1 citations · 2 across the 4 of their papers we have counts for
5 papers
Post-training makes large language models less human-like
Marcel Binz, Elif Akata, Abdullah Almaatouq +76
Large language models (LLMs) are increasingly used as surrogates for human participants, but it remains unclear which models best capture human behavior and why. To address this, w…
Integrative Experiments Identify How Punishment Impacts Welfare in Public Goods Games
Mohammed Alsobay, David G. Rand, Duncan J. Watts +1
Punishment as a mechanism for promoting cooperation has been studied extensively for more than two decades, but its effectiveness remains a matter of dispute. Here, we examine how…
Bringing Everyone to the Table: An Experimental Study of LLM-Facilitated Group Decision Making
Mohammed Alsobay, David M. Rothschild, Jake M. Hofman +1
Group decision-making often suffers from uneven information sharing, hindering decision quality. While large language models (LLMs) have been widely studied as aids for individuals…
Prompt Adaptation as a Dynamic Complement in Generative AI Systems
Eaman Jahani, Benjamin S. Manning, Joe Zhang +5
As generative AI systems rapidly improve, a key question emerges: how do users adapt to these changes, and when does such adaptation matter for realizing performance gains? Drawing…
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers
Hussein Mozannar, Valerie Chen, Mohammed Alsobay +7
Evaluation of large language models for code has primarily relied on static benchmarks, including HumanEval (Chen et al., 2021), or more recently using human preferences of LLM res…