Author

Ameya Godbole

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#natural language process... Mar 2026

Evaluating LLM-Simulated Conversations in Modeling Inconsistent and Uncollaborative Behaviors in Human Social Interaction

This paper reconsiders the evaluation of simulated conversations by explicitly recognizing that human conversations inherently involve inconsistent and uncollaborative behaviors, such as misunderstandings and interruptions, and argues that LLM-simulated conversations should reproduce them at frequencies comparable to t...

Ryo Kamoi, Ameya Godbole, Bing-Lin Zhou et al. · arXiv.org · 0 citations

#machine learning Preprint May 2026

Correcting test set contamination by spiking the training data

The core proposal is to spike the training data by intentionally contaminating some test examples at known rates, which can then be used to calibrate predictors of model memorization which enable principled statistical correction of inflated test scores.

J. Wei, Jerry Li, Ameya Godbole et al. · 0 citations