Show, Don't Tell: Aligning Language Models with Demonstrated Feedback

1 code implementation • 2 Jun 2024 • Omar Shaikh, Michelle Lam, Joey Hejna, Yijia Shao, Michael Bernstein, Diyi Yang

Across our benchmarks and user study, we find that win-rates for DITTO outperform few-shot prompting, supervised fine-tuning, and other self-play methods by an average of 19% points.

Imitation Learning Language Modelling

Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems

1 code implementation • 10 Mar 2021 • Chloé Bakalar, Renata Barreto, Stevie Bergman, Miranda Bogen, Bobbie Chern, Sam Corbett-Davies, Melissa Hall, Isabel Kloumann, Michelle Lam, Joaquin Quiñonero Candela, Manish Raghavan, Joshua Simons, Jonathan Tannen, Edmund Tong, Kate Vredenburgh, Jiejing Zhao

We discuss how we disentangle normative questions of product and policy design (like, "how should the system trade off between different stakeholders' interests and needs?")

BIG-bench Machine Learning Fairness

Power Networks: A Novel Neural Architecture to Predict Power Relations

no code implementations • COLING 2018 • Michelle Lam, Catherina Xu, Angela Kong, Vinodkumar Prabhakaran

Can language analysis reveal the underlying social power relations that exist between participants of an interaction?

Amanuensis: The Programmer's Apprentice

no code implementations • 29 Jun 2018 • Thomas Dean, Maurice Chiang, Marcus Gomez, Nate Gruver, Yousef Hindy, Michelle Lam, Peter Lu, Sophia Sanchez, Rohun Saxena, Michael Smith, Lucy Wang, Catherine Wong

This document provides an overview of the material covered in a course taught at Stanford in the spring quarter of 2018.