One such approach to increase the efficiency of coupled-cluster based methods is through rank reduction. Parrish et al. have used orthogonal projectors to transform CCSD amplitudes into smaller-ranked tensors. Lesiuk has successfully applied such an approach to CCSD(T). Rank reduction can also be used in conjunction with tensor hypercontraction (THC) methods. Through the use of the CANDECOMP/PARAFAC (CP) decomposition of the orthogonal projectors, Hohenstein et al. have applied THC to CCSD amplitudes, while Jiang et al. recently applied this approach to the (T) correction. Another approach to this problem is to reformulate coupled-cluster theory through local correlation methods, especially methods that use pair natural orbitals (PNOs). State-of-the-art PNO-based coupled-cluster methods include the in the domain-based local pair natural orbital [DLPNO-CCSD(T)] method in ORCA; the pair natural orbital local [PNO-LCCSD(T)] method in Molpro; and the local natural orbital [LNO-CCSD(T)] method in MRCC. ORCA's DLPNO-CCSD(T) algorithm has been executed on system sizes containing more than 1000 atoms, far greater than the 30 atoms using canonical CCSD(T) methods.