3 papers
cs.LG2026
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability
Yijin Zhou, Yutang Ge, Wenyuan Xie +3
Transformers excel in natural language processing and computer vision tasks. However, they still face challenges in generalizing to Out-of-Distribution (OOD) datasets, i.e. data wh…
cs.CL2025
DocMEdit: Towards Document-Level Model Editing
Li Zeng, Zeming Liu, Chong Feng +2
Model editing aims to correct errors and outdated knowledge in the Large language models (LLMs) with minimal cost. Prior research has proposed a variety of datasets to assess the e…
cs.CL2024
FAME: Towards Factual Multi-Task Model Editing
Li Zeng, Yingyu Shan, Zeming Liu +2
Large language models (LLMs) embed extensive knowledge and utilize it to perform exceptionally well across various tasks. Nevertheless, outdated knowledge or factual errors within…