3 papers
cs.CL2026
Task-Dependent Evaluation of LLM Output Homogenization: A Taxonomy-Guided Framework
Shomik Jain, Jack Lanchantin, Maximilian Nickel +4
Large language models often generate homogeneous outputs, but whether this is problematic depends on the specific task. For objective math tasks, responses may vary in terms of pro…
cs.HC2026
Interaction Context Often Increases Sycophancy in LLMs
Shomik Jain, Charlotte Park, Matt Viana +2
We investigate how the presence and type of interaction context shapes sycophancy in LLMs. While real-world interactions allow models to mirror a user's values, preferences, and se…
cs.CY2025
Allocation Multiplicity: Evaluating the Promises of the Rashomon Set
Shomik Jain, Margaret Wang, Kathleen Creel +1
The Rashomon set of equally-good models promises less discriminatory algorithms, reduced outcome homogenization, and fairer decisions through model ensembles or reconciliation. How…