Jianqi Gao
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View article: Application of 3D printing imaging technology in the treatment of bronchopleural fistula with individual customized bronchial occluder
Application of 3D printing imaging technology in the treatment of bronchopleural fistula with individual customized bronchial occluder Open
The 3D-printed personalized occluder (TG-II) significantly reduced postoperative inflammatory responses and alleviated cough-associated pain, demonstrating superior short-term efficacy and safety compared to conventional treatment (CG) and…
View article: Promoting Knowledge Base Question Answering by Directing LLMs to Generate Task-relevant Logical Forms
Promoting Knowledge Base Question Answering by Directing LLMs to Generate Task-relevant Logical Forms Open
Knowledge base question answering (KBQA) refers to the system that produces answers to user queries by reasoning with a large-scale structured knowledge base. Advanced works have achieved great success either by generating logical forms (L…
View article: Hierarchical Reinforcement Learning for Safe Mapless Navigation with Congestion Estimation
Hierarchical Reinforcement Learning for Safe Mapless Navigation with Congestion Estimation Open
Reinforcement learning-based mapless navigation holds significant potential. However, it faces challenges in indoor environments with local minima area. This paper introduces a safe mapless navigation framework utilizing hierarchical reinf…
View article: LogLLM: Log-based Anomaly Detection Using Large Language Models
LogLLM: Log-based Anomaly Detection Using Large Language Models Open
Software systems often record important runtime information in logs to help with troubleshooting. Log-based anomaly detection has become a key research area that aims to identify system issues through log data, ultimately enhancing the rel…
View article: Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective
Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective Open
Multi-agent target assignment and path planning (TAPF) are two key problems in intelligent warehouse. However, most literature only addresses one of these two problems separately. In this study, we propose a method to simultaneously solve …
View article: RDE: A Hybrid Policy Framework for Multi-Agent Path Finding Problem
RDE: A Hybrid Policy Framework for Multi-Agent Path Finding Problem Open
Multi-agent path finding (MAPF) is an abstract model for the navigation of multiple robots in warehouse automation, where multiple robots plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been empl…
View article: A Two-Objective ILP Model of OP-MATSP for the Multi-Robot Task Assignment in an Intelligent Warehouse
A Two-Objective ILP Model of OP-MATSP for the Multi-Robot Task Assignment in an Intelligent Warehouse Open
Multi-robot task assignment is one of the main processes in an intelligent warehouse. This paper models multi-robot task assignment in an intelligent warehouse as an open-path multi-depot asymmetric traveling salesman problem (OP-MATSP). A…
View article: Back to Prior Knowledge: Joint Event Causality Extraction via Convolutional Semantic Infusion
Back to Prior Knowledge: Joint Event Causality Extraction via Convolutional Semantic Infusion Open
Joint event and causality extraction is a challenging yet essential task in information retrieval and data mining. Recently, pre-trained language models (e.g., BERT) yield state-of-the-art results and dominate in a variety of NLP tasks. Ho…