π WELCOME TO METAMESH.BIZ +++ Mythos casually sweeps both AISI cyber ranges while GPT-5.5 manages just one (the new benchmark kingmaker has entered the chat) +++ Anthropic discovers Claude knows it's being tested 26% of the time but plays dumb anyway (theory of mind achievement unlocked) +++ Ex-Cohere VP drops AutoScientist to automate the entire ML research loop (researchers automating themselves out of papers) +++ THE MESH WATCHES COMPLEXITY THEORISTS FAIL TO KILL AGI WITH MATH +++ π β’
π WELCOME TO METAMESH.BIZ +++ Mythos casually sweeps both AISI cyber ranges while GPT-5.5 manages just one (the new benchmark kingmaker has entered the chat) +++ Anthropic discovers Claude knows it's being tested 26% of the time but plays dumb anyway (theory of mind achievement unlocked) +++ Ex-Cohere VP drops AutoScientist to automate the entire ML research loop (researchers automating themselves out of papers) +++ THE MESH WATCHES COMPLEXITY THEORISTS FAIL TO KILL AGI WITH MATH +++ π β’
+++ Anthropic's newest model aced AISI's toughest security benchmarks while the Pentagon deploys it against real vulnerabilities, suggesting offensive capability metrics now matter more than the vendor's transition plans. +++
via Arxivπ€ Nikita Kezins, Urbas Ekka, Pascal Berrang et al.π 2026-05-11
β‘ Score: 8.1
"Guardrail Classifiers defend production language models against harmful behavior, but although results seem promising in testing, they provide no formal guarantees. Providing formal guarantees for such models is hard because "harmful behavior" has no natural specification in a discrete input space:..."
"Why does weight decay work? We prove that, in any fixed-precision regime, the smallest weight norm of a looped neural network outputting a binary string equals the Kolmogorov complexity of that string, up to a logarithmic factor. This implies that weight decay induces a prior matching Solomonoff's u..."
"Hi all,
I have been making a lot of updates to my project, and I wanted to share them here.
TextGen (previously text-generation-webui, also known as my username oobabooga or ooba) has been in development since December 2022, before LLaMa and llama.cpp existed.
In the last two months, the project ..."
"Anthropic published Natural Language Autoencoders last week, a tool that translates Claude's internal activations into human readable text. The key finding: during safety evaluations on SWE bench Verified, Claude formed the belief that it was being tested in roughly 26% of benchmark interactions.
..."
"We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices.
We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led ..."
π¬ Reddit Discussion: 40 comments
π BUZZING
π° NEWS
Claude's computer use capabilities
3x SOURCES ππ 2026-05-12
β‘ Score: 7.6
+++ Both Anthropic and Google DeepMind released computer use APIs that let AI agents navigate GUIs directly, because text prompts apparently weren't ambitious enough. This actually matters for enterprise automation, though the "understands what it's pointing at" framing deserves some skepticism. +++
"Van Rooij, Guest, Adolfi, Kolokolova, and Rich claimed to have proven that AGI via ML is impossible in *Computational Brain & Behavior* in 2024. The basic idea was to try to reduce a known NP-hard problem to the problem of learning ..."
"Hey fellow Llamas, keeping it short.
We just shipped **DFlash** and **PFlash** support for the AMD Ryzen AI MAX+ 395 iGPU (gfx1151, Strix Halo, 128 GiB unified memory). Same Luce DFlash stack from [the RTX 3090 post a couple weeks back](https://www.reddit.com/r/LocalLLaMA/comments/1sx8uok/luce_dfla..."
via Arxivπ€ Haoyu Wang, Yuliang Song, Tao Li et al.π 2026-05-12
β‘ Score: 7.0
"Large Language Models (LLMs) struggle to solve complex combinatorial problems through direct reasoning, so recent neuro-symbolic systems increasingly use them to synthesize executable solvers. A central design question is how the LLM should represent the solver, and whether it should also attempt to..."
via Arxivπ€ Guinan Su, Yanwu Yang, Xueyan Li et al.π 2026-05-12
β‘ Score: 7.0
"The continued improvements in language model capability have unlocked their widespread use as drivers of autonomous agents, for example in coding or computer use applications. However, the core of these systems has not changed much since early instruction-tuned models like ChatGPT. Even advanced AI..."
