2 citations · 6 across the 11 of their papers we have counts for
11 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…
Ideological Isolation in Online Social Networks: A Survey of Computational Definitions, Metrics, and Mitigation Strategies
Xiaodan Wang, Yanbin Liu, Shiqing Wu +4
The proliferation of online social networks has significantly reshaped the way individuals access and engage with information. While these platforms offer unprecedented connectivit…
Towards Superior Quantization Accuracy: A Layer-sensitive Approach
Feng Zhang, Yanbin Liu, Weihua Li +3
Large Vision and Language Models have exhibited remarkable human-like intelligence in tasks such as natural language comprehension, problem-solving, logical reasoning, and knowledg…
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…
AaKOS: Aspect-adaptive Knowledge-based Opinion Summarization
Guan Wang, Weihua Li, Edmund M-K. Lai +1
The rapid growth of information on the Internet has led to an overwhelming amount of opinions and comments on various activities, products, and services. This makes it difficult an…
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…