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Found 10 papers, 4 papers with code
Authenticated Delegation and Authorized AI Agents
The rapid deployment of autonomous AI agents creates urgent challenges around authorization, accountability, and access control in digital spaces.
Bridging the Data Provenance Gap Across Text, Speech and Video
In this work we conduct the largest and first-of-its-kind longitudinal audit across modalities--popular text, speech, and video datasets--from their detailed sourcing trends and use restrictions to their geographical and linguistic representation.
Consent in Crisis: The Rapid Decline of the AI Data Commons
To our knowledge, we conduct the first, large-scale, longitudinal audit of the consent protocols for the web domains underlying AI training corpora.
Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?
New capabilities in foundation models are owed in large part to massive, widely-sourced, and under-documented training data collections.
Leveraging Large Language Models for Learning Complex Legal Concepts through Storytelling
Finally, we find that learning with stories shows a higher retention rate for non-native speakers in the follow-up assessment.
Verifiable evaluations of machine learning models using zkSNARKs
In a world of increasing closed-source commercial machine learning models, model evaluations from developers must be taken at face value.
LePaRD: A Large-Scale Dataset of Judges Citing Precedents
We present the Legal Passage Retrieval Dataset LePaRD.
The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI
The race to train language models on vast, diverse, and inconsistently documented datasets has raised pressing concerns about the legal and ethical risks for practitioners.
The Law and NLP: Bridging Disciplinary Disconnects
Legal practice is intrinsically rooted in the fabric of language, yet legal practitioners and scholars have been slow to adopt tools from natural language processing (NLP).
Art and the science of generative AI: A deeper dive
A new class of tools, colloquially called generative AI, can produce high-quality artistic media for visual arts, concept art, music, fiction, literature, video, and animation.