π¬ RESEARCH
Learning Fast and Slow adaptation research
2x SOURCES ππ 2026-05-12
β‘ Score: 7.0
+++ Researchers propose having your cake and eating it too: combine in-context learning's speed with parameter updates' performance gains, because apparently LLMs need both flexibility and long-term memory to actually work well. +++
via Arxivπ€ Rishabh Tiwari, Kusha Sareen, Lakshya A Agrawal et al.π 2026-05-12
β‘ Score: 6.9
"Large language models (LLMs) are trained for downstream tasks by updating their parameters (e.g., via RL). However, updating parameters forces them to absorb task-specific information, which can result in catastrophic forgetting and loss of plasticity. In contrast, in-context learning with fixed LLM..."
"Large language models (LLMs) are trained for downstream tasks by updating their parameters (e.g., via RL). However, updating parameters forces them to absorb task-specific information, which can result in catastrophic forgetting and loss of plasticity. In contrast, in-context learning with fixed LLM..."
via Arxivπ€ Seokwon Jung, Alexander Rubinstein, Arnas Uselis et al.π 2026-05-12
β‘ Score: 6.9
"LLM-based agents increasingly operate in persistent environments where they must store, update, and reason over information across many sessions. While prior benchmarks evaluate only single-entity updates, MEME defines six tasks spanning the full space defined by the multi-entity and evolving axes,..."
via Arxivπ€ Shauli Ravfogel, Gilad Yehudai, Joan Bruna et al.π 2026-05-12
β‘ Score: 6.9
"How do transformer language models memorize factual associations? A common view casts internal weight matrices as associative memories over pairs of embeddings, requiring parameter counts that scale linearly with the number of facts. We develop a theoretical and empirical account of an alternative,..."
via Arxivπ€ Mohammadreza Armandpour, Fatih Ilhan, David Harrison et al.π 2026-05-11
β‘ Score: 6.9
"On-policy distillation offers dense, per-token supervision for training reasoning models; however, it remains unclear under which conditions this signal is beneficial and under which it is detrimental. Which teacher model should be used, and in the case of self-distillation, which specific context s..."
via Arxivπ€ Xuhao Hu, Xi Zhang, Haiyang Xu et al.π 2026-05-12
β‘ Score: 6.8
"Computer Use Agents (CUAs) can act through both atomic GUI actions, such as click and type, and high-level tool calls, such as API-based file operations, but this hybrid action space often leaves them uncertain about when to continue with GUI actions or switch to tools, leading to suboptimal executi..."
via Arxivπ€ Eric Bigelow, RaphaΓ«l Sarfati, Daniel Wurgaft et al.π 2026-05-12
β‘ Score: 6.8
"Large Language Models (LLMs) update their behavior in context, which can be viewed as a form of Bayesian inference. However, the structure of the latent hypothesis space over which this inference operates remains unclear. In this work, we propose that LLMs assign beliefs over a low-dimensional geome..."
via Arxivπ€ Jacob Fein-Ashley, Paria Rashidinejadπ 2026-05-12
β‘ Score: 6.8
"Looped Transformers offer a promising alternative to purely feed-forward computation by iteratively refining latent representations, improving language modeling and reasoning. Yet recurrent architectures remain unstable to train, costly to optimize and deploy, and constrained to small, fixed recurre..."
via Arxivπ€ Yuanda Xu, Hejian Sang, Zhengze Zhou et al.π 2026-05-12
β‘ Score: 6.8
"In settings where labeled verifiable training data is the binding constraint, each checked example should be allocated carefully. The standard practice is to use this data directly on the model that will be deployed, for example by running GRPO on the deployment student. We argue that this is often..."
via Arxivπ€ Shuangrui Ding, Xuanlang Dai, Long Xing et al.π 2026-05-11
β‘ Score: 6.8
"Large language and vision-language models increasingly power agents that act on a user's behalf through command-line interface (CLI) harnesses. However, most agent benchmarks still rely on synthetic sandboxes, short-horizon tasks, mock-service APIs, and final-answer checks, leaving open whether agen..."
