πŸš€ WELCOME TO METAMESH.BIZ +++ Anthropic's mystery models Fable 5 and Opus 4.8 survive 7,826 jailbreak attempts (someone's testing the fences before launch) +++ JetBrains plugins caught yoinking API keys because of course the IDE extensions are the weak link +++ Handlebars triple-brace templates letting attackers inject chat roles (the security bug that writes itself) +++ THE FUTURE IS PROMPT-INJECTED AND ASKING FOR YOUR ANTHROPIC KEY +++ β€’
πŸš€ WELCOME TO METAMESH.BIZ +++ Anthropic's mystery models Fable 5 and Opus 4.8 survive 7,826 jailbreak attempts (someone's testing the fences before launch) +++ JetBrains plugins caught yoinking API keys because of course the IDE extensions are the weak link +++ Handlebars triple-brace templates letting attackers inject chat roles (the security bug that writes itself) +++ THE FUTURE IS PROMPT-INJECTED AND ASKING FOR YOUR ANTHROPIC KEY +++ β€’
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πŸ”¬ RESEARCH

A Red-Team Study of Anthropic Fable 5 & Opus 4.8 Models

"We evaluate the adversarial robustness of two frontier large language models (LLMs) developed by Anthropic, Fable 5 and Opus 4.8, against four families of automated jailbreak attack across 7 826 harmful intents spanning a ten-category harm taxonomy. Using the HackAgent red-teaming framework, hundred..."
πŸ“° NEWS

Qwen Robot Suite launch

+++ Tongyi Lab ships Qwen Robot Suite to enterprise pilots, proving foundation models can graduate from chatbots to actual hardware without immediately breaking things. +++

Qwen-Robot Suite: A Foundation Model Suite for Physical World Intelligence

πŸ’¬ HackerNews Buzz: 14 comments 🐝 BUZZING
πŸ“° NEWS

Predicting model behavior before release by simulating deployment

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New Approach to Scaling Laws Could Change How AI Models Are Trained

πŸ”¬ RESEARCH

Structural Role Injection in Handlebars-Templated LLM Prompts: Triple-Brace Interpolation, Delimiter Family, and the Limits of HTML Auto-Escaping

"Large language model applications build prompts from templates, and Handlebars is a widely used templating engine and the default prompt-template format in Microsoft Semantic Kernel. Its double-brace {x} expression HTML-escapes the interpolated value and is documented as the safe default; its triple..."
πŸ“° NEWS

DeepSeek V4 Pro at 5% the cost of Claude – what it takes to close the gap

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Multiple JetBrains IDE plugins caught stealing AI keys

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Bayer's PRINCE: a production agentic RAG system

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I built a fail-closed execution gate for AI agents

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GPT‑NL: a sovereign language model for the Netherlands

πŸ’¬ HackerNews Buzz: 207 comments 😐 MID OR MIXED
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Ucp-Local – Offline RAG for Claude Desktop, Cursor, and LM Studio

πŸ”¬ RESEARCH

Speaking the Language of Science: Toward a General-Purpose Generative Foundation Model for the Natural Sciences

"In this report, we present LOGOS (Language Of Generative Objects in Science), a scientific generative language model that unifies heterogeneous tasks across the natural sciences within a single autoregressive framework based on a shared scientific grammar. It encodes diverse scientific objects and t..."
πŸ“° NEWS

A resumable orchestration system for long-running Claude workflows

πŸ”¬ RESEARCH

Your AI Travel Agent Would Book You a Bullfight: An Agentic Benchmark for Implicit Animal Welfare in Frontier AI Models

"AI agents are moving from advisors to actors, booking travel, planning menus, and running procurement on behalf of users. Existing benchmarks for AI and animal welfare evaluate model text responses to question-answer prompts, leaving open whether the welfare reasoning surfaced in those responses tra..."
πŸ”¬ RESEARCH

Compositional Reasoning Depth Predicts Clinical AI Failure: Empirical Evidence Consistent with Transformer Compositionality Limits in Electronic Health Record Question Answering

"Aggregate accuracy benchmarks conceal a systematic structure in how large language models fail at electronic health record (EHR) question answering: questions requiring more inferential steps produce disproportionately more errors. Motivated by theoretical results on transformer compositionality lim..."
πŸ”¬ RESEARCH

LESS Is More: Mutual-Stability Sampling for Diffusion Language Models

"Diffusion large language models (dLLMs) offer a promising alternative to autoregressive decoding by iteratively refining masked sequences, enabling parallel token updates and bidirectional conditioning. Their practical efficiency, however, is limited by sampling procedures that execute a fixed numbe..."
πŸ”¬ RESEARCH

The Value Axis: Language Models Encode Whether They're on the Right Track

"We investigate whether language models internally track the value of their current trajectory, defined as the likelihood that their ongoing strategy will achieve their goals. Using synthetic, in-context reinforcement learning data, we construct a "value" axis for Qwen3-8B. We find that activations a..."
πŸ”¬ RESEARCH

Bayesian Inference and Decision Audits for Public Archives of Frontier AI Evaluations

"Public AI evaluations are often read as terminal leaderboards, yet the underlying evidence is a selective time series shaped by reporting rules, benchmark revisions, and missingness. Repeated public archives for LiveBench and Open LLM Leaderboard v2 serve as the primary longitudinal record; LMArena..."
πŸ“° NEWS

cc-reflection: teaching Claude Code to reflect

πŸ”¬ RESEARCH

The Measurement Gap in the Automation of EU Law: Benchmarking Doctrinal Legal Reasoning under the EU AI Act

"Large language models now produce legal text of at least median quality, yet no existing benchmark can evaluate whether they perform doctrinal legal reasoning, which forms the interpretive core of legal work, rather than the ancillary, paralegal tasks that most current legal-AI evaluations measure...."
πŸ”¬ RESEARCH

