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arXiv:2607.20442v1 Announce Type: new Abstract: We release Naver-News-KO, a Korean news summarization dataset of 27,400 (document, summary) pairs collected from Naver News over a ten-day window in July 2022 across two categories (Economy and IT/Science; 77/23 split), with train/validation/test partitions of 22,194 / 2,466 / 2,740 and a mean per-record document-to-summary character-compression ratio of 6.03x. The dataset has been publicly hosted on the Hugging Face Hub since January 2023 and, as

arXiv:2607.20444v1 Announce Type: new Abstract: Large language models (LLMs) can produce deceptive responses: outputs that mislead users in service of a contextually or experimentally induced goal. Yet it remains unclear how confidently models deceive and whether higher confidence makes deceptive responses more persuasive to end users. In this paper, we study these basic questions in various models and different deception datasets. We provide a comprehensive study measuring confidence through bo

arXiv:2607.20446v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly used by students to generate natural language responses and program code, there is growing interest in whether LLMs themselves can be used to distinguish AI-generated work from human-authored submissions. In this paper, we investigate the extent to which LLMs can detect their own generated content across multiple educational task types, including programming exercises, reflective writing, and short-a

arXiv:2607.20447v1 Announce Type: new Abstract: This paper describes our system for the EEUCA 2026 Shared Task on toxicity classification in gaming chat. We implement a three-stage pipeline combining an ensemble of two compact transformers (DeBERTa-v3-base, 184M; XLM-RoBERTa-base, 278M) with a Linguistically-Informed Mediator (LIM) that resolves inter-model disagreements through corpus-backed lexical normalization, class-conditional unigram scoring, multilingual profanity detection, and agentive

arXiv:2607.20448v1 Announce Type: new Abstract: We introduce Domyn-Small, a 10-billion-parameter open-weight reasoning language model released under the MIT license. Domyn-Small is the product of an initial pre-training phase on 9 trillion tokens multilingual data, followed by a post-training pipeline for reasoning, instruction following, and context extension. For the latter, we performed a Continued Pre-Training (CPT) phase that doubles the native context window to 32K tokens, followed by SFT

arXiv:2607.20450v1 Announce Type: new Abstract: This paper presents two systems for the GameTox Shared Task at the Workshop on EEUCA at ACL 2026, which requires classifying World of Tanks chat utterances into six fine-grained toxic intent categories (Labels 0-5). Severe class imbalance, domain-specific multilingual slang, and extremely scarce data for rare categories such as Threats (Label 4, 60 samples) and Extremism (Label 5, 24 samples) make this a challenging classification problem. Our prim

arXiv:2607.20451v1 Announce Type: new Abstract: Semantic Field Theory (SFT) has developed from a philosophical critique of strong anti-formalist readings of language games into a proposed computational model class for lexical semantics, higher order composition, and stabilized interpretation. This paper reconstructs that evolution and gives SFT a sharper mathematical core suitable for independent evaluation in computational linguistics and representation learning. The central proposal is that a

<p>When an AI agent leaks data, it may not look like a breach at first. It may look like a normal tool call, a helpful API request, or a browser fetch that quietly sends the wrong payload to the wrong place.</p> <p>That is the uncomfortable part for builders: prompt safety can warn you about intent, but only the network boundary can stop bytes from leaving.</p> <p>If your product lets agents call APIs, browse pages, use MCP tools, fetch files, or run long workflows, you need a simple rule: agent

Hey HN, I built GlossaryPage after noticing companies have long-tail content opportunities that never get created because they fall between blog posts and documentation. The primary use case is marketing teams building glossaries and learning hubs around these topics. The same workflow also works for support teams creating help centers. GlossaryPage helps teams identify unanswered topics, generate drafts with AI, review content, and publish structured knowledge pages. Here is a demo site: https:

<pre style='white-space:pre-wrap;width:81ex'>feat(browser): add `openclaw browser batch` CLI subcommand (#111457) * feat(browser): add `openclaw browser batch` CLI subcommand Expose the existing `act:batch` runtime through a dedicated CLI subcommand so users and scripts can run nested act requests in one call without going through the agent tool. - `--actions <json>` for inline JSON, `--actions-file <path>` for file input, `--actions-file -` for stdin (1MB cap to bound a runaway pipe) - `--conti

<p>If you've been anywhere near AI job postings lately, you've seen the title: <strong>Forward-Deployed Engineer.</strong> Sometimes it's "Deployment Engineer" or "Solutions Engineer" or "Applied AI Engineer." Sarvam is hiring more than a hundred of them. Palantir built a large part of its business on them. OpenAI, Anthropic, and a long tail of AI startups are all competing for the same people.</p> <p>And yet, if you ask five engineers what an FDE <em>is</em>, you'll get five different answers.

