Critic-Guided Decoding for Controlled Text Generation

Minbeom Kim, Hwanhee Lee, Kang Min Yoo, Joonsuk Park, Hwaran Lee, Kyomin Jung


Abstract
Steering language generation towards objectives or away from undesired content has been a long-standing goal in utilizing language models (LM). Recent work has demonstrated reinforcement learning and weighted decoding as effective approaches to achieve a higher level of language control and quality with pros and cons. In this work, we propose a novel critic decoding method for controlled language generation (CriticControl) that combines the strengths of reinforcement learning and weighted decoding. Specifically, we adopt the actor-critic framework and train an LM-steering critic from reward models. Similar to weighted decoding, our method freezes the language model and manipulates the output token distribution using a critic to improve training efficiency and stability. Evaluation of our method on three controlled generation tasks, topic control, sentiment control, and detoxification, shows that our approach generates more coherent and well-controlled texts than previous methods. In addition, CriticControl demonstrates superior generalization ability in zero-shot settings. Human evaluation studies also corroborate our findings.
Anthology ID:
2023.findings-acl.281
Volume:
Findings of the Association for Computational Linguistics: ACL 2023
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4598–4612
Language:
URL:
https://aclanthology.org/2023.findings-acl.281
DOI:
10.18653/v1/2023.findings-acl.281
Bibkey:
Cite (ACL):
Minbeom Kim, Hwanhee Lee, Kang Min Yoo, Joonsuk Park, Hwaran Lee, and Kyomin Jung. 2023. Critic-Guided Decoding for Controlled Text Generation. In Findings of the Association for Computational Linguistics: ACL 2023, pages 4598–4612, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Critic-Guided Decoding for Controlled Text Generation (Kim et al., Findings 2023)
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PDF:
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Video:
 https://preview.aclanthology.org/proper-vol2-ingestion/2023.findings-acl.281.mp4