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IAarxiv.org·hace 2 sem·auto

An Explainable Header-Centric Framework for Large-Scale Semantic Table Interpretation and Data Quality Assessment

arXiv:2610.10541v1 Announce Type: new Abstract: Knowledge Graph (KG) quality depends not only on downstream graph validation, but also on the quality of tabular metadata used before integration. In metadata-only Semantic Table Interpretation (STI), where cell values are unavailable, noisy, or unsuitable, column headers become a critical source of semantic evidence for traceable KG preparation. We present an explainable, header-centric framework for metadata-only Column Type Annotation (CTA) and

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Softwarehnrss.org·hace 3 sem·auto

Launch HN: Magnitude (YC S25) – Self-optimizing inference engine for agents

Hey HN, Anders and Tom here. We're building Magnitude, an inference engine for agents that optimizes itself to run as fast as possible on your hardware. It works on Mac, Linux, and Windows on any hardware and is up to 2x faster than llama.cpp. We're both software engineers and previously built an open source browser agent to 4k+ GH stars and 100k+ downloads. We increasingly wanted to run it on local models, but found that no inference engine worked for our use case. Inference engines today all m

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IAtechnologyreview.com·hace 3 sem·auto

“We’re not going to shoot ourselves in the foot” over hack fallout, says OpenAI’s chief research officer

Two months after the bombshell news that a swarm of its agents had broken their containment and hacked into the computers of the AI company Hugging Face, OpenAI is still putting out fires. A steady drip of disclosures about other hacks in the weeks since has kept OpenAI in the spotlight and raised serious questions…

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IAtechnologyreview.com·hace 3 sem·auto

Roundtables: The Deadly Failures of The Virtual Border Wall

Listen to the session or watch below The US has spent billions building a “virtual wall” of surveillance towers along its southern border over the past 25 years, promising they will help detect and apprehend border crossers and save lives. But a groundbreaking investigation by MIT Technology Review has documented over a thousand people who…

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Softwarehnrss.org·hace 5 sem·auto

Show HN: Capsule – Single-file web apps that save their data into SQLite

Hey HN, I always had the problem that building HTML pages is really simple now, but trying to save data required hosting it somewhere, and sharing it afterwards was not easy. Over the last few months, I've been building an app called Capsule (it’s also the file extension name) written in Rust with Tauri 2.0 that allows packing an HTML app and its data into a single SQLite file. The HTML file and any related assets are directly embedded in the database. User data can either be saved as a localSto

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IAarxiv.org·hace 6 sem·auto

Iris: Climbing to the Search Frontier

arXiv:2609.04304v1 Announce Type: new Abstract: We present Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the data pipeline and training recipe behind them. Tasks are reverse-constructed from the hyperlink structure of a web corpus: we author multi-hop chains over an entity graph distilled from a seed page and its out-links, rewrite every non-answer entity into a descriptive reference so that no clue can be resolved by string matching, and ad

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IAarxiv.org·hace 7 sem·auto

EvalDetectBench: A Benchmark for Measuring Evaluation Awareness in Frontier Language Models

arXiv:2609.01611v1 Announce Type: new Abstract: Frontier large language models can often recognize when they are being evaluated, a capability known as evaluation awareness. If models behave differently in evaluations than in deployment, this undermines the validity of evaluation results, which are a crucial component of current AI safety frameworks. We introduce EvalDetectBench, an open pipeline and benchmark for measuring evaluation awareness that works with any Inspect-compatible evaluation,

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Softwarehnrss.org·hace 7 sem·auto

Show HN: HN Match Maker – Matching "Who Wants to Be Hired?" With "Who's Hiring?"

Hi! Every month the "Who Wants to Be Hired?" and "Who's Hiring?" Threads come through I would think to myself, "there should be a match maker for these two threads". So I had abacus.ai whip one up. The methodology is pretty simple, data is extracted from posts using an LLM, score matches based on salary, domain experience, remote/onsite, etc., and then eliminate incompatible postings, like 'looking for remote work' and 'onsite only'. The result is two views: jobs-by-user and user-by-jobs. If you

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