Abstract. We incorporate two ideas in ADC. The first one, delaying variable elimination, permits performing joins in different buckets, not forcing to eliminate ...
Improving the applicability of adaptive consistency: preliminary results.
Bibliographic details on Improving the Applicability of Adaptive Consistency: Preliminary Results.
Improving the Applicability of Adaptive Consistency: Preliminary Results ... A New Algorithm for Maintaining Arc Consistency After Constraint Retraction. Pavel ...
A popular approach for improving the correct- ness of output from large language models. (LLMs) is Self-Consistency – poll the LLM.
Recent studies have shown that deep networks can achieve promising results for image denoising. However, how to simultaneously incorporate the valuable ...
TL;DR: We propose Adaptive Consistency, a method that significantly reduces the sampling cost of LLMs, with negligible drop in accuracy for coding and reasoning ...
Missing: Preliminary | Show results with:Preliminary
May 19, 2023 · Our experiments over 13 datasets and two LLMs demonstrate that Adaptive-Consistency reduces sample budget by up to 6.0 times with an average ...
Missing: Applicability | Show results with:Applicability
We introduce adaptive consistency regularization to improve semi-supervised transfer learning by exploit- ing the characteristics of both semi-supervised learn ...
Missing: Applicability | Show results with:Applicability
Aug 8, 2021 · We introduce adaptive consistency regularization to improve semi-supervised transfer learning by exploit- ing the characteristics of both semi- ...
Missing: Applicability | Show results with:Applicability