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cs.AI2026
Recalling Too Well: Sycophancy Evaluation and Mitigation in Memory-Augmented Models
Shelly Bensal, Axel Magnuson, Aparna Balagopalan +1
Persistent memory systems promise to make LLMs more helpful by storing user beliefs over time. We show they also make models less correct by amplifying sycophancy, wherein models p…
cs.AI2026
The Price of Agreement: Measuring LLM Sycophancy in Agentic Financial Applications
Zhenyu Zhao, Aparna Balagopalan, Adi Agrawal +3
Given the increased use of LLMs in financial systems today, it becomes important to evaluate the safety and robustness of such systems. One failure mode that LLMs frequently displa…