activity
20222025
most citedConcept Induction: Analyzing Unstructured Text with High-Level Concepts Using LLooM

42 citations · 45 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Finetuning LLMs for Human Behavior Prediction in Social Science Experiments

Akaash Kolluri, Shengguang Wu, Joon Sung Park +1

Large language models (LLMs) offer a powerful opportunity to simulate the results of social science experiments. In this work, we demonstrate that finetuning LLMs directly on indiv…

cs.CL2025

Can Vision Language Models Understand Mimed Actions?

Hyundong Cho, Spencer Lin, Tejas Srinivasan +4

Nonverbal communication (NVC) plays an integral role in human language, but studying NVC in general is challenging because of its broad scope and high variance in interpretation am…

cs.HC2024★ 42 cited

Concept Induction: Analyzing Unstructured Text with High-Level Concepts Using LLooM

Michelle S. Lam, Janice Teoh, James Landay +2

Data analysts have long sought to turn unstructured text data into meaningful concepts. Though common, topic modeling and clustering focus on lower-level keywords and require signi…

cs.LG2024★ 3 cited

Clarify: Improving Model Robustness With Natural Language Corrections

Yoonho Lee, Michelle S. Lam, Helena Vasconcelos +2

The standard way to teach models is by feeding them lots of data. However, this approach often teaches models incorrect ideas because they pick up on misleading signals in the data…

stat.AP2022

Balancing Producer Fairness and Efficiency via Prior-Weighted Rating System Design

Thomas Ma, Michael S. Bernstein, Ramesh Johari +1

Online marketplaces use rating systems to promote the discovery of high-quality products. However, these systems also lead to high variance in producers' economic outcomes: a new p…