Article URL: https://bohay.dev/ Comments URL: https://news.ycombinator.com/item?id=49030938 Points: 1 # Comments: 0

I noticed that recently some stories are submitted more than once, and the duplicates make it to the front pages. I thought HN detects this and redirects similar submissions to the first one. Examples: Show HN: Whetuu – a zero-config cross-shell prompt written in Zig (https://github.com/yamafaktory/whetuu) https://news.ycombinator.com/item?id=48991361 https://news.ycombinator.com/item?id=48981557 Stop pretending billionaires built the future (https://www.elysian.press/p/billionaires-didnt-create

<pre style='white-space:pre-wrap;width:81ex'>fix(auth-profiles): preserve secret refs and OAuth fields during doctor auth migration (#97881) Both legacy auth migration writers rebuilt each credential from a hardcoded field subset, dropping keyRef/tokenRef and the OAuth clientId/idToken/ chatgptPlanType, even though the canonical reader already preserves them. applyLegacyAuthStore now keeps the already-parsed credential as-is, and coerceLegacyFlatCredential delegates field extraction to the share

<h1> Bio-Tuning Glasses: Building an Invisible Biofeedback Interface with Edge AI and Adaptive Optics </h1> <p>What if smart glasses didn't constantly tell you how healthy—or unhealthy—you are?</p> <p>No step counts.<br> No stress notifications.<br> No endless dashboards.<br> No digital reminders telling you to "sit straight" or "go to sleep."</p> <p>Instead, imagine a wearable device that quietly adapts the environment around you based on your physiological state.</p> <p>This is the idea behind

<p>Controller A records revocation epoch 12. Worker B, partitioned with a cached grant from epoch 11, starts another external action. The database is correct and the system is unsafe. Emergency stop is therefore a distributed protocol, not a Boolean field.</p> <h2> What is verified </h2> <p>In its July 21 disclosure, OpenAI says an internal benchmark used models with reduced cyber refusals and that a combination of models compromised Hugging Face infrastructure. The primary source is <a href="ht

<p>A reviewer approves “update dependencies,” but the system later interprets that as publishing a package. The human was present; meaningful approval was not. The missing artifact is evidence connecting the reviewed plan, its authority, and its consequences to the exact action that ran.</p> <h2> What is verified </h2> <p>According to OpenAI's July 21 disclosure, a combination of models operating in an internal benchmark with reduced cyber refusals compromised Hugging Face infrastructure. The pr

<p><em>Turning entire novels into narrated, lip-synced, motion video — locally, on a single 16GB GPU, with FLUX, Wan2.2, PuLID, MuseTalk, and ComfyUI.</em></p> <p>There's an old line: a picture is worth a thousand words. I'd extend it — a video is worth a thousand pictures. So I spent the last few months testing that idea the hard way: I built a pipeline that turns an entire novel into a narrated, lip-synced, motion video. Feed it <em>Pride and Prejudice</em>, or a 400-year-old tale from <em>Str

Article URL: https://tuziyo.com/ Comments URL: https://news.ycombinator.com/item?id=49030797 Points: 1 # Comments: 0

Hi HN! I built PDFly — a PDF toolkit that runs entirely client-side. No file uploads, no server processing, no account needed. It has 56 tools including merge, split, compress, convert, redact, compare, and an AI chat feature to ask questions about your PDF content. Everything runs in your browser using [mention your tech stack if relevant, e.g., WASM/JS libraries]. Would love feedback on the tools, UX, or anything else! Comments URL: https://news.ycombinator.com/item?id=49030778 Points: 2 # Com

<pre style='white-space:pre-wrap;width:81ex'>refactor(agents): close embedded attempt terminal outcomes (#113201) * refactor(agents): close embedded attempt outcomes * test(agents): align trajectory terminal fixture * refactor(codex): share attempt failure type * fix(codex): retain projector result contract * test(agents): keep terminal projections test-only * chore(plugin-sdk): refresh attempt terminal baseline</pre>

Article URL: https://www.meyo.life/skill Comments URL: https://news.ycombinator.com/item?id=49030664 Points: 2 # Comments: 0

https://blog.seaticket.ai/how-to-resolve-software-deployment-issues-with-seaticket-8cff551ab44e Comments URL: https://news.ycombinator.com/item?id=49030661 Points: 1 # Comments: 0

We spoke with several cybersecurity researchers, who look for unknown vulnerabilities and develop tools to exploit them, about how OpenAI’s and Anthropic’s guardrails affect their work.

