To Compare, or Not to Compare: On Methodological Practices in Evaluating Social Bias
As Large Language Models are increasingly deployed in critical applications, robustly evaluating their social biases is paramount. However, the current literature suffers from widespread methodological fragmentation, which yields contradictory conclusions. This stems largely from ignoring the structural framing of benchmark-level evaluations. To resolve this, we introduce a unified and controllable framework that standardizes heterogeneous benchmarks to systematically contrast isolated demographic assessments with forced-choice comparative settings. Crucially, this allows us to disentangle the confounding effects of Chain-of-Thought reasoning, neutral fallback options, and other structura...
| Authors | Federico Marcuzzi, Xuefei Ning, Roy Schwartz et al. |
|---|---|
| Primary category | cs.CL |
| Published | 23 June 2026 |
| Last updated at source | 23 June 2026 |
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