Search Results for author:
Found 5 papers, 1 papers with code
SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models
Knowledge graph completion (KGC) aims to reason over known facts and infer the missing links.
Ranked #2 on
Link Prediction
on WN18RR
ChemistryQA: A Complex Question Answering Dataset from Chemistry
We notice that some real-world QA tasks are more complex, which cannot be solved by end-to-end neural networks or translated to any kind of formal representations.
BERT-AL: BERT for Arbitrarily Long Document Understanding
When we apply BERT to long text tasks, e. g., document-level text summarization: 1) Truncating inputs by the maximum sequence length will decrease performance, since the model cannot capture long dependency and global information ranging the whole document.
IJCNLP-2017 Task 5: Multi-choice Question Answering in Examinations
The IJCNLP-2017 Multi-choice Question Answering(MCQA) task aims at exploring the performance of current Question Answering(QA) techniques via the realworld complex questions collected from Chinese Senior High School Entrance Examination papers and CK12 website1.
