Simplifying the Modeling of Arbitrary Conditionals in Natural Language

In three linesAC-GPT modifies causal Transformers to evaluate and sample from arbitrary conditionals (past, future, mixed contexts) in a single forward pass. The method preserves left-to-right ordering and next-token prediction objective, enabling fine-tuning of existing LLMs without degrading standard performance.

Summary generated by Claude — human-verified