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20232026
most citedRetrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

13 citations · 44 across the 37 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CL2024★ 2 cited

TableRAG: Million-Token Table Understanding with Language Models

Si-An Chen, Lesly Miculicich, Julian Martin Eisenschlos +7

Recent advancements in language models (LMs) have notably enhanced their ability to reason with tabular data, primarily through program-aided mechanisms that manipulate and analyze…

cs.CL2024★ 13 cited

Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

Siyun Zhao, Yuqing Yang, Zilong Wang +3

Large language models (LLMs) augmented with external data have demonstrated remarkable capabilities in completing real-world tasks. Techniques for integrating external data into LL…

cs.CR2024

EnJa: Ensemble Jailbreak on Large Language Models

Jiahao Zhang, Zilong Wang, Ruofan Wang +2

As Large Language Models (LLMs) are increasingly being deployed in safety-critical applications, their vulnerability to potential jailbreaks -- malicious prompts that can disable t…

cs.CL2024

OfficeBench: Benchmarking Language Agents across Multiple Applications for Office Automation

Zilong Wang, Yuedong Cui, Li Zhong +4

Office automation significantly enhances human productivity by automatically finishing routine tasks in the workflow. Beyond the basic information extraction studied in much of the…

cs.CL2024

Position Engineering: Boosting Large Language Models through Positional Information Manipulation

Zhiyuan He, Huiqiang Jiang, Zilong Wang +3

The performance of large language models (LLMs) is significantly influenced by the quality of the prompts provided. In response, researchers have developed enormous prompt engineer…

cs.CL2024★ 5 cited

LLM-RadJudge: Achieving Radiologist-Level Evaluation for X-Ray Report Generation

Zilong Wang, Xufang Luo, Xinyang Jiang +2

Evaluating generated radiology reports is crucial for the development of radiology AI, but existing metrics fail to reflect the task's clinical requirements. This study proposes a…

cs.AI2024

The Application of ChatGPT in Responding to Questions Related to the Boston Bowel Preparation Scale

Xiaoqiang Liu, Yubin Wang, Zicheng Huang +8

Background: Colonoscopy, a crucial diagnostic tool in gastroenterology, depends heavily on superior bowel preparation. ChatGPT, a large language model with emergent intelligence wh…