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Found 6 papers, 5 papers with code
What's in a Name? Auditing Large Language Models for Race and Gender Bias
We employ an audit design to investigate biases in state-of-the-art large language models, including GPT-4.
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
The advent of large language models (LLMs) and their adoption by the legal community has given rise to the question: what types of legal reasoning can LLMs perform?
Designing Equitable Algorithms
Predictive algorithms are now used to help distribute a large share of our society's resources and sanctions, such as healthcare, loans, criminal detentions, and tax audits.
LegalBench: Prototyping a Collaborative Benchmark for Legal Reasoning
Finally-inspired by the Open Science movement-we make a call for the legal and computer science communities to join our efforts by contributing new tasks.
Forecasting Algorithms for Causal Inference with Panel Data
Conducting causal inference with panel data is a core challenge in social science research.
On the Opportunities and Risks of Foundation Models
AI is undergoing a paradigm shift with the rise of models (e. g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.