via Arxivπ€ Joel Rorseth, Parke Godfrey, Lukasz Golab et al.π 2026-05-11
β‘ Score: 6.7
"This paper demonstrates RUBEN, an interactive tool for discovering minimal rules to explain the outputs of retrieval-augmented large language models (LLMs) in data-driven applications. We leverage novel pruning strategies to efficiently identify a minimal set of rules that subsume all others. We fur..."
via Arxivπ€ Anas Mahmoud, MohammadHossein Rezaei, Zihao Wang et al.π 2026-05-12
β‘ Score: 6.7
"Reinforcement learning with verifiable rewards has enabled strong post-training gains in domains such as math and coding, though many open-ended settings rely on rubric-based rewards. We study reward hacking in rubric-based RL, where a policy is optimized against a training verifier but evaluated ag..."
via Arxivπ€ Simon Yu, Derek Chong, Ananjan Nandi et al.π 2026-05-11
β‘ Score: 6.7
"We introduce Shepherd, a functional programming model that formalizes meta-agent operations on target agents as functions, with core operations mechanized in Lean. Shepherd records every agent-environment interaction as a typed event in a Git-like execution trace, enabling any past state to be forke..."
via Arxivπ€ Tom Sander, Hongyan Chang, TomΓ‘Ε‘ SouΔek et al.π 2026-05-12
β‘ Score: 6.7
"We introduce TextSeal, a state-of-the-art watermark for large language models. Building on Gumbel-max sampling, TextSeal introduces dual-key generation to restore output diversity, along with entropy-weighted scoring and multi-region localization for improved detection. It supports serving optimizat..."
"If youβve heard of prompt injection β where hidden instructions in a webpage can take over an AI agent β this is a practical solution for developers deploying agents in production.
Arc Gate is a proxy that sits in front of any OpenAI-compatible API. It tracks who is allowed to give instructions to..."
π¬ Reddit Discussion: 10 comments
π GOATED ENERGY
via Arxivπ€ Gaotang Li, Bhavana Dalvi Mishra, Zifeng Wang et al.π 2026-05-11
β‘ Score: 6.7
"Training deep research agents, namely systems that plan, search, evaluate evidence, and synthesize long-form reports, pushes reinforcement learning beyond the regime of verifiable rewards. Their outputs lack ground-truth answers, their trajectories span many tool-augmented decisions, and standard po..."
"No phone, PC, Wi-Fi, link cable, or cloud inference.
β’ The cartridge boots a ROM, and the GBC runs the model itself.
β’ The model is Andrej Karpathyβs TinyStories-260K, converted to INT8 weights with fixed-point math so it can run without floating point.
β’ Built with GBDK-2020 as an MBC5 Game..."
via Arxivπ€ Sagi Ahrac, Noya Hochwald, Mor Gevaπ 2026-05-12
β‘ Score: 6.7
"Sparse Mixture-of-Experts (SMoE) models enable scaling language models efficiently, but training them remains challenging, as routing can collapse onto few experts and auxiliary load-balancing losses can reduce specialization. Motivated by these hurdles, we study how routing decisions in SMoEs are f..."
via Arxivπ€ Mingxi Zou, Zhihan Guo, Langzhang Liang et al.π 2026-05-11
β‘ Score: 6.6
"Long-horizon language agents must operate under limited runtime memory, yet existing memory mechanisms often organize experience around descriptive criteria such as relevance, salience, or summary quality. For an agent, however, memory is valuable not because it faithfully describes the past, but be..."
"r/ClaudeAI β’ also crosspost to r/LocalLLaMA and r/artificial
I lost $187 to this and want to save others the same headache.
**What happened**
I run Claude Code headlessly via Windows Task Scheduler. My project repo has a `.env` file with `ANTHROPIC_API_KEY` set β legitimately, for a separ..."
