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After Retrieval, Before Generation: Enhancing the Trustworthiness of Large Language Models in Retrieval-Augmented Generation
v1v2 (latest)

After Retrieval, Before Generation: Enhancing the Trustworthiness of Large Language Models in Retrieval-Augmented Generation

21 May 2025
Xinbang Dai
Huikang Hu
Yuncheng Hua
Jiaqi Li
Yongrui Chen
Rihui Jin
Nan Hu
Guilin Qi
    RALM3DV
ArXiv (abs)PDFHTMLGithub (1★)

Papers citing "After Retrieval, Before Generation: Enhancing the Trustworthiness of Large Language Models in Retrieval-Augmented Generation"

3 / 3 papers shown
Deep Research: A Survey of Autonomous Research Agents
Deep Research: A Survey of Autonomous Research Agents
Wenlin Zhang
Xiaopeng Li
Yingyi Zhang
Pengyue Jia
Yichao Wang
Huifeng Guo
Yong Liu
Xiangyu Zhao
LLMAG
104
11
0
18 Aug 2025
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to RefuseInternational Conference on Learning Representations (ICLR), 2024
Maojia Song
Shang Hong Sim
Rishabh Bhardwaj
Hai Leong Chieu
Navonil Majumder
Soujanya Poria
558
27
0
17 Sep 2024
Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting
Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting
Zilong Wang
Zifeng Wang
Long Le
Huaixiu Steven Zheng
Swaroop Mishra
...
Anush Mattapalli
Ankur Taly
Jingbo Shang
Zifeng Wang
Tomas Pfister
RALM
318
73
0
11 Jul 2024
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