24 citations · 34 across the 11 of their papers we have counts for
11 papers
ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation
Weihan Wang, Zhen Yang, Bin Xu +2
Vision-language pre-training (VLP) methods are blossoming recently, and its crucial goal is to jointly learn visual and textual features via a transformer-based architecture, demon…
KoLA: Carefully Benchmarking World Knowledge of Large Language Models
Jifan Yu, Xiaozhi Wang, Shangqing Tu +32
The unprecedented performance of large language models (LLMs) necessitates improvements in evaluations. Rather than merely exploring the breadth of LLM abilities, we believe meticu…
Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction
Ji Qi, Chuchun Zhang, Xiaozhi Wang +8
The robustness to distribution changes ensures that NLP models can be successfully applied in the realistic world, especially for information extraction tasks. However, most prior…
Syntactically Robust Training on Partially-Observed Data for Open Information Extraction
Ji Qi, Yuxiang Chen, Lei Hou +2
Open Information Extraction models have shown promising results with sufficient supervision. However, these models face a fundamental challenge that the syntactic distribution of t…
ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction
Ji Qi, Bin Xu, Kaisheng Zeng +5
Document-level relation extraction with graph neural networks faces a fundamental graph construction gap between training and inference - the golden graph structure only available…
OpenQA: Hybrid QA System Relying on Structured Knowledge Base as well as Non-structured Data
Gaochen Wu, Bin Xu, Yuxin Qin +3
Search engines based on keyword retrieval can no longer adapt to the way of information acquisition in the era of intelligent Internet of Things due to the return of keyword relate…
PatentMiner: Patent Vacancy Mining via Context-enhanced and Knowledge-guided Graph Attention
Gaochen Wu, Bin Xu, Yuxin Qin +4
Although there are a small number of work to conduct patent research by building knowledge graph, but without constructing patent knowledge graph using patent documents and combini…
Improving Low-resource Reading Comprehension via Cross-lingual Transposition Rethinking
Gaochen Wu, Bin Xu, Yuxin Qin +4
Extractive Reading Comprehension (ERC) has made tremendous advances enabled by the availability of large-scale high-quality ERC training data. Despite of such rapid progress and wi…
Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition
Meihan Tong, Shuai Wang, Bin Xu +4
Few-shot Named Entity Recognition (NER) exploits only a handful of annotations to identify and classify named entity mentions. Prototypical network shows superior performance on fe…
A Multilingual Modeling Method for Span-Extraction Reading Comprehension
Gaochen Wu, Bin Xu, Dejie Chang +1
Span-extraction reading comprehension models have made tremendous advances enabled by the availability of large-scale, high-quality training datasets. Despite such rapid progress a…
DiaKG: an Annotated Diabetes Dataset for Medical Knowledge Graph Construction
Dejie Chang, Mosha Chen, Chaozhen Liu +9
Knowledge Graph has been proven effective in modeling structured information and conceptual knowledge, especially in the medical domain. However, the lack of high-quality annotated…