collaborators

5 papers

cs.CL2026

Sycophantic Praise: Evaluating Excessive Praise in Language Models

Daniel Vennemeyer, Phan Anh Duong, Meryl Ye +2

Sycophancy in language models is typically studied as excessive agreement or validation, while explicit praise and flattery have received comparatively little attention. We argue t…

cs.AI2026

What Counts as AI Sycophancy? A Taxonomy and Expert Survey of a Fragmented Construct

Meryl Ye, Lujain Ibrahim, Jessica Y. Bo +5

AI sycophancy has become a prominent concern in large language model (LLM) research. Yet the term lacks a consistent definition and has been applied to behaviors ranging from agree…

cs.CL2026

Sycophancy Is Not One Thing: Causal Separation of Sycophantic Behaviors in LLMs

Daniel Vennemeyer, Phan Anh Duong, Tiffany Zhan +1

Large language models (LLMs) often exhibit sycophantic behaviors -- such as excessive agreement with or flattery of the user -- but it is unclear whether these behaviors arise from…

cs.CL2026

Objective Matters: Fine-Tuning Objectives Shape Safety, Robustness, and Persona Drift

Daniel Vennemeyer, Punya Syon Pandey, Phan Anh Duong +2

Fine-tuning LLMs on benign data can still degrade alignment and adversarial robustness, yet direct analysis of the role of fine-tuning objectives in shaping these safety outcomes r…

cs.CL2025

GuessingGame: Measuring the Informativeness of Open-Ended Questions in Large Language Models

Dylan Hutson, Daniel Vennemeyer, Aneesh Deshmukh +2

We introduce GuessingGame, a protocol for evaluating large language models (LLMs) as strategic question-askers in open-ended, open-domain settings. A Guesser LLM identifies a hidde…