Abstract: Knowledge Graph Embedding (KGE) aims to learn dense embeddings as the representations for entities and relations in KGs. Indeed, the entities in existing KGs suffer from the data imbalance ...

Abstract: Knowledge Graphs (KGs), with their intricate hierarchies and semantic ... In particular, SimE is competitive with state-of-the-art KG embedding models and is able to achieve high values of ...

We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding ...