15 citations · 15 across the 11 of their papers we have counts for
12 papers
AI Smart Glasses for Wearable Intelligence: From Egocentric Sensing to Agentic Personalization
Xu Yuan, Yi Wang, Zhuohang Jiang +8
Recent advances in artificial intelligence (AI) are reshaping smart glasses from egocentric capture and display devices into platforms for wearable intelligence. Smart glasses incr…
FashionKG-RAG: Knowledge Graph-Enhanced Retrieval-Augmented Generation for Fashion Question Answering
Yujuan Ding, Linyin Luo, Shijie Wang +5
Fashion is a knowledge-intensive domain in which effective decision-making depends on integrating multiple types of knowledge. Although Large Language Models (LLMs) have transforme…
Diffusion Language Model for Recommendation
Chengyi Liu, Yongqi Zhou, Junwei Pan +8
Large language model (LLM)-empowered recommender systems have emerged as a promising paradigm for generative recommendation, leveraging their strong semantic reasoning and generati…
Inference Cost Attacks for Retrieval-Augmented Large Language Models
Chengliang Liu, Liangbo Ning, Yujuan Ding +1
Retrieval-Augmented Generation (RAG)-enhanced LLM systems, while powerful, introduce substantial inference costs due to the inclusion of an extra multi-stage pipeline that dynamica…
Mixture-of-Experts Knowledge Graph Retrieval-Augmented Generation for Multi-Agent LLM-based Recommendation
Shijie Wang, Chengyi Liu, Yujuan Ding +4
Large language models (LLMs) have recently been adopted for recommendations due to their ability to understand user intent and item semantics. However, LLM-based recommender system…
Beyond Description: A Multimodal Agent Framework for Insightful Chart Summarization
Yuhang Bai, Yujuan Ding, Shanru Lin +1
Chart summarization is crucial for enhancing data accessibility and the efficient consumption of information. However, existing methods, including those with Multimodal Large Langu…
HV-Attack: Hierarchical Visual Attack for Multimodal Retrieval Augmented Generation
Linyin Luo, Yujuan Ding, Yunshan Ma +2
Advanced multimodal Retrieval-Augmented Generation (MRAG) techniques have been widely applied to enhance the capabilities of Large Multimodal Models (LMMs), but they also bring alo…
WebRec: Enhancing LLM-based Recommendations with Attention-guided RAG from Web
Zihuai Zhao, Yujuan Ding, Wenqi Fan +1
Recommender systems play a vital role in alleviating information overload and enriching users' online experience. In the era of large language models (LLMs), LLM-based recommender…
Diffusion Generative Recommendation with Continuous Tokens
Haohao Qu, Shanru Lin, Yujuan Ding +2
Recent advances in generative artificial intelligence, particularly large language models (LLMs), have opened new opportunities for enhancing recommender systems (RecSys). Most exi…
A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Models
Liangbo Ning, Ziran Liang, Zhuohang Jiang +8
With the advancement of web techniques, they have significantly revolutionized various aspects of people's lives. Despite the importance of the web, many tasks performed on it are…
ChartAdapter: Large Vision-Language Model for Chart Summarization
Peixin Xu, Yujuan Ding, Wenqi Fan
Chart summarization, which focuses on extracting key information from charts and interpreting it in natural language, is crucial for generating and delivering insights through effe…
A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models
Wenqi Fan, Yujuan Ding, Liangbo Ning +5
As one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can offer reliable and up-to-date external knowledge, providing huge convenience for numerous tas…