12 citations · 39 across the 19 of their papers we have counts for
19 papers
Logical Consistency is Vital: Neural-Symbolic Information Retrieval for Negative-Constraint Queries
Ganlin Xu, Zhoujia Zhang, Wangyi Mei +7
Information retrieval plays a crucial role in resource localization. Current dense retrievers retrieve the relevant documents within a corpus via embedding similarities, which comp…
Negation Triplet Extraction with Syntactic Dependency and Semantic Consistency
Yuchen Shi, Deqing Yang, Jingping Liu +3
Previous works of negation understanding mainly focus on negation cue detection and scope resolution, without identifying negation subject which is also significant to the downstre…
Improving Recall of Large Language Models: A Model Collaboration Approach for Relational Triple Extraction
Zepeng Ding, Wenhao Huang, Jiaqing Liang +2
Relation triple extraction, which outputs a set of triples from long sentences, plays a vital role in knowledge acquisition. Large language models can accurately extract triples fr…
Reason from Fallacy: Enhancing Large Language Models' Logical Reasoning through Logical Fallacy Understanding
Yanda Li, Dixuan Wang, Jiaqing Liang +4
Large Language Models (LLMs) have demonstrated good performance in many reasoning tasks, but they still struggle with some complicated reasoning tasks including logical reasoning.…
ToNER: Type-oriented Named Entity Recognition with Generative Language Model
Guochao Jiang, Ziqin Luo, Yuchen Shi +3
In recent years, the fine-tuned generative models have been proven more powerful than the previous tagging-based or span-based models on named entity recognition (NER) task. It has…
Exploiting Duality in Open Information Extraction with Predicate Prompt
Zhen Chen, Jingping Liu, Deqing Yang +5
Open information extraction (OpenIE) aims to extract the schema-free triplets in the form of (\emph{subject}, \emph{predicate}, \emph{object}) from a given sentence. Compared with…
Causality-aware Concept Extraction based on Knowledge-guided Prompting
Siyu Yuan, Deqing Yang, Jinxi Liu +4
Concepts benefit natural language understanding but are far from complete in existing knowledge graphs (KGs). Recently, pre-trained language models (PLMs) have been widely used in…
Accelerating Personalized PageRank Vector Computation
Zhen Chen, Xingzhi Guo, Baojian Zhou +2
Personalized PageRank Vectors are widely used as fundamental graph-learning tools for detecting anomalous spammers, learning graph embeddings, and training graph neural networks. T…
Distilling Script Knowledge from Large Language Models for Constrained Language Planning
Siyu Yuan, Jiangjie Chen, Ziquan Fu +5
In everyday life, humans often plan their actions by following step-by-step instructions in the form of goal-oriented scripts. Previous work has exploited language models (LMs) to…
ANALOGYKB: Unlocking Analogical Reasoning of Language Models with A Million-scale Knowledge Base
Siyu Yuan, Jiangjie Chen, Changzhi Sun +3
Analogical reasoning is a fundamental cognitive ability of humans. However, current language models (LMs) still struggle to achieve human-like performance in analogical reasoning t…
Generative Entity Typing with Curriculum Learning
Siyu Yuan, Deqing Yang, Jiaqing Liang +4
Entity typing aims to assign types to the entity mentions in given texts. The traditional classification-based entity typing paradigm has two unignorable drawbacks: 1) it fails to…
Improving Continual Relation Extraction through Prototypical Contrastive Learning
Chengwei Hu, Deqing Yang, Haoliang Jin +2
Continual relation extraction (CRE) aims to extract relations towards the continuous and iterative arrival of new data, of which the major challenge is the catastrophic forgetting…
Large-scale Multi-granular Concept Extraction Based on Machine Reading Comprehension
Siyu Yuan, Deqing Yang, Jiaqing Liang +5
The concepts in knowledge graphs (KGs) enable machines to understand natural language, and thus play an indispensable role in many applications. However, existing KGs have the poor…
Contextual Information and Commonsense Based Prompt for Emotion Recognition in Conversation
Jingjie Yi, Deqing Yang, Siyu Yuan +3
Emotion recognition in conversation (ERC) aims to detect the emotion for each utterance in a given conversation. The newly proposed ERC models have leveraged pre-trained language m…
Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation Extraction
Jiaxin Yu, Deqing Yang, Shuyu Tian
Compared with traditional sentence-level relation extraction, document-level relation extraction is a more challenging task where an entity in a document may be mentioned multiple…
Improving Information Cascade Modeling by Social Topology and Dual Role User Dependency
Baichuan Liu, Deqing Yang, Yueyi Wang +1
In the last decade, information diffusion (also known as information cascade) on social networks has been massively investigated due to its application values in many fields. In re…
A Question-answering Based Framework for Relation Extraction Validation
Jiayang Cheng, Haiyun Jiang, Deqing Yang +1
Relation extraction is an important task in knowledge acquisition and text understanding. Existing works mainly focus on improving relation extraction by extracting effective featu…
Complex Relation Extraction: Challenges and Opportunities
Haiyun Jiang, Qiaoben Bao, Qiao Cheng +3
Relation extraction aims to identify the target relations of entities in texts. Relation extraction is very important for knowledge base construction and text understanding. Tradit…
Towards Combinational Relation Linking over Knowledge Graphs
Weiguo Zheng, Mei Zhang
Given a natural language phrase, relation linking aims to find a relation (predicate or property) from the underlying knowledge graph to match the phrase. It is very useful in many…