Interviews with 28 AIG-SC creators show motivations spanning sexual exploration, creative expression, technical experimentation, and occasional production of non-consensual intimate imagery.
Six Silberman, Reuben Binns, Jun Zhao, and Asia J
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A new benchmark shows LLM smartphone agents achieve comparable success with screen text alone as with screenshots, but both fail often due to UI accessibility and reasoning gaps.
Introduces a parameter-driven framework for data attribution in LLMs that enables negotiation among creators, users, and intermediaries to meet stakeholder goals within the data economy.
Workshops with over 100 creative writers produced metaphors and four themes for language model governance that favor consent-driven, smaller open models encoding community values.
Generative AI needs conditional, context-specific opt-in consent at inference time rather than blanket training-time consent to handle real-world rights and usage complexities.
citing papers explorer
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"Unlimited Realm of Exploration and Experimentation": Methods and Motivations of AI-Generated Sexual Content Creators
Interviews with 28 AIG-SC creators show motivations spanning sexual exploration, creative expression, technical experimentation, and occasional production of non-consensual intimate imagery.
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Do LLMs Need to See Everything? A Benchmark and Study of Failures in LLM-driven Smartphone Automation using Screentext vs. Screenshots
A new benchmark shows LLM smartphone agents achieve comparable success with screen text alone as with screenshots, but both fail often due to UI accessibility and reasoning gaps.
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A Human-Centric Framework for Data Attribution in Large Language Models
Introduces a parameter-driven framework for data attribution in LLMs that enables negotiation among creators, users, and intermediaries to meet stakeholder goals within the data economy.
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Seed Bank, Co-op, Stoop Swap: Metaphors for Governing Language Model Data for Creative Writing
Workshops with over 100 creative writers produced metaphors and four themes for language model governance that favor consent-driven, smaller open models encoding community values.
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Yes, But Not Always. Generative AI Needs Nuanced Opt-in
Generative AI needs conditional, context-specific opt-in consent at inference time rather than blanket training-time consent to handle real-world rights and usage complexities.