77 citations · 304 across the 92 of their papers we have counts for
17 papers · 1 filter
Answering Complex Logical Queries on Knowledge Graphs via Query Computation Tree Optimization
Yushi Bai, Xin Lv, Juanzi Li +1
Answering complex logical queries on incomplete knowledge graphs is a challenging task, and has been widely studied. Embedding-based methods require training on complex queries, an…
Finding Skill Neurons in Pre-trained Transformer-based Language Models
Xiaozhi Wang, Kaiyue Wen, Zhengyan Zhang +3
Transformer-based pre-trained language models have demonstrated superior performance on various natural language processing tasks. However, it remains unclear how the skills requir…
MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction
Xiaozhi Wang, Yulin Chen, Ning Ding +9
The diverse relationships among real-world events, including coreference, temporal, causal, and subevent relations, are fundamental to understanding natural languages. However, two…
COPEN: Probing Conceptual Knowledge in Pre-trained Language Models
Hao Peng, Xiaozhi Wang, Shengding Hu +5
Conceptual knowledge is fundamental to human cognition and knowledge bases. However, existing knowledge probing works only focus on evaluating factual knowledge of pre-trained lang…
A Survey of Knowledge Enhanced Pre-trained Language Models
Linmei Hu, Zeyi Liu, Ziwang Zhao +3
Pre-trained Language Models (PLMs) which are trained on large text corpus via self-supervised learning method, have yielded promising performance on various tasks in Natural Langua…
EDUKG: a Heterogeneous Sustainable K-12 Educational Knowledge Graph
Bowen Zhao, Jiuding Sun, Bin Xu +9
Web and artificial intelligence technologies, especially semantic web and knowledge graph (KG), have recently raised significant attention in educational scenarios. Nevertheless, s…
Step out of KG: Knowledge Graph Completion via Knowledgeable Retrieval and Reading Comprehension
Xin Lv, Yankai Lin, Zijun Yao +4
Knowledge graphs, as the cornerstone of many AI applications, usually face serious incompleteness problems. In recent years, there have been many efforts to study automatic knowled…
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…
Unveiling the Black Box of PLMs with Semantic Anchors: Towards Interpretable Neural Semantic Parsing
Lunyiu Nie, Jiuding Sun, Yanlin Wang +6
The recent prevalence of pretrained language models (PLMs) has dramatically shifted the paradigm of semantic parsing, where the mapping from natural language utterances to structur…
Towards a General Pre-training Framework for Adaptive Learning in MOOCs
Qingyang Zhong, Jifan Yu, Zheyuan Zhang +6
Adaptive learning aims to stimulate and meet the needs of individual learners, which requires sophisticated system-level coordination of diverse tasks, including modeling learning…
GraphQ IR: Unifying the Semantic Parsing of Graph Query Languages with One Intermediate Representation
Lunyiu Nie, Shulin Cao, Jiaxin Shi +5
Subject to the huge semantic gap between natural and formal languages, neural semantic parsing is typically bottlenecked by its complexity of dealing with both input semantics and…
A Roadmap for Big Model
Sha Yuan, Hanyu Zhao, Shuai Zhao +97
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm. Researchers have achieved various outcomes in the c…
LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
Feng Yao, Chaojun Xiao, Xiaozhi Wang +7
Recognizing facts is the most fundamental step in making judgments, hence detecting events in the legal documents is important to legal case analysis tasks. However, existing Legal…
Schema-Free Dependency Parsing via Sequence Generation
Boda Lin, Zijun Yao, Jiaxin Shi +6
Dependency parsing aims to extract syntactic dependency structure or semantic dependency structure for sentences. Existing methods suffer the drawbacks of lacking universality or h…
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…
SQUIRE: A Sequence-to-sequence Framework for Multi-hop Knowledge Graph Reasoning
Yushi Bai, Xin Lv, Juanzi Li +4
Multi-hop knowledge graph (KG) reasoning has been widely studied in recent years to provide interpretable predictions on missing links with evidential paths. Most previous works us…
Multimodal Entity Tagging with Multimodal Knowledge Base
Hao Peng, Hang Li, Lei Hou +2
To enhance research on multimodal knowledge base and multimodal information processing, we propose a new task called multimodal entity tagging (MET) with a multimodal knowledge bas…