Papers with supervised maximum likelihood estimation approach
Learning to Rank Generation with Pairwise Partial Rewards (2023.emnlp-main)
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| Challenge: | Existing methods for conditional text generation suffer from large action space and delayed reward, as the reward can be computed only after an entire sequence is generated. |
| Approach: | They propose a method that provides partial rewards for intermediate actions taken on partial sequences to prioritize actions that lead to the generation of more desirable sequences. |
| Outcome: | The proposed method overcomes the limitations of the prevalent supervised maximum likelihood estimation approach. |