  Successive cancellation list (SCL) decoding enables polar codes and their
generalizations to deliver satisfactory performance in finite-length scenarios
but it comes with high latency and complexity. To reduce latency, a partitioned
SCL (PSCL) decoding algorithm, implemented over a PSCL decoding tree, can be
utilized. In this work, we aim to lower down the complexity of the PSCL
decoding, resulting in an efficient decoding algorithm with low latency and
complexity for polar-like codes. To achieve this, we define two metrics at each
level of the PSCL decoding tree. One is for evaluating the reliability of a
path and the other is for estimating the probability of the correct path being
included in a list of paths. Then, we propose a double-threshold strategy in
the PSCL decoding process where unreliable valid paths are pruned based on the
first metric, and then a list of surviving paths is selected based on the
second metric. Simulation results demonstrate that when polar/CRC-polar/PAC
codes are decoded using the proposed low-complexity PSCL decoder, both the
sorting complexity and the computational complexity are reduced and
significantly decrease as the signal-to-noise ratio (SNR) increases.