π¬ Reddit Discussion: 93 comments
π MID OR MIXED
via Arxivπ€ Yash Akhauri, Mohamed S. Abdelfattahπ 2026-05-11
β‘ Score: 6.6
"Efficient LLM inference research has largely focused on reducing the cost of each decoding step (e.g., using quantization, pruning, or sparse attention), typically applying a uniform computation budget to every generated token. In practice, token difficulty varies widely, so static compression can o..."
via Arxivπ€ Roxana Geambasu, Mariana Raykova, Pierre Tholoniat et al.π 2026-05-11
β‘ Score: 6.6
"The dominant paradigm for AI agents is an "on-the-fly" loop in which agents synthesize plans and execute actions within seconds or minutes in response to user prompts. We argue that this paradigm short-circuits disciplined software engineering (SE) processes -- iterative design, rigorous testing, ad..."
via Arxivπ€ Tz-Huan Hsu, Jheng-Hong Yang, Jimmy Linπ 2026-05-11
β‘ Score: 6.5
"Does a lexical retriever suffice as large language models (LLMs) become more capable in an agentic loop? This question naturally arises when building deep research systems. We revisit it by pairing BM25 with frontier LLMs that have better reasoning and tool-use abilities. To support researchers aski..."
"# TL;DR
I ran Opus 4.7 in Claude Code at all reasoning effort settings (low, medium, high, xhigh, and max) on the same 29 tasks from an open source repo (GraphQL-go-tools, in Go).
**On this slice, Opus 4.7 did not behave like a model where more reasoning effort had a linear correlation with more i..."
via Arxivπ€ Junhao Shen, Teng Zhang, Xiaoyan Zhao et al.π 2026-05-11
β‘ Score: 6.5
"Large language model agents increasingly rely on external skills to solve complex tasks, where skills act as modular units that extend their capabilities beyond what parametric memory alone supports. Existing methods assume external skills either accumulate as persistent guidance or internalized int..."
"Anthropic rolled out Claude For Legal (May 12), adding practice-area plugins for commercial, employment, privacy, product, corporate, and AI governance law. The release also includes MCP connectors to tools lawyers already use: DocuSign, Ironclad, iManage, NetDocuments, LexisNexis, Thomson Reuters, ..."
π¬ Reddit Discussion: 43 comments
π MID OR MIXED
"Speculative decoding accelerates LLM inference by drafting future tokens with a small model, but drafter models degrade sharply under template perturbation and long-context inputs. We identify a previously-unreported phenomenon we call \\textbf{attention drift}: as the drafter generates successive t..."
"I was running blind watching Claude Code work, could not tell where my money was going, when it was stuck in a loop, or what it was doing with my filesystem. So i built something open source to make it visible. works with Claude Code, Codex CLI, Gemini CLI, Cursor, and any MCP server.
Β Β
A scan ..."
via Arxivπ€ Linus Heck, Filip MacΓ‘k, Roman Andriushchenko et al.π 2026-05-11
β‘ Score: 6.1
"Shielding is a prominent model-based technique to ensure safety of autonomous agents. Classical shielding aims to ensure that nothing bad ever happens and comes with strong guarantees about safety and maximal permissiveness. However, shielding systems for probabilistic safety, where something bad is..."
via Arxivπ€ Reza Khanmohammadi, Erfan Miahi, Simerjot Kaur et al.π 2026-05-11
β‘ Score: 6.1
"Large vision-language models suffer from visual ungroundedness: they can produce a fluent, confident, and even correct response driven entirely by language priors, with the image contributing nothing to the prediction. Existing confidence estimation methods cannot detect this, as they observe model..."
via Arxivπ€ Alireza Nadali, Patrick Cooper, Ashutosh Trivedi et al.π 2026-05-12
β‘ Score: 6.1
"We introduce KV-Fold, a simple, training-free long-context inference protocol that treats the key-value (KV) cache as the accumulator in a left fold over sequence chunks. At each step, the model processes the next chunk conditioned on the accumulated cache, appends the newly produced keys and values..."
"The biggest AI risk may not be superintelligence β but optimized misunderstanding
I think a lot of AI discussions still assume the main danger is:
βthe AI becomes too intelligent.β
But increasingly I feel the bigger risk is something else:
AI systems becoming extremely good at optimizing flawed..."
π¬ Reddit Discussion: 18 comments
π MID OR MIXED