RAG, Fine-Tuning & ContextAli Modarressi et al. (LMU Munich, MCML, Adobe Research)LMU Munich

Modarressi et al. present NoLiMa

Presented NoLiMa — in a long-context evaluation with literal overlap removed, many models dropped below 50% of their short-context performance at 32K

Why it matters

Showed that needle-in-a-haystack scores overstate long-context ability

Source — Primary sources first; secondary reports are labelled “Press”

Paperarxiv.orghttps://arxiv.org/abs/2502.05167

Added in Week 35, 2026 · See that week

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