Successor Features for Efficient Multi-Subject Controlled Text Generation
Meng Cao, Mehdi Fatemi, Jackie C. K. Cheung, Samira Shabanian
2024Year
2Citations
2Top-tier citations
Abstract
While large language models (LLMs) have achieved impressive performance in generating fluent and realistic text, controlling the generated text so that it exhibits properties such as safety, factuality, and non-toxicity remains challenging.
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Install the CLIlune papers fulltext eeff1930-28ba-4f29-9d12-5132aaf7babaCited by top-tier papers2
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- QUARK: Controllable Text Generation with Reinforced UnlearningXiming Lu, Sean Welleck, Jack Hessel, Liwei Jiang et al.NeurIPS 2022 · 290 citations
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