Yifu Li
Biographic Data
| ID | 4430288 |
|---|---|
| NAME | Yifu Li |
| GIVEN NAMES | Yifu |
| FAMILY NAME | Li |
| SIGNATURE | LI Y |
| AFFILIATIONS | University of Oklahoma |
| ORCID | 0000-0003-0602-8429 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Embracing or rejecting AI? A mixed-method study on undergraduate students’ perceptions of artificial intelligence at a private university in China
The rise of artificial intelligence (AI), particularly ChatGPT, has transformed educational landscapes globally. Moreover, the Beijing Consensus on Artificial Intelligence and Education and the ‘Pact for the Future’ propose that AI can support UNESCO in achieving development goals, especially focusing on SDG 4, which emphasizes quality education. Thus, this study investigates undergraduate students’ familiarity with and attitudes toward AI tools,…
Efficient Duplicate Comment Detection for Rulemaking Agencies With Unsupervised Deep Learning: A Cost-Effective and High-Accuracy Approach
Government agencies tasked with soliciting comments from the American public in response to changes in rulemaking have long been interested in finding effective techniques to automatically process spam comments, including flagging and filtering duplicate comments. Duplicate submissions are problematic because they obscure genuine public input and may amplify fringe opinions nonrepresentative of the majority of the American public. Given that dupl…
Public Segmentation and the Impact of AI Use in E-Rulemaking
Digitization has profoundly changed how government interacts with its publics. The expanding use of AI promises even more advancement. However, the rollout of AI is not without risk. This work explores the use of AI in federal rulemaking, the process by which regulations are introduced and revised. The US federal government has created digital platforms that dramatically expand access for the public commenting on pending regulations. However, the…
Predicting depression by using a novel deep learning model and video-audio-text multimodal data
These results underscore the robustness and precision of the IMDD-Net, highlighting the importance of integrating local and global features across multiple modalities for accurate depression prediction
Managing Opinion Spamming with AI in Regulatory Public Engagement
Aconitine blocks Herg and Kv1.5 potassium channels
Aconitine blocks Herg and Kv1.5 potassium channels
Embracing or rejecting AI? A mixed-method study on undergraduate students’ perceptions of artificial intelligence at a private university in China
The rise of artificial intelligence (AI), particularly ChatGPT, has transformed educational landscapes globally. Moreover, the Beijing Consensus on Artificial Intelligence and Education and the ‘Pact for the Future’ propose that AI can support UNESCO in achieving development goals, especially focusing on SDG 4, which emphasizes quality education. Thus, this study investigates undergraduate students’ familiarity with and attitudes toward AI tools,…
Efficient Duplicate Comment Detection for Rulemaking Agencies With Unsupervised Deep Learning: A Cost-Effective and High-Accuracy Approach
Government agencies tasked with soliciting comments from the American public in response to changes in rulemaking have long been interested in finding effective techniques to automatically process spam comments, including flagging and filtering duplicate comments. Duplicate submissions are problematic because they obscure genuine public input and may amplify fringe opinions nonrepresentative of the majority of the American public. Given that dupl…
Public Segmentation and the Impact of AI Use in E-Rulemaking
Digitization has profoundly changed how government interacts with its publics. The expanding use of AI promises even more advancement. However, the rollout of AI is not without risk. This work explores the use of AI in federal rulemaking, the process by which regulations are introduced and revised. The US federal government has created digital platforms that dramatically expand access for the public commenting on pending regulations. However, the…
Predicting depression by using a novel deep learning model and video-audio-text multimodal data
These results underscore the robustness and precision of the IMDD-Net, highlighting the importance of integrating local and global features across multiple modalities for accurate depression prediction
Managing Opinion Spamming with AI in Regulatory Public Engagement
Computer Science (4 works) · Political science (4 works) · Artificial Intelligence (3 works) · Law (3 works) · Deep learning (2 works) · Hate Speech and Cyberbullying Detection (2 works) · Rulemaking (2 works) · Aconitine (1 works) · Aconitum (1 works) · AI in Service Interactions (1 works)