7 papers
Autonomous Information Seeking: A Roadmap for Agentic Recommender Systems
Xinyu Lin, Yashar Deldjoo, Sunhao Dai +7
The rapid integration of large language model-based agents into recommender systems has driven a shift from static, ranking-based pipelines toward autonomous and interactive system…
NeuroCogMap Reveals Cognitive Organization of Large Language Models
Zhongxiang Sun, Haolang Lu, Qiang Ma +11
Understanding how complex cognitive functions are organized within artificial systems is central to interpreting large language models (LLMs) and relating them to biological cognit…
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…
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…