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MemoReason: Evaluating the Effect of Parametric Memory on Contextual Reasoning in LLMs
Large Language Models (LLMs) perform well on reasoning benchmarks, but it remains unclear whether this reflects genuine contextual reasoning or reliance on facts memorized in their parameters. We investigate this by distinguishing two possibilities: a broad \textit{memorization bias}, where familiar content improves re...
Toward Collective-Centric Evaluation of Preference Inference for Participatory Democracy
A novel comprehensive and collective-centric evaluation benchmark for the task of Preference Inference, which aims to support the development of AI systems that scale deliberation without compromising the integrity of its democratic outcomes.