2 citations · 2 across the 4 of their papers we have counts for
4 papers
FlowPipe: LLM-Enhanced Conditional Generative Flow Networks for Data Preparation Pipeline Construction
Kunyu Ni, Lei Cao, Jie He +4
Data preparation pipelines improve data quality in machine learning by transforming raw tables into learning-ready data through sequential cleaning and feature transformation opera…
Similarity-Based Domain Adaptation with LLMs
Jie He, Wendi Zhou, Xiang Lorraine Li +1
Unsupervised domain adaptation leverages abundant labeled data from various source domains to generalize onto unlabeled target data. Prior research has primarily focused on learnin…
Evaluating and Safeguarding the Adversarial Robustness of Retrieval-Based In-Context Learning
Simon Yu, Jie He, Pasquale Minervini +1
With the emergence of large language models, such as LLaMA and OpenAI GPT-3, In-Context Learning (ICL) gained significant attention due to its effectiveness and efficiency. However…
Instances and Labels: Hierarchy-aware Joint Supervised Contrastive Learning for Hierarchical Multi-Label Text Classification
Simon Yu, Jie He, Víctor Gutiérrez-Basulto +1
Hierarchical multi-label text classification (HMTC) aims at utilizing a label hierarchy in multi-label classification. Recent approaches to HMTC deal with the problem of imposing a…