Memory vs. Context? Influential Factors of Factual Recall in Language Models
We reproduce and stress-test the work of Yu et al. (2023), who characterize how language models (LMs) arbitrate between memorized knowledge and contradictory in-context statements. We replicate their world-capitals experiments on 31 models spanning Pythia, GPT-2, Qwen3, and Ministral families, including base and post-trained variants, and extend evaluations to five additional knowledge relation types from the ParaConflict dataset. We empirically confirm most of their original findings: larger models and higher-frequency entities tend to favor memorized answers, with substantial family-level variance. However, several conclusions do not generalize cleanly: entity-frequency effects disappea...
| Authors | Guilhem Fouilhé, Nicholas Asher, Philippe Muller |
|---|---|
| Primary category | cs.CL |
| Published | 21 September 2026 |
| Last updated at source | 21 September 2026 |
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