732 citations · 790 across the 18 of their papers we have counts for
19 papers
AISPA: User-Centric System Prompt Auditing for Large Language Model Applications
Xiangning Lin, Shenzhe Zhu, Shu Yang +23
System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout commercial AI products, but are r…
Intentionality is a Design Decision: Measuring Functional Intentionality for Accountable AI Systems
Allessia Chiappetta, Robert Mahari
As AI systems increasingly exhibit autonomous, goal-directed, and long-horizon behavior, users lack a standardized way to detect the degree to which a system functions like an inte…
Community-centric modeling of citation dynamics explains collective citation patterns in science, law, and patents
Sadamori Kojaku, Robert Mahari, Sandro Claudio Lera +3
Many human knowledge systems, such as science, law, and invention, are built on documents and the citations that link them. Citations, while serving multiple purposes, primarily fu…
Authenticated Delegation and Authorized AI Agents
Tobin South, Samuele Marro, Thomas Hardjono +5
The rapid deployment of autonomous AI agents creates urgent challenges around authorization, accountability, and access control in digital spaces. New standards are needed to know…
Bridging the Data Provenance Gap Across Text, Speech and Video
Shayne Longpre, Nikhil Singh, Manuel Cherep +40
Progress in AI is driven largely by the scale and quality of training data. Despite this, there is a deficit of empirical analysis examining the attributes of well-established data…
Early Career Citations Capture Judicial Idiosyncrasies and Predict Judgments
Robert Mahari, Sandro Claudio Lera
Judicial impartiality is a cornerstone of well-functioning legal systems. We assemble a dataset of 112,312 civil lawsuits in U.S. District Courts to study the effect of extraneous…
Data-Driven Law Firm Rankings to Reduce Information Asymmetry in Legal Disputes
Alexandre Mojon, Robert Mahari, Sandro Claudio Lera
Selecting capable counsel can shape the outcome of litigation, yet evaluating law firm performance remains challenging. Widely used rankings prioritize prestige, size, and revenue…
Consent in Crisis: The Rapid Decline of the AI Data Commons
Shayne Longpre, Robert Mahari, Ariel Lee +46
General-purpose artificial intelligence (AI) systems are built on massive swathes of public web data, assembled into corpora such as C4, RefinedWeb, and Dolma. To our knowledge, we…
Insights from an experiment crowdsourcing data from thousands of US Amazon users: The importance of transparency, money, and data use
Alex Berke, Robert Mahari, Sandy Pentland +2
Data generated by users on digital platforms are a crucial resource for advocates and researchers interested in uncovering digital inequities, auditing algorithms, and understandin…
Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?
Shayne Longpre, Robert Mahari, Naana Obeng-Marnu +5
New capabilities in foundation models are owed in large part to massive, widely-sourced, and under-documented training data collections. Existing practices in data collection have…
Leveraging Large Language Models for Learning Complex Legal Concepts through Storytelling
Hang Jiang, Xiajie Zhang, Robert Mahari +8
Making legal knowledge accessible to non-experts is crucial for enhancing general legal literacy and encouraging civic participation in democracy. However, legal documents are ofte…
Verifiable evaluations of machine learning models using zkSNARKs
Tobin South, Alexander Camuto, Shrey Jain +5
In a world of increasing closed-source commercial machine learning models, model evaluations from developers must be taken at face value. These benchmark results-whether over task…
The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI
Shayne Longpre, Robert Mahari, Anthony Chen +14
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. To reme…
zkTax: A pragmatic way to support zero-knowledge tax disclosures
Alex Berke, Tobin South, Robert Mahari +2
Tax returns contain key financial information of interest to third parties: public officials are asked to share financial data for transparency, companies seek to assess the financ…
LePaRD: A Large-Scale Dataset of Judges Citing Precedents
Robert Mahari, Dominik Stammbach, Elliott Ash +1
We present the Legal Passage Retrieval Dataset LePaRD. LePaRD is a massive collection of U.S. federal judicial citations to precedent in context. The dataset aims to facilitate wor…
The Law and NLP: Bridging Disciplinary Disconnects
Robert Mahari, Dominik Stammbach, Elliott Ash +1
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). At the…
Art and the science of generative AI: A deeper dive
Ziv Epstein, Aaron Hertzmann, Laura Herman +11
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. The…
Co-creation and ownership for AI radio
Skylar Gordon, Robert Mahari, Manaswi Mishra +1
Recent breakthroughs in AI-generated music open the door for new forms for co-creation and co-creativity. We present Artificialfm, a proof-of-concept casual creator that blend…
AutoLAW: Augmented Legal Reasoning through Legal Precedent Prediction
Robert Zev Mahari
This paper demonstrate how NLP can be used to address an unmet need of the legal community and increase access to justice. The paper introduces Legal Precedent Prediction (LPP), th…