Zhendong Mao

DACL-RAG: Data Augmentation Strategy with Curriculum Learning for Retrieval-Augmented Generation

2025 · arXiv (Cornell University)

Retrieval-Augmented Generation (RAG) is an effective method to enhance the capabilities of large language models (LLMs). Existing methods typically optimize the retriever or the generator in a RAG system by directly using the top-k retrieved …

Knowledge Graph Embedding: A Survey of Approaches and Applications

2017 · IEEE Transactions on Knowledge and Data Engineering

Knowledge graph (KG) embedding is to embed components of a KG including entities and relations into continuous vector spaces, so as to simplify the manipulation while preserving the inherent structure of the KG. It can …

Curriculum Learning for Natural Language Understanding

2020

With the great success of pre-trained language models, the pretrain-finetune paradigm now becomes the undoubtedly dominant solution for natural language understanding (NLU) tasks. At the fine-tune stage, target task data is usually introduced in a …

Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

Entities, as the essential elements in relation extraction tasks, exhibit certain structure. In this work, we formulate such entity structure as distinctive dependencies between mention pairs. We then propose SSAN, which incorporates these structural dependencies …