Papers with quantile regression
Order of Magnitude Speedups for LLM Membership Inference (2024.emnlp-main)
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| Challenge: | Large Language Models (LLMs) are complex and require fine-tuning on proprietary datasets to improve performance and relevance. |
| Approach: | They propose a low-cost membership inference attack that leverages an ensemble of small quantile regression models to determine if a document belongs to the model’s training set. |
| Outcome: | The proposed approach achieves comparable or improved accuracy on fine-tuned LLMs of varying families and across multiple datasets. |
Text-to-Distribution Prediction with Quantile Tokens and Neighbor Context (2026.acl-long)
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Yilun Zhu, Yuan Zhuang, Nikhita Vedula, Dushyanta Dhyani, Shaoyuan Xu, Mohsen Bayati, Bryan Wang, Shervin Malmasi
| Challenge: | Existing methods for text regression lack local grounding and rely on shared representations. |
| Approach: | They propose a distributional regression model with quantile tokens that insert dedicated quantiles into the input sequence. |
| Outcome: | The proposed method outperforms baseline models on the inside Airbnb and StackSample datasets. |