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20222026
most citedA Customized Text Sanitization Mechanism with Differential Privacy

30 citations · 101 across the 45 of their papers we have counts for

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Showing 2025 · cs.IRShow all

6 papers · 2 filters

cs.IR2025

Parametric Retrieval-Augmented Generation using Latent Routing of LoRA Adapters

Zhan Su, Fengran Mo, Jinghan Zhang +3

Parametric Retrieval-Augmented Generation (PRAG) is a RAG approach that integrates external knowledge directly into model parameters using a LoRA adapter, aiming at reducing the in…

cs.IR2025

Boosting Data Utilization for Multilingual Dense Retrieval

Chao Huang, Fengran Mo, Yufeng Chen +5

Multilingual dense retrieval aims to retrieve relevant documents across different languages based on a unified retriever model. The challenge lies in aligning representations of di…

cs.IR2025

Adaptive Personalized Conversational Information Retrieval

Fengran Mo, Yuchen Hui, Yuxing Tian +5

Personalized conversational information retrieval (CIR) systems aim to satisfy users' complex information needs through multi-turn interactions by considering user profiles. Howeve…

cs.IR2025

ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrieval

Fengran Mo, Jinghan Zhang, Yuchen Hui +4

Conversational search aims to satisfy users' complex information needs via multiple-turn interactions. The key challenge lies in revealing real users' search intent from the contex…

cs.IR2025

Conversational Search: From Fundamentals to Frontiers in the LLM Era

Fengran Mo, Chuan Meng, Mohammad Aliannejadi +1

Conversational search enables multi-turn interactions between users and systems to fulfill users' complex information needs. During this interaction, the system should understand t…

cs.IR2025

FinSage: A Multi-aspect RAG System for Financial Filings Question Answering

Xinyu Wang, Jijun Chi, Zhenghan Tai +13

Leveraging large language models in real-world settings often entails a need to utilize domain-specific data and tools in order to follow the complex regulations that need to be fo…