85 citations · 94 across the 7 of their papers we have counts for
6 papers · 1 filter
SPICA: Retrieving Scenarios for Pluralistic In-Context Alignment
Quan Ze Chen, K. J. Kevin Feng, Chan Young Park +1
When different groups' values differ, one approach to model alignment is to steer models at inference time towards each group's preferences. However, techniques like in-context lea…
Cocoa: Co-Planning and Co-Execution with AI Agents
K. J. Kevin Feng, Kevin Pu, Matt Latzke +6
As AI agents take on increasingly long-running tasks involving sophisticated planning and execution, there is a corresponding need for novel interaction designs that enable deeper…
Chain of Alignment: Integrating Public Will with Expert Intelligence for Language Model Alignment
Andrew Konya, Aviv Ovadya, Kevin Feng +4
We introduce a method to measure the alignment between public will and language model (LM) behavior that can be applied to fine-tuning, online oversight, and pre-release safety che…
Policy Prototyping for LLMs: Pluralistic Alignment via Interactive and Collaborative Policymaking
K. J. Kevin Feng, Inyoung Cheong, Quan Ze Chen +1
Emerging efforts in AI alignment seek to broaden participation in shaping model behavior by eliciting and integrating collective input into a policy for model finetuning. While plu…
(A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice
Inyoung Cheong, King Xia, K. J. Kevin Feng +2
Large language models (LLMs) are increasingly capable of providing users with advice in a wide range of professional domains, including legal advice. However, relying on LLMs for l…
Canvil: Designerly Adaptation for LLM-Powered User Experiences
K. J. Kevin Feng, Q. Vera Liao, Ziang Xiao +3
Advancements in large language models (LLMs) are sparking a proliferation of LLM-powered user experiences (UX). In product teams, designers often craft UX to meet user needs, but i…