15 citations · 23 across the 14 of their papers we have counts for
14 papers
Whole-Piece Training for Symbolic Music Language Models via Full-Horizon Compressed Recurrence
Yungang Yi, Weihua Li, Matthew Kuo +2
For computational efficiency, modern language models are typically trained on independently sampled fixed-length sequences. Symbolic music language models largely inherit this para…
PerceiverS: A Multi-Scale Perceiver with Effective Segmentation for Long-Term Expressive Symbolic Music Generation
Yungang Yi, Weihua Li, Matthew Kuo +1
AI-based music generation has made significant progress in recent years. However, generating symbolic music that is both long-structured and expressive remains a significant challe…
Balancing Information Perception with Yin-Yang: Agent-Based Information Neutrality Model for Recommendation Systems
Mengyan Wang, Yuxuan Hu, Shiqing Wu +3
While preference-based recommendation algorithms effectively enhance user engagement by recommending personalized content, they often result in the creation of ``filter bubbles''.…
Detecting misinformation through Framing Theory: the Frame Element-based Model
Guan Wang, Rebecca Frederick, Jinglong Duan +4
In this paper, we delve into the rapidly evolving challenge of misinformation detection, with a specific focus on the nuanced manipulation of narrative frames - an under-explored a…
BHEISR: Nudging from Bias to Balance -- Promoting Belief Harmony by Eliminating Ideological Segregation in Knowledge-based Recommendations
Mengyan Wang, Yuxuan Hu, Zihan Yuan +4
In the realm of personalized recommendation systems, the increasing concern is the amplification of belief imbalance and user biases, a phenomenon primarily attributed to the filte…
Soft Prompt Guided Joint Learning for Cross-Domain Sentiment Analysis
Jingli Shi, Weihua Li, Quan Bai +2
Aspect term extraction is a fundamental task in fine-grained sentiment analysis, which aims at detecting customer's opinion targets from reviews on product or service. The traditio…
DOR: A Novel Dual-Observation-Based Approach for News Recommendation Systems
Mengyan Wang, Weihua Li, Jingli Shi +2
Online social media platforms offer access to a vast amount of information, but sifting through the abundance of news can be overwhelming and tiring for readers. personalised recom…
A Light-weight, Effective and Efficient Model for Label Aggregation in Crowdsourcing
Yi Yang, Zhong-Qiu Zhao, Quan Bai +2
Due to the noises in crowdsourced labels, label aggregation (LA) has emerged as a standard procedure to post-process crowdsourced labels. LA methods estimate true labels from crowd…
Swinv2-Imagen: Hierarchical Vision Transformer Diffusion Models for Text-to-Image Generation
Ruijun Li, Weihua Li, Yi Yang +3
Recently, diffusion models have been proven to perform remarkably well in text-to-image synthesis tasks in a number of studies, immediately presenting new study opportunities for i…
GAC: A Deep Reinforcement Learning Model Toward User Incentivization in Unknown Social Networks
Shiqing Wu, Weihua Li, Quan Bai
In recent years, many applications have deployed incentive mechanisms to promote users' attention and engagement. Most incentive mechanisms determine specific incentive values base…
Identifying Influential Users in Unknown Social Networks for Adaptive Incentive Allocation Under Budget Restriction
Shiqing Wu, Weihua Li, Hao Shen +1
In recent years, recommendation systems have been widely applied in many domains. These systems are impotent in affecting users to choose the behavior that the system expects. Mean…
Graph-based Joint Pandemic Concern and Relation Extraction on Twitter
Jingli Shi, Weihua Li, Sira Yongchareon +2
Public concern detection provides potential guidance to the authorities for crisis management before or during a pandemic outbreak. Detecting people's concerns and attention from o…
ABEM: An Adaptive Agent-based Evolutionary Approach for Mining Influencers in Online Social Networks
Weihua Li, Yuxuan Hu, Shiqing Wu +2
A key step in influence maximization in online social networks is the identification of a small number of users, known as influencers, who are able to spread influence quickly and…
Privacy Information Classification: A Hybrid Approach
Jiaqi Wu, Weihua Li, Quan Bai +2
A large amount of information has been published to online social networks every day. Individual privacy-related information is also possibly disclosed unconsciously by the end-use…