124 citations · 127 across the 11 of their papers we have counts for
13 papers
ICG: Improving Cover Image Generation via MLLM-based Prompting and Personalized Preference Alignment
Zhipeng Bian, Jieming Zhu, Qijiong Liu +6
Recent advances in multimodal large language models (MLLMs) and diffusion models (DMs) have opened new possibilities for AI-generated content. Yet, personalized cover image generat…
FuXi-: Efficient Sequential Recommendation with Exponential-Power Temporal Encoder and Diagonal-Sparse Positional Mechanism
Dezhi Yi, Wei Guo, Wenyang Cui +5
Sequential recommendation aims to model users' evolving preferences based on their historical interactions. Recent advances leverage Transformer-based architectures to capture glob…
Regret-aware Re-ranking for Guaranteeing Two-sided Fairness and Accuracy in Recommender Systems
Xiaopeng Ye, Chen Xu, Jun Xu +3
In multi-stakeholder recommender systems (RS), users and providers operate as two crucial and interdependent roles, whose interests must be well-balanced. Prior research, including…
Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents
Haoyu Wang, Sunhao Dai, Haiyuan Zhao +6
Previous studies have found that PLM-based retrieval models exhibit a preference for LLM-generated content, assigning higher relevance scores to these documents even when their sem…
CHOP: Mobile Operating Assistant with Constrained High-frequency Optimized Subtask Planning
Yuqi Zhou, Shuai Wang, Sunhao Dai +4
The advancement of visual language models (VLMs) has enhanced mobile device operations, allowing simulated human-like actions to address user requirements. Current VLM-based mobile…
Inference Computation Scaling for Feature Augmentation in Recommendation Systems
Weihao Liu, Zhaocheng Du, Haiyuan Zhao +5
Large language models have become a powerful method for feature augmentation in recommendation systems. However, existing approaches relying on quick inference often suffer from in…
Few-shot LLM Synthetic Data with Distribution Matching
Jiyuan Ren, Zhaocheng Du, Zhihao Wen +4
As large language models (LLMs) advance, their ability to perform in-context learning and few-shot language generation has improved significantly. This has spurred using LLMs to pr…
CreAgent: Towards Long-Term Evaluation of Recommender System under Platform-Creator Information Asymmetry
Xiaopeng Ye, Chen Xu, Zhongxiang Sun +4
Ensuring the long-term sustainability of recommender systems (RS) emerges as a crucial issue. Traditional offline evaluation methods for RS typically focus on immediate user feedba…
Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration
Sunhao Dai, Weihao Liu, Yuqi Zhou +6
The proliferation of Large Language Models (LLMs) has led to an influx of AI-generated content (AIGC) on the internet, transforming the corpus of Information Retrieval (IR) systems…
Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time
Haiyuan Zhao, Guohao Cai, Jieming Zhu +3
In video recommendation, an ongoing effort is to satisfy users' personalized information needs by leveraging their logged watch time. However, watch time prediction suffers from du…
Exploring the Escalation of Source Bias in User, Data, and Recommender System Feedback Loop
Yuqi Zhou, Sunhao Dai, Liang Pang +4
Recommender systems are essential for information access, allowing users to present their content for recommendation. With the rise of large language models (LLMs), AI-generated co…
Guaranteeing Accuracy and Fairness under Fluctuating User Traffic: A Bankruptcy-Inspired Re-ranking Approach
Xiaopeng Ye, Chen Xu, Jun Xu +3
Out of sustainable and economical considerations, two-sided recommendation platforms must satisfy the needs of both users and providers. Previous studies often show that the two si…
Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era
Sunhao Dai, Chen Xu, Shicheng Xu +3
With the rapid advancements of large language models (LLMs), information retrieval (IR) systems, such as search engines and recommender systems, have undergone a significant paradi…