5 citations · 5 across the 7 of their papers we have counts for
16 papers
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…
WebRenderBench: Enhancing Web Interface Generation through Layout-Style Consistency and Reinforcement Learning
Peichao Lai, Jinhui Zhuang, Kexuan Zhang +6
Automating the conversion of UI images into web code is a critical task for front-end development and rapid prototyping. Advances in multimodal large language models (MLLMs) have m…
M2IO-R1: An Efficient RL-Enhanced Reasoning Framework for Multimodal Retrieval Augmented Multimodal Generation
Zhiyou Xiao, Qinhan Yu, Binghui Li +3
Current research on Multimodal Retrieval-Augmented Generation (MRAG) enables diverse multimodal inputs but remains limited to single-modality outputs, restricting expressive capaci…
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…
TableRAG: A Retrieval Augmented Generation Framework for Heterogeneous Document Reasoning
Xiaohan Yu, Pu Jian, Chong Chen
Retrieval-Augmented Generation (RAG) has demonstrated considerable effectiveness in open-domain question answering. However, when applied to heterogeneous documents, comprising bot…
Bridge the Domains: Large Language Models Enhanced Cross-domain Sequential Recommendation
Qidong Liu, Xiangyu Zhao, Yejing Wang +6
Cross-domain Sequential Recommendation (CDSR) aims to extract the preference from the user's historical interactions across various domains. Despite some progress in CDSR, two prob…