Papers by Velizar Shulev
Continual Reinforcement Learning for Controlled Text Generation (2024.lrec-main)
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| Challenge: | Controlled Text Generation (CTG) aims to steer text generation towards texts possessing a desired attribute. |
| Approach: | They propose an algorithm that steers the generation of continuations of a given context . they propose a Continual Learning problem to learn at every step to steer next-word generation . |
| Outcome: | The proposed algorithm is based on a plug-and-play language model and exhibits promising results. |