The recent publications in the field of coding theory and related areas indicate a strong trend towards the exploration of new coding constructions, decoding algorithms, and the enhancement of error correction capabilities. A significant portion of the research is dedicated to the development of codes with specific properties, such as quasi-optimality, self-duality, and local recoverability, which are crucial for applications in quantum computing, distributed storage, and network coding. Additionally, there is a notable focus on improving decoding schemes, including retry decoding and perturbation-enhanced decoding, to achieve lower error rates and higher efficiency. The exploration of lattice codes and their decoding strategies, as well as the study of differential properties in information channels, further highlight the field's move towards more robust and efficient communication systems. The research also delves into the theoretical aspects of coding, such as the classification of self-dual codes and the analysis of higher-order Delsarte dual linear programs, aiming to bridge the gap between theoretical bounds and practical code constructions.

Noteworthy Papers

• Quasi-optimal cyclic orbit codes: Establishes a connection between codewords of cyclic orbit codes and linear sets on the projective line, leading to new bounds and a general existence theorem for quasi-optimal codes.
• Sequence Reconstruction for Single-Deletion Single-Substitution Channel: Provides a tight upper bound on the intersection size of error balls for sequences with a minimum Hamming distance, advancing sequence reconstruction techniques.
• Channel Coding based on Skew Polynomials and Multivariate Polynomials: Introduces new constructions and decoding approaches for error-correcting codes, including dual-containing codes for quantum error correction and locally recoverable codes for distributed storage.
• Finite Dimensional Lattice Codes with Self Error-Detection and Retry Decoding: Presents a novel retry decoding scheme for lattice-based transmissions, significantly reducing word error rates without the need for re-transmissions.
• Toward Universal Decoding of Binary Linear Block Codes via Enhanced Polar Transformations: Introduces a universal soft decoding algorithm that transforms any binary linear block code into a polar-like code, achieving competitive performance with lower complexity.