Researchers propose a finite-state machine framework for text generation, offering precise control and improved performance.
Author: Brandon T. Willard, Normal Computing; R´emi Louf, Normal Computing. Table of Links Abstract and Intro LLM Sampling and Guided Generation Iterative FSM Processing and Indexing Extensions to Iterative Parsing Discussion, References and Acknowledgments Abstract In this article we show how the problem of neural text generation can be constructively reformulated in terms of transitions between the states of a finite-state machine.
Table of Links Abstract and Intro LLM Sampling and Guided Generation Iterative FSM Processing and Indexing Extensions to Iterative Parsing Discussion, References and Acknowledgments Abstract and Intro Abstract and Intro LLM Sampling and Guided Generation LLM Sampling and Guided Generation Iterative FSM Processing and Indexing Iterative FSM Processing and Indexing Extensions to Iterative Parsing Extensions to Iterative Parsing Discussion, References and Acknowledgments Discussion, References and...
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