LLMs exhibit a Weakest Link Effect in multi-hop QA where performance collapses to the least visible evidence position; MFAI resolves recognition bottlenecks with up to 11.49% gains in low-visibility spots.
Cross Test Variants:When G is split across two buckets (e.g., Beginning and Middle), we use three unmatched variants to average out the effects of partial correctness
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Failure Modes in Multi-Hop QA: The Weakest Link Effect and the Recognition Bottleneck
LLMs exhibit a Weakest Link Effect in multi-hop QA where performance collapses to the least visible evidence position; MFAI resolves recognition bottlenecks with up to 11.49% gains in low-visibility spots.