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Unlocking Anticipatory Text Generation: A Constrained Approach for Large Language Models Decoding (2024.emnlp-main)

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Challenge: Large language models have shown a powerful ability for text generation, but undesired behaviors such as toxicity and hallucinations can manifest.
Approach: They propose to formalize text generation as a future-constrained generation problem to minimize undesirable behaviors and enforce faithfulness to instructions.
Outcome: The proposed approach is effective across three tasks, including keyword-constrained generation, toxicity reduction, and factual correctness in question-answering.

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