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Type Checking Project Haystack Grids using JSON Schema and Pydantic

Focus to learn more arXiv-issued DOI via DataCite Submission history From: Thomas Hirsch [ view email ] [v1] Tue, 19 May 2026 15:07:37 UTC (38 KB) Full-text links: Access Paper: View a PDF of the paper titled Type Checking Project Haystack Grids using JSON Schema and Pydantic, by Thomas Hirsch and 2 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Pa

pers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle ( What is ? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .

Hollywood-backed nonprofit launches machine-readable AI consent registry

About Us to Social the Standard a Trusted Partner Your Consent About Us to Social the Standard a Trusted Partner Your Consent ! 1 Protect Human Creativity Register Your Consent with Sound Start With Consent RSL Media turns consent into a signal AI can read. It gives people and rightsholders a clear way to say how AI may use their work, identity, characters, and marks. The choices are simple. Allowed This use is approved. Allowed with terms This use is allowed only with conditions, like permission, credit, payment, or limits. Prohibited This use is not allowed. “AI technologies are expanding rampantly, essentially unchecked and unregulated. In order for humans to remain in front of these technologies, consent must be the first consideration. RSL Media is a simple, effective and free solutions-based technology

for facilitating and activating consent. It's also the industry's first practical solution where people everywhere, not just public figures, can assert control over how their work is used by AI.” Cate Blanchett “AI can't respect rights it can't see, and this means human consent is virtually invisible in this new digital era. The right to decide whether AI can use your work or identity should not be reserved for only those who can afford lawyers or have platforms big enough to be heard, it is a basic human right. RSL Media was created to make those choices clear so people can set their own terms, responsible companies can honor them and policymakers have a practical way to make AI protections work in the real world.” Nikki Hexum “Today, rights information is fragmented across contracts, databases and private systems, leaving creators speaking in terms that AI platforms cannot easily interpret or comply with. RSL Media provides a critical infrastructure layer by translating consent and usage rights into a format that can work across systems, for both individuals and AI.” James Everingham “Bringing artists, performers and creators into the consent solution that RSL Media provides is essential to protecting rights, recognizing the value of human creativity and enabling innovation responsibly.” Jacqueline Sabec “Creativity is the most precious and irreplaceable expression of what makes us human. It is born of our lived experience, emotion and vision. In this extraordinary moment of technological change, we have a duty to protect it, and to protect the artists now, and in the future, who dedicate their lives to it and the pursuit of inventing the unknown.” Francesca Amfitheatrof “Of course artists and cultural creatives will inevitably be involved with AI. At the moment, however, AI is merely stealing from us all. This is an urgent and essential initiative. It's also eminently doable, so let's do it without delay.” Dame Emma Thompson “RSL Media has a solution to a very serious problem, and their solution is simple, transparent, and resistant to manipulation. The sooner this independent standard is adopted, the better for all involved.” Steven Soderbergh “Artists have always been inspired by those who went before them, that is how culture develops and reflects the society that it is born in. Every artist knows there is an absolute divide between inspiration and imitation. The one is an extension of the imagination, and the other a block to imagination, at the same time being crass theft.” Dame Helen Mirren “CAA is deeply committed to protecting the creative rights and identities of artists in this ever-evolving digital landscape. The launch of RSL Media represents a ground-breaking step toward empowering artists with clear, enforceable control over how their work and likenesses are used by AI technologies. By providing a standardized consent framework, RSL Media not only safeguards our clients' intellectual property, but also ensures they receive the credit and compensation they deserve in the AI economy.” Kevin Huvane “Music artists have spent the last few years watching their voices, songs and likenesses get vacuumed into AI systems without permission, without credit and without compensation. RSL Media flips the script. By turning consent into a signal that machines can actually read and respect, it gives every creator a practical way to set the terms for how their work is used. The Music Artists Coalition is proud to support RSL Media and

