TailNLG: A Multilingual Benchmark Addressing Verbalization of Long-Tail Entities

ArXi:2603.27768v1 Announce Type: new The automatic verbalization of structured knowledge is a key task for making knowledge graphs accessible to non-expert users and ing retrieval-augmented generation systems. Although recent advances in Data-to-Text generation have improved multilingual coverage, little attention has been paid to potential biases in the verbalization of rare entities, frequently known as long-tail entities. In this work, we present the first systematic study of long-tail entities in Data-to-Text generation. We.