activity
20182023
most citedSEE: Syntax-aware Entity Embedding for Neural Relation Extraction

21 citations · 31 across the 4 of their papers we have counts for

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Showing cs.CLShow all

7 papers · 1 filter

cs.CL2023

OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch

Juntao Li, Zecheng Tang, Yuyang Ding +9

Large language models (LLMs) with billions of parameters have demonstrated outstanding performance on various natural language processing tasks. This report presents OpenBA, an ope…

cs.CL20234 cited

Make a Choice! Knowledge Base Question Answering with In-Context Learning

Chuanyuan Tan, Yuehe Chen, Wenbiao Shao +1

Question answering over knowledge bases (KBQA) aims to answer factoid questions with a given knowledge base (KB). Due to the large scale of KB, annotated data is impossible to cove…

cs.CL2023

CED: Catalog Extraction from Documents

Tong Zhu, Guoliang Zhang, Zechang Li +7

Sentence-by-sentence information extraction from long documents is an exhausting and error-prone task. As the indicator of document skeleton, catalogs naturally chunk documents int…

cs.CL2022

A Method of Query Graph Reranking for Knowledge Base Question Answering

Yonghui Jia, Wenliang Chen

This paper presents a novel reranking method to better choose the optimal query graph, a sub-graph of knowledge graph, to retrieve the answer for an input question in Knowledge Bas…

cs.CL2022

Better Query Graph Selection for Knowledge Base Question Answering

Yonghui Jia, Wenliang Chen

This paper presents a novel approach based on semantic parsing to improve the performance of Knowledge Base Question Answering (KBQA). Specifically, we focus on how to select an op…

cs.CL201810 cited

Adversarial Learning for Chinese NER from Crowd Annotations

YaoSheng Yang, Meishan Zhang, Wenliang Chen +3

To quickly obtain new labeled data, we can choose crowdsourcing as an alternative way at lower cost in a short time. But as an exchange, crowd annotations from non-experts may be o…