Word Class Representations Spontaneously Emerge from Successor Representations Trained on Natural Language 事件

Word Class Representations Spontaneously Emerge from Successor Representations Trained on Natural Language arXiv:2605.24585v1 Announce Type: new Abstract: Language models are typically trained to predict the next token in a sequence. Here, we explore an alternative predictive principle from reinforcement learning: Successor Representations (SRs), which model the expected discounted distribution of future states rather than the immediate next state. We transfer this framework to natural language