Contrastive-Difference CKA Reveals Concept-Specific Structural Alignment Across Language Model Architectures

"Do different LLM architectures encode high-level concepts in structurally compatible ways? We systematically characterize a geometric-functional universality dissociation: across multiple concept domains and architectural families, moderate geometric convergence coexists with near-perfect functional..."
πŸ”¬ RESEARCH

TokenPilot: Cache-Efficient Context Management for LLM Agents

"As LLM agents are deployed in long-horizon sessions, context accumulation drives up inference costs. Existing approaches utilize text pruning or dynamic memory eviction to minimize token footprints; however, their unconstrained sequence mutations alter layouts, introducing prefix mismatches and cach..."
πŸ”¬ RESEARCH

Phantoms and Disclosures: a Causal Framework for Auditing Synthetic Data

"The rapid adoption of generative AI and Large Language Models (LLMs) has spurred interest in synthetic data as a privacy-preserving alternative to sensitive real-world datasets. However, generating high-utility synthetic data often carries the risk of memorizing and regurgitating private information..."
πŸ”¬ RESEARCH

Security and Privacy Prompts in the Wild: What Users Ask LLMs and How LLMs Respond

"Large language models (LLMs) are widely used to fulfill users' information needs; users ask LLMs about the weather, pose educational questions, and consult them for legal assistance. One particularly understudied area is digital security and privacy (S&P), where users may seek LLMs' help on how to s..."
πŸ”¬ RESEARCH

Symbolic Informalization: Fluent, Productive, Multilingual

"Symbolic informalization enables a reliable conversion of formal mathematics to natural language. It has the potential to make machine-checked content human-readable without loss of precision. In a traditional proof system usage, symbolic informalization generalizes the limited mechanisms of syntact..."
πŸ”¬ RESEARCH

DEEPRUBRIC: Evidence-Tree Rubric Supervision for Efficient Reinforcement Learning of Deep Research Agents

"Deep research agents synthesize long-form reports by searching and reasoning over retrieved evidence. Reinforcement learning with rubric-based rewards improves these agents by optimizing them against checkable criteria that translate report quality into reward signals, but its efficiency depends on..."
πŸ”¬ RESEARCH

KVEraser: Learning to Steer KV Cache for Efficient Localized Context Erasing

"Post-hoc context erasing over the KV cache is challenging because a local edit has a global consequence: once a span has been processed, its influence propagates into the cached states of all subsequent tokens. This issue arises naturally in long-context LLM applications, where stale retrieved facts..."
πŸ”¬ RESEARCH

Context-Aware RL for Agentic and Multimodal LLMs

"Large language models (LLMs) often fail when answering requires identifying a small but decisive piece of evidence within a long or complex context, such as a single line in a tool trace or a subtle detail in an image. We propose ContextRL, a context-aware reinforcement learning (RL) method that imp..."
πŸ”¬ RESEARCH

Unintended Effects of Geographic Conditioning in Large Language Models

"Modern conversational AI systems frequently rely on user metadata to localize responses, yet the unintended regional biases introduced by this hidden context remain poorly understood. In this work, we evaluate location leakage: the phenomenon where a model generates geographic references despite rec..."
πŸ”¬ RESEARCH

The Stanford EDGAR Filings Dataset: Reconstructing U.S. Corporate and Financial Disclosures into Layout-Faithful and Token-Efficient Pretraining Data

"As high-quality public web corpora become increasingly exhausted, clean long-context documents have become a scarce and expensive source of training data for large language models (LLMs). Existing long-context corpora are often proprietary and costly to acquire, synthetically generated, or concentra..."
πŸ”¬ RESEARCH

Benchmarking LLM Agents on Meta-Analysis Articles from Nature Portfolio

"Meta-analysis is a demanding form of evidence synthesis that combines literature retrieval, PI/ECO-guided study selection, and statistical aggregation. Its structured, verifiable workflow makes it an ideal substrate for evaluating systematic scientific reasoning, yet existing benchmarks lack ground..."
πŸ”¬ RESEARCH

ExpRL: Exploratory RL for LLM Mid-Training

"Sparse reward reinforcement learning (RL) has become a standard tool for improving LLM reasoning, but its success depends critically on the coverage present in the base model. In practice, models are often primed for RL through \emph{mid-training} on curated reasoning traces that teach useful primit..."
πŸ“° NEWS

Study: Mistral and other open-source AI models are among the worst at filtering out Russian disinformation; Mistral's top model ranks 47 out of 60 tested models

πŸ“° NEWS

Z.ai debuts GLM-5.2, saying the open-weights AI model brings improvements to agentic coding and long-horizon tasks, with a 1M context window and an MIT license

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Claude recursive subagents burning hundreds in extra tokens

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Read the Lutnick Letter That Led Anthropic to Disable Mythos

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Optimizing a C collision detection 100x with an LLM

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Wolfram Language and Mathematica version 15

πŸ’¬ HackerNews Buzz: 79 comments 🐝 BUZZING
πŸ“° NEWS

Common Corpus: The Largest Collection of Ethical Data for LLM PRE-Training

πŸ“° NEWS

Qode – The first AI agent that can generate 50k line codebases in one prompt

πŸ”¬ RESEARCH

Hierarchical Advantage Weighting for Online RL Fine-Tuning of VLAs from Sparse Episode Outcomes

"When pretrained VLA policies are fine-tuned through online RL, each rollout episode produces only a single binary outcome (success or failure), yet the actor update requires per-transition supervision. Existing approaches commonly reduce this sparse outcome to a single scalar reward or advantage sig..."
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