most citedA Survey of Multimodal Retrieval-Augmented Generation

5 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2026

MSearcher: Modular Multimodal Information Seeking Agency with Retrieval-Oriented Reasoning

Xiaohan Yu, Chao Feng, Lang Mei +1

Recent advances in DeepResearch-style agents have demonstrated strong capabilities in autonomous information acquisition and synthesize from real-world web environments. However, e…

cs.IR20251 cited

Addressing Personalized Bias for Unbiased Learning to Rank

Zechun Niu, Lang Mei, Liu Yang +4

Unbiased learning to rank (ULTR), which aims to learn unbiased ranking models from biased user behavior logs, plays an important role in Web search. Previous research on ULTR has s…

cs.AI2025

AI-SearchPlanner: Modular Agentic Search via Pareto-Optimal Multi-Objective Reinforcement Learning

Lang Mei, Zhihan Yang, Xiaohan Yu +2

Recent studies have explored integrating Large Language Models (LLMs) with search engines to leverage both the LLMs' internal pre-trained knowledge and external information. Specia…

cs.IR20255 cited

A Survey of Multimodal Retrieval-Augmented Generation

Lang Mei, Siyu Mo, Zhihan Yang +1

Multimodal Retrieval-Augmented Generation (MRAG) enhances large language models (LLMs) by integrating multimodal data (text, images, videos) into retrieval and generation processes…

cs.CL2025

PanguIR Technical Report for NTCIR-18 AEOLLM Task

Lang Mei, Chong Chen, Jiaxin Mao

As large language models (LLMs) gain widespread attention in both academia and industry, it becomes increasingly critical and challenging to effectively evaluate their capabilities…