跳至主導覽
跳至搜尋
跳過主要內容
國立陽明交通大學研發優勢分析平台 首頁
English
中文
首頁
人員
單位
研究成果
計畫
獎項
活動
貴重儀器
影響
按專業知識、姓名或所屬機構搜尋
InstructPatentGPT: training patent language models to follow instructions with human feedback
Jieh-Sheng Lee
科技法律研究所
研究成果
:
Article
›
同行評審
總覽
指紋
指紋
深入研究「InstructPatentGPT: training patent language models to follow instructions with human feedback」主題。共同形成了獨特的指紋。
排序方式
重量
按字母排序
Keyphrases
Language Model
100%
Human Feedback
100%
Patent Prosecution
80%
Reinforcement Learning from Human Feedback
40%
Artificial Intelligence
20%
Patent Office
20%
3-stage
20%
Training Data
20%
Hardware Requirements
20%
Human Intention
20%
Patent Claims
20%
Patent Data
20%
Model Capabilities
20%
Patent Text
20%
Public Domain
20%
Consumer-grade
20%
Modern Techniques
20%
Granted Patents
20%
Generative Language Models
20%
Grant Applications
20%
Patent Drafting
20%
Engineering
Proof-of-Concept
100%
Reinforcement Learning
100%
Graphics Processing Unit
50%
Patent Office
50%
Artificial Intelligence
50%
Controllability
50%
Computer Science
Language Modeling
100%
Patent Prosecution
80%
Reinforcement Learning
40%
Training Data
20%
Hardware Requirement
20%
Data Originates
20%
Artificial Intelligence
20%
Graphics Processing Unit
20%
Social Sciences
Language Modeling
100%
Patent Prosecution
80%
Controllability
20%
Artificial Intelligence
20%
Psychology
Artificial Intelligence
100%
Controllability
100%
Material Science
Patent Prosecution
100%