63 citations · 104 across the 4 of their papers we have counts for
4 papers
Beyond Linear Steering: Unified Multi-Attribute Control for Language Models
Narmeen Oozeer, Luke Marks, Shreyans Jain +2
Controlling multiple behavioral attributes in large language models (LLMs) at inference time is a challenging problem due to interference between attributes and the limitations of…
Designing Data: Proactive Data Collection and Iteration for Machine Learning
Aspen Hopkins, Fred Hohman, Luca Zappella +2
Lack of diversity in data collection has caused significant failures in machine learning (ML) applications. While ML developers perform post-collection interventions, these are tim…
Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task
Kenneth Li, Aspen K. Hopkins, David Bau +3
Language models show a surprising range of capabilities, but the source of their apparent competence is unclear. Do these networks just memorize a collection of surface statistics,…
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development
Aspen Hopkins, Serena Booth
Practitioners from diverse occupations and backgrounds are increasingly using machine learning (ML) methods. Nonetheless, studies on ML Practitioners typically draw populations fro…