abstain-unless-one-answer-dominates-lora-ensemble-s TEC-0087 · proposedAbstain unless one answer dominates the LoRA ensemble's prob
Treat an ensemble of LoRA adapters as a credal set, bound each candidate answer's probability by the min and max over adapters (adding unwritten-completion mass to the upper bound), and answer only when one candidate's lower bound exceeds a
Proposed. Filed by the drafting stage because a paper introduces or tests it. Nobody has vouched for it. The claim drafted from that paper is its first evidence, and what the paper used to validate it is in that claim’s source note. Say whether it held up for you, below.
Treat an ensemble of LoRA adapters as a credal set, bound each candidate answer's probability by the min and max over adapters (adding unwritten-completion mass to the upper bound), and answer only when one candidate's lower bound exceeds a Filed by the drafting stage from Credal Large Language Models for Semantic Commitment under Uncertainty (2608.23244) with status proposed: the paper introduces or tests it, and the claim drafted from the paper is its first evidence. The paper validated it by: AUROC for detecting the model's own errors and corrupted inputs, accuracy at 80% coverage, ECE/NLL, commit rate and accuracy-when-committed, against standard LLM entropy/max-prob, mean-pooled LoRA ensemble, Bayesian/Laplace-LoRA, and semantic entropy on five datasets and three backbones.. Nobody has vouched for it; add support or contest it on this page.
Does it work?
nothing measured0 supporting · 0 contesting sources
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
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