24 citations · 25 across the 11 of their papers we have counts for
5 papers · 1 filter
ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval
Suyuan Huang, Chao Zhang, Yuanyuan Wu +12
Dense retrieval in most industries employs dual-tower architectures to retrieve query-relevant documents. Due to online deployment requirements, existing real-world dense retrieval…
From a Social Cognitive Perspective: Context-aware Visual Social Relationship Recognition
Shiwei Wu, Chao Zhang, Joya Chen +4
People's social relationships are often manifested through their surroundings, with certain objects or interactions acting as symbols for specific relationships, e.g., wedding ring…
Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation
Yuanjie Lyu, Zihan Niu, Zheyong Xie +4
Despite the significant progress of large language models (LLMs) in various tasks, they often produce factual errors due to their limited internal knowledge. Retrieval-Augmented Ge…
NoteLLM-2: Multimodal Large Representation Models for Recommendation
Chao Zhang, Haoxin Zhang, Shiwei Wu +6
Large Language Models (LLMs) have demonstrated exceptional proficiency in text understanding and embedding tasks. However, their potential in multimodal representation, particularl…
NoteLLM: A Retrievable Large Language Model for Note Recommendation
Chao Zhang, Shiwei Wu, Haoxin Zhang +5
People enjoy sharing "notes" including their experiences within online communities. Therefore, recommending notes aligned with user interests has become a crucial task. Existing on…