5 papers
Personalized Clustering via Targeted Representation Learning
Xiwen Geng, Suyun Zhao, Yixin Yu +5
Clustering traditionally aims to reveal a natural grouping structure within unlabeled data. However, this structure may not always align with users' preferences. In this paper, we…
Unsupervised Learning for Class Distribution Mismatch
Pan Du, Wangbo Zhao, Xinai Lu +8
Class distribution mismatch (CDM) refers to the discrepancy between class distributions in training data and target tasks. Previous methods address this by designing classifiers to…
E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model
Xinmei Huang, Haoyang Li, Jing Zhang +7
Database knob tuning is a significant challenge for database administrators, as it involves tuning a large number of configuration knobs with continuous or discrete values to achie…
Diversifying Question Generation over Knowledge Base via External Natural Questions
Shasha Guo, Jing Zhang, Xirui Ke +2
Previous methods on knowledge base question generation (KBQG) primarily focus on enhancing the quality of a single generated question. Recognizing the remarkable paraphrasing abili…
Streamlining Redundant Layers to Compress Large Language Models
Xiaodong Chen, Yuxuan Hu, Jing Zhang +3
This paper introduces LLM-Streamline, a pioneer work on layer pruning for large language models (LLMs). It is based on the observation that different layers have varying impacts on…