41 citations · 115 across the 8 of their papers we have counts for
8 papers
KC-GenRe: A Knowledge-constrained Generative Re-ranking Method Based on Large Language Models for Knowledge Graph Completion
Yilin Wang, Minghao Hu, Zhen Huang +3
The goal of knowledge graph completion (KGC) is to predict missing facts among entities. Previous methods for KGC re-ranking are mostly built on non-generative language models to o…
Interactive Contrastive Learning for Self-supervised Entity Alignment
Kaisheng Zeng, Zhenhao Dong, Lei Hou +6
Self-supervised entity alignment (EA) aims to link equivalent entities across different knowledge graphs (KGs) without seed alignments. The current SOTA self-supervised EA method d…
A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning
Minghao Hu, Yuxing Peng, Zhen Huang +1
Rapid progress has been made in the field of reading comprehension and question answering, where several systems have achieved human parity in some simplified settings. However, th…
Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension
Minghao Hu, Yuxing Peng, Zhen Huang +1
This paper considers the reading comprehension task in which multiple documents are given as input. Prior work has shown that a pipeline of retriever, reader, and reranker can impr…
Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classification
Minghao Hu, Yuxing Peng, Zhen Huang +2
Open-domain targeted sentiment analysis aims to detect opinion targets along with their sentiment polarities from a sentence. Prior work typically formulates this task as a sequenc…
Attention-Guided Answer Distillation for Machine Reading Comprehension
Minghao Hu, Yuxing Peng, Furu Wei +4
Despite that current reading comprehension systems have achieved significant advancements, their promising performances are often obtained at the cost of making an ensemble of nume…
Read + Verify: Machine Reading Comprehension with Unanswerable Questions
Minghao Hu, Furu Wei, Yuxing Peng +3
Machine reading comprehension with unanswerable questions aims to abstain from answering when no answer can be inferred. In addition to extract answers, previous works usually pred…
Reinforced Mnemonic Reader for Machine Reading Comprehension
Minghao Hu, Yuxing Peng, Zhen Huang +3
In this paper, we introduce the Reinforced Mnemonic Reader for machine reading comprehension tasks, which enhances previous attentive readers in two aspects. First, a reattention m…