Generic Triple-Latent Compression with Gated Associative Retrieval

This research introduces generic triple-latent sequence models, which use a running token state and compressed pair-memory to capture higher-order token interactions. These models show improvement over a Transformer baseline on language-model benchmarks, though a retrieval extension enhances recall but is slower.