TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition
원문 초록
TEXTOIR is the first integrated and visualized platform for text open intent recognition. It is composed of two main modules: open intent detection and open intent discovery. Each module integrates most of the state-of-the-art algorithms and benchmark intent datasets. It also contains an overall framework connecting the two modules in a pipeline scheme. In addition, this platform has visualized tools for data and model management, training, evaluation and analysis of the performance from different aspects. TEXTOIR provides useful toolkits and convenient visualized interfaces for each sub-module (Toolkit code: https://github.com/thuiar/TEXTOIR), and designs a framework to implement a complete process to both identify known intents and discover open intents (Demo code: https://github.com/thuiar/TEXTOIR-DEMO).
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting Framework
From Intent Discovery to Recognition with Topic Modeling and Synthetic Data
Developing a Chatbot system using Deep Learning based for Universities consultancy
skfolio: Portfolio Optimization in Python
100-Day Analysis of USD/IDR Exchange Rate Dynamics Around the 2025 U.S. Presidential Inauguration
Automated Risk Management Mechanisms in DeFi Lending Protocols: A Crosschain Comparative Analysis of Aave and Compound
토론
이 논문과 연결된 포럼 글이 아직 없습니다.