activity
20232026
most citedThe Challenge of Using LLMs to Simulate Human Behavior: A Causal Inference Perspective

40 citations · 41 across the 6 of their papers we have counts for

collaborators
Showing 2026Show all

5 papers · 1 filter

cs.CY2026

AI-Moderated Interviews for Market Research and Digital Twins Calibration

Yuting Deng, Jingxuan Liu, Olivier Toubia +1

AI-moderated interviews are emerging as a scalable market-research method for generating consumer insights and building consumer "digital twins." Yet it remains unclear whether the…

cs.CY2026

ExploraTwin, a Non-Profit Research Platform for Digital Twin Simulations

Naveen Venkat, Yuchen Qiu, Tianyi Peng +2

Digital twin simulations show promise, but current empirical evidence suggests that the approach should be tested before being deployed in any particular context. To lower the fric…

cs.HC2026

Innovating with Generative AI: A Human Bottleneck Framework

Julian De Freitas, Ayelet Israeli, Gideon Nave +2

We propose a human bottleneck perspective for understanding how generative AI transforms the innovation process. The central premise is that many constraints traditionally plaguing…

cs.HC2026

Synthetic Contact with AI Reduces Cross-Partisan Animosity

Benjamin Lira, Noah Castelo, Stefano Puntoni +1

Americans' warmth toward members of the opposing political party has fallen sharply over the past three decades -- yet meaningful cross-partisan contact remains scarce, in part bec…

cs.CY2026

Examining and Addressing Barriers to Diversity in LLM-Generated Ideas

Yuting Deng, Melanie Brucks, Olivier Toubia

Ideas generated by independent samples of humans tend to be more diverse than ideas generated from independent LLM samples, raising concerns that widespread reliance on LLMs could…