UAB uses ANLL from a single generation as a difficulty signal and a marginal-greedy concave optimization to allocate remaining sampling budget, yielding up to 3% higher average accuracy on reasoning benchmarks.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Uncertainty-Aware Budget Allocation for Adaptive Test-Time Reasoning
UAB uses ANLL from a single generation as a difficulty signal and a marginal-greedy concave optimization to allocate remaining sampling budget, yielding up to 3% higher average accuracy on reasoning benchmarks.