Papers with Pareto optimization
Towards Higher Pareto Frontier in Multilingual Machine Translation (2023.acl-long)
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| Challenge: | Existing Pareto optimization approaches are limited by the long-tailed distribution of multilingual corpora. |
| Approach: | They propose a Pareto mutual distillation framework that pushes the Paret frontier outwards rather than making trade-offs. |
| Outcome: | The proposed framework pushes the Pareto frontier outwards rather than making trade-offs, the authors show. |
Towards Pareto-Efficient RLHF: Paying Attention to a Few High-Reward Samples with Reward Dropout (2024.findings-emnlp)
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| Challenge: | RLHF is a bi-objective problem that has the nature of a Pareto optimization . reward dropout is generalizable and most effective with non-pretrained target models . |
| Approach: | They propose a method that guarantees a Pareto improvement by leveraging reinforcement learning to fine-tune language models. |
| Outcome: | The proposed method guarantees a Pareto improvement on two benchmark datasets . it is generalizable and most effective with non-pretrained target models, saving the effort of pretraining. |
Pareto Optimal Learning for Estimating Large Language Model Errors (2024.acl-long)
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| Challenge: | Existing approaches for improving the correctness of LLMs include prompt engineering, retrieval methods, and a generative model. |
| Approach: | They propose a method that generates a risk score to estimate the probability of error in an LLM by integrating multiple sources of information. |
| Outcome: | The proposed method is well correlated with the true LLM error rate, thus facilitating error correction. |