LLM outputs remains a major bottleneck in NLP: human evaluation is expensive and slow, lexical metrics correlate poorly with human judgments on open-ended generation, and holistic LLM judges often produce opaque scores that are hard to debug. We propose BINEVAL, a framework that decompose..."
πŸ“° NEWS

Open handoff: Thought Tree, a markup/spec idea for modular LLM workflows

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