Baobao Chang

Table-to-Text Generation by Structure-Aware Seq2seq Learning

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Table-to-text generation aims to generate a description for a factual table which can be viewed as a set of field-value records. To encode both the content and the structure of a table, we propose a …

Incorporating Glosses into Neural Word Sense Disambiguation

2018

Word Sense Disambiguation (WSD) aims to identify the correct meaning of polysemous words in the particular context. Lexical resources like WordNet which are proved to be of great help for WSD in the knowledge-based methods. …

Improving the Robustness of Distantly-Supervised Named Entity Recognition via Uncertainty-Aware Teacher Learning and Student-Student Collaborative Learning

2024

Distantly-Supervised Named Entity Recognition (DS-NER) effectively alleviates the burden of annotation, but meanwhile suffers from the label noise.Recent works attempt to adopt the teacher-student framework to gradually refine the training labels and improve the overall …

Joint entity-relation extraction: A key technique for knowledge graph construction—A survey

2026 · Journal of Terminology and Knowledge Engineering

<p indent="0mm">Knowledge graph (KG), which aims to represent unstructured semantic knowledge in the form of structured triplet, is crucial to establishing the knowledge base for artificial intelligence (AI) research. There are many techniques proposed for …

Gated Self-Matching Networks for Reading Comprehension and Question Answering

2017

In this paper, we present the gated selfmatching networks for reading comprehension style question answering, which aims to answer questions from a given passage. We first match the question and passage with gated attention-based recurrent …

Jointly Extracting Event Triggers and Arguments by Dependency-Bridge RNN and Tensor-Based Argument Interaction

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Event extraction plays an important role in natural language processing (NLP) applications including question answering and information retrieval. Traditional event extraction relies heavily on lexical and syntactic features, which require intensive human engineering and may …

Double Graph Based Reasoning for Document-level Relation Extraction

2020

Document-level relation extraction aims to extract relations among entities within a document. Different from sentence-level relation extraction, it requires reasoning over multiple sentences across paragraphs. In this paper, we propose Graph Aggregation-and-Inference Network (GAIN), a …

A Survey on In-context Learning

2022 · arXiv (Cornell University)

With the increasing capabilities of large language models (LLMs), in-context learning (ICL) has emerged as a new paradigm for natural language processing (NLP), where LLMs make predictions based on contexts augmented with a few examples. …