Constrained Text Generation

Constrained text generation focuses on creating text that adheres to specific rules or requirements, a challenge for even advanced language models. Current research explores diverse approaches, including constraint programming, perturbed masking techniques, and heuristic search algorithms like A*-esque decoding, often integrated with large language models or adapted for unsupervised settings. This field is crucial for improving the controllability and reliability of language models, with applications ranging from standardized test creation to more nuanced text summarization and machine translation. The development of robust benchmarks and evaluation metrics is also a significant area of ongoing work.