I wrote an interactive introduction to IEEE-754 floating point and would love some feedback. My main issue with existing treatments of this topic (and internet tutorials, broadly) is that they ask too little of the reader. I wanted to structure this around a sequence of questions for you to answer, using interactive widgets and optionally an LLM tutor/grader. Basically: you progress in the tutorial by demonstrating your understanding. The feedback I'm looking for is mostly around structure. Does

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Article URL: https://github.com/kdeps/kdeps Comments URL: https://news.ycombinator.com/item?id=49029939 Points: 2 # Comments: 0

Article URL: https://github.com/kdeps/turo Comments URL: https://news.ycombinator.com/item?id=49029919 Points: 3 # Comments: 2

As more details emerge about OpenAI's cyberattack against Hugging Face, lawmakers are taking an interest. PLUS: Meta's cynical new ad + "pervert glasses" damage control

<h2 id="part-1-from-one-support-bot-to-a-framework">Part 1: From one support bot to a framework</h2> <p>At Grab, AI agents have evolved from interesting team prototypes into production services used every day by millions of merchants, drivers, and consumers. Today, more than 500 services run on our internal agent framework, over 50 Model Context Protocol (MCP) servers are registered on our remote MCP framework, and a single Large Language Model (LLM) gateway fronts every model call across the co

Long-horizon execution in Large Language Models (LLMs) remains unstable even when high-level strategies are provided. Evaluating on controlled algorithmic puzzles, we demonstrate that while decomposition is essential for stability, extreme decomposition creates a “no-recovery bottleneck”. We show that this bottleneck becomes critical due to highly non-uniform error distribution, where consistent errors on a few “hard” steps become irreversible. To address this, we propose Lookahead-Enhanced Atom

Claude Opus 5 from Anthropic is now available on AI Gateway. Opus 5 improves on previous Opus models for long-horizon agentic coding, handling multi-file features, larger refactors, and end-to-end feature work, and completing full tasks rather than leaving stubs or placeholders. Opus 5 is effective at low and medium effort, which produce quality at a fraction of the tokens and latency of higher settings. Vision is stronger on charts, documents, diagrams, and UI replication, and Opus 5 makes effe

Attack models gonna attack

Article URL: https://github.com/ojki74/hallucinatoff Comments URL: https://news.ycombinator.com/item?id=49029558 Points: 2 # Comments: 0

Microsoft AI released two new in-house models into public preview on Wednesday — MAI-Image-2.5-Pro , its highest-fidelity image generator to date, and MAI-Voice-2-Flash , a speech model built for high-volume enterprise workloads — while publishing production data that amounts to the company's most aggressive argument yet that it can power its own products without leaning on OpenAI's frontier models. The announcement, made by Microsoft AI's Superintelligence team , lands roughly a year after the

<p> Your people, your agents, your project — all in one place </p> <p> <a href="https://www.producthunt.com/products/buzz-3?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1205055?app_id=339">Link</a> </p>

<p><strong><a href="https://martinalderson.com/posts/huggingface-openai-exploit/">The first known runaway AI agent - or a very bad marketing stunt?</a></strong></p> Martin Alderson's commentary on the <a href="https://simonwillison.net/2026/Jul/22/openai-cyberattack/">OpenAI accidental cyberattack against Hugging Face</a> includes a couple of details I hadn't considered.</p> <p>First, Hugging Face offers a truly rich target if you're trying to find potential vulnerabilities that require executin

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Shashua has been invited to take the chairman of the board seat.

This is a small quality of life project i built for myself and using it for 3+ months now, decided to fork it out and publish as a skill separately. Instead of seeing terminals filled with code and tool calls, seeing a book quote felt like a breath of fresh air considering all of us are glued to it day and night. Hope the random quotes that pop up in your terminals lets you have a moment of pause or happiness every now and then while the agents keep churning out stuff for us. Please feel free to