Papers by Yuebin Xu
EcoTune: Token-Efficient Multi-Fidelity Hyperparameter Optimization for Large Language Model Inference (2025.emnlp-main)
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| Challenge: | Multi-fidelity optimization improves inference performance with low-fidelity evaluations, but its static scheduling strategies ignore token consumption, leading to high costs. |
| Approach: | They propose a token-efficient multi-fidelity optimization method that optimizes for inference hyperparameters . their method reduces token consumption by over 80% while maintaining or surpassing performance . |
| Outcome: | The proposed method improves over the HELM leaderboard by 7.1%, 24.3%, 21.9%, and 4.6% while maintaining or surpassing performance. |