4 papers
Rich-Media Re-Ranker: A User Satisfaction-Driven LLM Re-ranking Framework for Rich-Media Search
Zihao Guo, Ligang Zhou, Zeyang Tang +5
Re-ranking plays a crucial role in modern information search systems by refining the ranking of initial search results to better satisfy user information needs. However, existing m…
An Efficient Framework for Whole-Page Reranking via Single-Modal Supervision
Zishuai Zhang, Sihao Yu, Wenyi Xie +5
The whole-page reranking plays a critical role in shaping the user experience of search engines, which integrates retrieval results from multiple modalities, such as documents, ima…
Leveraging LLMs to Evaluate Usefulness of Document
Xingzhu Wang, Erhan Zhang, Yiqun Chen +7
The conventional Cranfield paradigm struggles to effectively capture user satisfaction due to its weak correlation between relevance and satisfaction, alongside the high costs of r…
FltLM: An Intergrated Long-Context Large Language Model for Effective Context Filtering and Understanding
Jingyang Deng, Zhengyang Shen, Boyang Wang +6
The development of Long-Context Large Language Models (LLMs) has markedly advanced natural language processing by facilitating the process of textual data across long documents and…