12 citations · 20 across the 9 of their papers we have counts for
9 papers
Enhancing SPARQL Generation by Triplet-order-sensitive Pre-training
Chang Su, Jiexing Qi, He Yan +2
Semantic parsing that translates natural language queries to SPARQL is of great importance for Knowledge Graph Question Answering (KGQA) systems. Although pre-trained language mode…
AceMap: Knowledge Discovery through Academic Graph
Xinbing Wang, Luoyi Fu, Xiaoying Gan +23
The exponential growth of scientific literature requires effective management and extraction of valuable insights. While existing scientific search engines excel at delivering sear…
Towards Controlled Table-to-Text Generation with Scientific Reasoning
Zhixin Guo, Jianping Zhou, Jiexing Qi +6
The sheer volume of scientific experimental results and complex technical statements, often presented in tabular formats, presents a formidable barrier to individuals acquiring pre…
Asymmetric Polynomial Loss For Multi-Label Classification
Yusheng Huang, Jiexing Qi, Xinbing Wang +1
Various tasks are reformulated as multi-label classification problems, in which the binary cross-entropy (BCE) loss is frequently utilized for optimizing well-designed models. Howe…
Text Classification in the Wild: a Large-scale Long-tailed Name Normalization Dataset
Jiexing Qi, Shuhao Li, Zhixin Guo +5
Real-world data usually exhibits a long-tailed distribution,with a few frequent labels and a lot of few-shot labels. The study of institution name normalization is a perfect applic…
Adapting Knowledge for Few-shot Table-to-Text Generation
Zhixin Guo, Minyxuan Yan, Jiexing Qi +4
Pretrained language models (PLMs) have made remarkable progress in table-to-text generation tasks. However, the lack of domain-specific knowledge makes it challenging to bridge the…
Few-Shot Table-to-Text Generation with Prompt Planning and Knowledge Memorization
Zhixin Guo, Minyxuan Yan, Jiexing Qi +5
Pre-trained language models (PLM) have achieved remarkable advancement in table-to-text generation tasks. However, the lack of labeled domain-specific knowledge and the topology ga…
INFINITY: A Simple Yet Effective Unsupervised Framework for Graph-Text Mutual Conversion
Yi Xu, Luoyi Fu, Zhouhan Lin +2
Graph-to-text (G2T) generation and text-to-graph (T2G) triple extraction are two essential tasks for constructing and applying knowledge graphs. Existing unsupervised approaches tu…
RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL
Jiexing Qi, Jingyao Tang, Ziwei He +6
Relational structures such as schema linking and schema encoding have been validated as a key component to qualitatively translating natural language into SQL queries. However, int…