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Apparent "centrist" alignment in smaller language models often masks degenerate response collapse rather than genuine neutrality, exposing deep measurement artifacts in standard political benchmark evaluations.
Injecting domain-specific knowledge into small tabular models can lead to substantial performance gains in niche applications, highlighting the importance of tailored fine-tuning strategies.
Guaranteeing connectivity in text embedding graphs with a simple incremental construction unlocks more robust and parameter-insensitive spectral clustering.
