The field of error-correcting codes is witnessing significant advancements, with a focus on improving the performance and efficiency of various coding techniques. Researchers are exploring new approaches to enhance the list-recoverability of random linear codes, develop efficient decoding algorithms for constacyclic codes, and improve the rate-matching capabilities of deep polar codes. Additionally, there is a growing interest in understanding the limitations of computing quadratic functions on encoded data and developing low-complexity decoding schemes for generalized LDPC codes. Notably, recent studies have demonstrated the potential of generalized Reed-Solomon codes in achieving symmetric capacity and the effectiveness of concatenated coding structures in reducing decoding complexity. Noteworthy papers include: List-Recovery of Random Linear Codes over Small Fields, which presents a significant improvement over the Zyablov-Pinsker bound for list-recovery from erasures and errors. Decoding Algorithms for Two-dimensional Constacyclic Codes over Fq, which proposes efficient decoding algorithms exploiting the spectral domain properties of 2-D constacyclic codes. Rate-Matching Deep Polar Codes via Polar Coded Extension, which introduces a novel rate-matching technique for deep polar codes using code extension. Limitations to Computing Quadratic Functions on Reed-Solomon Encoded Data, which establishes a lower bound on the information downloaded for evaluating quadratic functions on encoded data. Generalized LDPC codes with low-complexity decoding and fast convergence, which proposes efficient decoding algorithms for generalized LDPC codes. Coding Theorem for Generalized Reed-Solomon Codes, which proves that generalized Reed-Solomon codes can achieve symmetric capacity. Low-Complexity Decoding for Low-Rate Block Codes of Short Length Based on Concatenated Coding Structure, which presents an improved decoding scheme for low-rate block codes using concatenated coding.