1 citations · 3 across the 10 of their papers we have counts for
11 papers
MMSearch-OPD: Easy Made Hard, Hard Made Learnable for Long-Horizon Multimodal Search Agents
Huanyao Zhang, Jiepeng Zhou, Jiaye Lin +9
Multimodal deep search is moving from short queries to long-horizon investigations that continually acquire evidence. However, training such agents remains constrained by limited c…
SearchArt: Training Long-Horizon Search Agent with Scalable Synthetic and Verified Task
Lang Mei, Xiaohan Yu, Chong Chen +27
Recent advances in large language models (LLMs) have enabled search agents to autonomously tackle complex tasks across extended search and reasoning horizons. However, training eff…
DeepVoyager-VL: Incentivizing Vision-in-the-Loop Search for Long-Horizon Multimodal Agents
Huanyao Zhang, Jiepeng Zhou, Runhao Zhao +12
Multimodal large language models (MLLMs) have advanced visual understanding and reasoning, yet their static parametric knowledge limits their ability to address knowledge-intensive…
AgentOmnia: Scaling Agentic Models for Full-Scenario Applications
Hao Jiang, Gangtao Xin, Yingdi Huang +35
Large language model agents have advanced rapidly, yet progress remains fragmented across domains, capabilities, task difficulty, and interaction settings. We frame this as full-sc…
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…
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…
CogPlanner: Unveiling the Potential of Agentic Multimodal Retrieval Augmented Generation with Planning
Xiaohan Yu, Zhihan Yang, Chong Chen
Multimodal Retrieval Augmented Generation (MRAG) systems have shown promise in enhancing the generation capabilities of multimodal large language models (MLLMs). However, existing…
Explainable CTR Prediction via LLM Reasoning
Xiaohan Yu, Li Zhang, Chong Chen
Recommendation Systems have become integral to modern user experiences, but lack transparency in their decision-making processes. Existing explainable recommendation methods are hi…
Break the ID-Language Barrier: An Adaption Framework for LLM-based Sequential Recommendation
Xiaohan Yu, Li Zhang, Xin Zhao +1
The recent breakthrough of large language models (LLMs) in natural language processing has sparked exploration in recommendation systems, however, their limited domain-specific kno…
RA-Rec: An Efficient ID Representation Alignment Framework for LLM-based Recommendation
Xiaohan Yu, Li Zhang, Xin Zhao +2
Large language models (LLM) have recently emerged as a powerful tool for a variety of natural language processing tasks, bringing a new surge of combining LLM with recommendation s…
Multi-Tower Multi-Interest Recommendation with User Representation Repel
Tianyu Xiong, Xiaohan Yu
In the era of information overload, the value of recommender systems has been profoundly recognized in academia and industry alike. Multi-interest sequential recommendation, in par…