Wenliang Chen

SEE: Syntax-Aware Entity Embedding for Neural Relation Extraction

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Distant supervised relation extraction is an efficient approach to scale relation extraction to very large corpora, and has been widely used to find novel relational facts from plain text. Recent studies on neural relation extraction …

Improving Neural Relation Extraction with Positive and Unlabeled Learning

2020 · Proceedings of the AAAI Conference on Artificial Intelligence

We present a novel approach to improve the performance of distant supervision relation extraction with Positive and Unlabeled (PU) Learning. This approach first applies reinforcement learning to decide whether a sentence is positive to a …

Probing Language Models for Pre-training Data Detection

2024 · arXiv (Cornell University)

Large Language Models (LLMs) have shown their impressive capabilities, while also raising concerns about the data contamination problems due to privacy issues and leakage of benchmark datasets in the pre-training phase. Therefore, it is vital …

Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning

2018 · International Conference on Computational Linguistics

A bottleneck problem with Chinese named entity recognition (NER) in new domains is the lack of annotated data. One solution is to utilize the method of distant supervision, which has been widely used in relation …