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se, with … inflated phrasing, and over-long sentences,” University of Minnesota associate professor and cofounder of MorphMind, the company behind the tool, Jie Ding, wrote in its GitHub readme. “They also drift from the author's own voice and lose the precision scholarship depends on.” A previous version of that statement, written prior to a recent readme update, lays the point of the tool bare. Academic Humanizer, the opening of the readme read until an update five days ago, is designed to “st

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e work next. Equivalent mutants exist: some survivors turn out to be semantically identical to the original program, so no test could ever catch them. Few public DAML codebases on GitHub come with a full test suite, so we are glad OpenZeppelin open-sourced its canton-stablecoin reference implementation. Mewt generated hundreds of mutants for it. We ran the highest-priority ones through the existing test suite, and seven of those survived. Three were equivalent mutants or sat behind a guard that

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stdlib call, and decomposition tests a coder’s ability to outline a design. Exercises test Python and JavaScript skills and come in three difficulty levels, Rath explained in the GitHub readme, with seeded generation for fresh variants of the different exercises. “If AI assistance is quietly eroding your ability to code unaided, the chart shows you – before an interview, an outage, or a day without wifi does,” Rath wrote in Atrophy's readme. Users take a baseline exam with one exercise in each

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settling on these safeguards, we also considered enforcing fair internet use with a blocklist or allowlist of particular sites. Unfair internet use falls into two main categories: GitHub (and its many mirrors) and package registries (where agents will often just run npm install to pull the latest release that already contains the solution). Blocklisting turned out to be impractical. Over several iterations of blocking domains and inspecting agent trajectories, our blocklist grew to roughly 1,200

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00,000 organizations, and over 3 million open models published , with new frontier capabilities — agentic coding, video segmentation, speech, embeddings — landing weekly. It's the GitHub of open models, where the community publishes weights, writes model cards, compares evaluations, and pulls models for experimentation. Open models have closed the gap with proprietary models on benchmark after benchmark, and they unlock things proprietary endpoints can't: State-of-the-art is now open. Leading op

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nce alignment as well as the data tooling we use for these in a future post. Build something with PRX, or find a bug in our pipeline? PRX is Apache 2.0 and the model code lives at github.com/Photoroom/PRX . We integrated PRX into the diffusers library and there is a Hugging Face Space to try out our latest version PRX Pixel . Come talk diffusion models and data with us on Discord . Qwen2.5-VL-7B-Captioner-Relaxed CMMD, "Rethinking FID" (Jayasumana et al., 2024) DINOv2 (Oquab et al., 2023), the f

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se signing keys are only valid for a limited time, an attacker typically cannot use the private key, even when it is leaked. We also verify that the kernel was signed by a trusted GitHub workflow from a trusted GitHub repository. Kernel signing is already supported by kernel-builder and we have provided the kernels verify-signature to verify a kernel. Kernels does not verify the signature upon loading a kernel yet, since we would like to test this new functionality more before fully rolling it o

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ndustry. Pattern 1: Workflow Automation Defining a workflow in which the model can operate, test, and iterate is a key design for automation. Karpathy’s autoresearch repo (https://github.com/karpathy/autoresearch) is a clean example of how such a workflow can be constructed. A common workflow follows a goal-oriented loop of plan, execute, observe/test, improve, and execute again until the goal is achieved. The process may trigger proactive requests to users for clarity in task specification or e

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n instead, also with four attempts. Across 57 tested repositories, this process flagged 47 violated properties, with 11 pointing to genuine bugs—5 of them previously unreported on GitHub. One such bug was in the sign function for zigzag decoding of the datrs/varinteger library. On input Std.U64.MAX, the expression (value + 1) overflowed, causing crashes in debug mode and silent corruption in release mode—an edge case that testing and fuzzing would typically miss. Leanstral’s pipeline caught it a

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ing work being done by Patch the Planet matters. Every new capability that helps us find bugs faster is just as available to an attacker, so the advantage goes to whoever finds the bugs and fixes them first. Patch the Planet If you enjoyed this post, share it: X LinkedIn GitHub Mastodon Hacker News Related Posts How we use /goal to find bugs in Patch the Planet July 28, 2026 Over the first few weeks of Patch the Planet, our engineers found three techniques for using /goal, which hands Codex an …

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ihao Liu, Ligeng Zhu, Zijian Zhang, Zenus Zhang, shinan6, DYZhang, Chao Liu, Zhou Yaoyang, gyy0592, AcrossForest, Emin, Qiming Chu, jiaxiaoyu, tastynoob, and zhenwei. 8. References SGLang GitHub Repository; SGLang .claude/skills; SGLang diffusion .claude/skills; AI-Infra-Auto-Driven-SKILLS; AI-Infra-Auto-Driven-SKILLS prompts; Kernel Design Agents (KDA); KernelWiki skill; ncu-report-skill; KDA-Pilot; SGLang Diffusion Advanced Optimizations, LMSYS Blog; OpenAI Codex Prompting: Goal mode; Humanize