the principle at its core: human creativity deserves human consent.” Ron Gubitz Signatories * Creative Artists Agency * Dame Emma Thompson * Dame Helen Mirren * George Clooney * Javier Bardem * Kristen Stewart * Meryl Streep * Mike Medavoy * Music Artists Coalition * Steven Soderbergh * Tom Hanks * Viola Davis Learn How It Works RSL Media makes creative rights readable at AI scale. It gives trusted registries, representatives, and rightsholders a common way to publish consent, restrictions, and licensing paths. Read the Standard Register Verify your identity through . Declare Set permissions for your identity and creative works. Encode Permissions get translated into machine-readable signals. Verify AI systems and platforms check the RSL Media Registry before using protected rights. Protect Human Creativity Register your consent on the RSL Media Registry and set permissions AI can read. Become a Trusted Partner Your Consent the Standard Resources Read the Standard to Social Us Follow

AI doesn't take jobs. It takes tasks

How AI changes your job Every job is a bundle of tasks, and AI hits them unevenly — some get automated, some get amplified, some stay stubbornly human. Search your job and see the breakdown. Every occupation placed by how AI lands. Bubble size = how many people do the job. Click any bubble for the full breakdown. Market data (growth, openings, pay, education) is straight from the BLS Employment Projections 2024–2034. No estimates. Tasks are verbatim from the U.S. Department of Labor's O*NET database — the real task statements for each occupation. The AI effect on each task is the only assessed layer, classified under a published rubric: automate = AI software can do it end-to-end; augment = AI does much of it but a human directs and is accountable; human = needs physical presence, dexterity, real-time trust, or legal accountability.

Physical/manual work is treated as human (we assess AI, not robots). Search 832 occupations. Click a row for its task breakdown.

The Unfireable Safety Kernel: Execution-Time AI Alignment for AI Agents and Other Escapable AI Systems

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Seth Dobrin [ view email ] [v1] Wed, 24 Jun 2026 17:32:27 UTC (1,057 KB) Full-text links: Access Paper: View a PDF of the paper titled The Unfireable Safety Kernel: Execution-Time AI Alignment for AI Agents and Other Escapable AI Systems, by Seth Dobrin and {\L}ukasz Chmiel View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explo

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Autodata: An agentic data scientist to create high quality synthetic data

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Jason Weston [ view email ] [v1] Wed, 24 Jun 2026 16:08:31 UTC (19,889 KB) Full-text links: Access Paper: View a PDF of the paper titled Autodata: An agentic data scientist to create high quality synthetic data, by Ilia Kulikov and 14 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle C

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InvestPhilBench: A Multi-Layer Dynamic Benchmark for Evaluating Large Language Model Procedural Reasoning in Expert Investment Philosophy

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Mingguang Chen [ view email ] [v1] Wed, 24 Jun 2026 15:53:20 UTC (955 KB) Full-text links: Access Paper: View a PDF of the paper titled InvestPhilBench: A Multi-Layer Dynamic Benchmark for Evaluating Large Language Model Procedural Reasoning in Expert Investment Philosophy, by Mingguang Chen and 1 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliogra

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WinDOM: Self-Family Distillation for Small-Model GUI Grounding

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Chengheng Li Chen [ view email ] [v1] Wed, 24 Jun 2026 15:35:29 UTC (1,581 KB) Full-text links: Access Paper: View a PDF of the paper titled WinDOM: Self-Family Distillation for Small-Model GUI Grounding, by Chengheng Li-Chen and 3 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Paper

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Agentic System as Compressor: Quantifying System Intelligence in Bits

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Zihan Qin [ view email ] [v1] Wed, 24 Jun 2026 15:32:49 UTC (1,615 KB) Full-text links: Access Paper: View a PDF of the paper titled Agentic System as Compressor: Quantifying System Intelligence in Bits, by Zihan Qin and 1 other authors View PDF HTML (experimental) TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers

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AI Snitches Get Glitches: Towards Evading Agentic Surveillance

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Hyejun Jeong [ view email ] [v1] Wed, 24 Jun 2026 13:50:22 UTC (1,328 KB) Full-text links: Access Paper: View a PDF of the paper titled AI Snitches Get Glitches: Towards Evading Agentic Surveillance, by Hyejun Jeong and 3 other authors View PDF TeX Source view license Current browse context: < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers?

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