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, read our blog post on the Agentic MapReduce architecture. Performance We evaluated Devin Security Swarm on a benchmark of 50 real-world vulnerabilities, each tied to a published GitHub Security Advisory (GHSA) across repositories in Go, Python, JavaScript, Rust, Ruby, C , Java, Swift, PHP, Elixir, Erlang, C, Kotlin, and Dart. Only Devin found three critical vulnerabilities that other tools missed: a PHP sandbox bypass via template injection, an argument injection through metadata value parsing

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eley, and we can’t wait to see what they do next! Thank you to our friends at the Stanford AI Lab for this idea! Baifeng Shi Email: baifeng shi@berkeley.edu Website: https://bfshi.github.io/ Advisor(s): Trevor Darrell Research Blurb: I work on building generalist vision and robotic models. What's next: Member of Technical Staff at Physical Intelligence Charlie Snell Email: csnell22@berkeley.edu Website: https://sea-snell.github.io Advisor(s): Dan Klein Research Blurb: My work aims to understand

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e out on whether it’ll yield anything—is that with Lean, you could imagine having a basically endlessly running program that’s constantly trying to extend Mathlib. Mathlib is this GitHub repository that’s basically all of math written in code. It’s very far from all of math, but they want it to be all of math. It’s written in code where you can ask, “Is this proof correct?” It’s very labor-intensive to write these proofs. There’s a whole subcommunity around it. But you could imagine having an AI

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the increasingly popular Cline, but more on that later. The reason why I am primarily using Qwen-Code when working with Qwen models is that: it is open-source, like Codex (https://github.com/openai/codex) but unlike Claude Code; Qwen models have been specifically optimized for the Qwen-Code harness (more information below); I can run both Codex (with the latest GPT model) and Qwen-Code with a local Qwen model side by side on the same machine without having to switch manually back and forth betwe

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GLang Documentation: HiCache Design; SGLang Blog: HiCache: High-Performance KV Cache Storage with Hierarchical Caching for LLM Serving; Netpreme SGLang X-Mem™ Integration: https://github.com/netpreme/sglang xmem; LinkedIn Engineering Blog: Turbocharging LinkedIn’s Recommendation Systems with SGLang; Qwen3-235B-A22B-Thinking-2507: https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507; SWE-bench: https://github.com/SWE-bench/SWE-bench; Netpreme Coding Agents Experiments: https://github.com/net

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k July 26, 2026 Zig creator calls Bun's Claude Rust rewrite 'unreviewed slop' July 15, 2026 HTTP gets a QUERY method so complex searches can stop pretending to be POST July 14, 2026 Speedier type checks in TypeScript 7.0 as first stable Go release ships July 10, 2026 GitHub cuts short offer to burn repos on CD after mockery ensues A purported jab of Sony's physical media phase-out blows up on GitHub itself July 7, 2026 .NET's long term support is not long term enough, dev complains June 30, 2026

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neering tasks. Every benchmark, whatever its reputation, combines the same three parts: Task set: The work the system is asked to do, from short synthetic Python functions to real GitHub issues paired with the pull requests that fixed them; Evaluation setup: The conditions the system solves the task under, including the system prompt, tools, retrieval, execution environment, and retry logic; Scoring method: The definition of success, whether hidden tests, objective ground-truth answers, or blind

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ore than 60 integrations, and when the platform you need isn't listed, a custom MCP connector fills the gap. Analytics & Business Intelligence Developer Platforms & Infrastructure GitHub Cloudflare Developer Platform Research, Scientific & Public Data Enterprise controls, Connector Credentials, and Connectors in Vibe Code are generally available now. Connectors Playground and Connectors in Workflows are in public preview. All of it is live in Studio. Connectors documentation; Connectors in Vibe

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, only medium models, or all models gives different apparent scaling laws Please cite this work as: Weng, Lilian. “Scaling Laws, Carefully”. Lil’Log (Jun 2026). https://lilianweng.github.io/posts/2026-06-24-scaling-laws/ Or use the BibTex citation: [1] S. Amari, N. Fujita, and S. Shinomoto. “Four Types of Learning Curves. Neural Computation.” 4(4):605–618, 1992. [2] Hestness et al. “Deep Learning Scaling is Predictable, Empirically.” arXiv preprint arXiv:1712.00409, 2017. [3] Rosenfeld et al. “A

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