most citedRadiology-Llama2: Best-in-Class Large Language Model for Radiology

30 citations · 73 across the 7 of their papers we have counts for

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cs.CL20243 cited

Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning

Yiwei Li, Peiwen Yuan, Shaoxiong Feng +5

Self-consistency (SC) has been a widely used decoding strategy for chain-of-thought reasoning. Despite bringing significant performance improvements across a variety of multi-step…

cs.CL20231 cited

BatchEval: Towards Human-like Text Evaluation

Peiwen Yuan, Shaoxiong Feng, Yiwei Li +4

Significant progress has been made in automatic text evaluation with the introduction of large language models (LLMs) as evaluators. However, current sample-wise evaluation paradig…

cs.CL202312 cited

ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data

Tianyang Zhong, Wei Zhao, Yutong Zhang +39

Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels. However, complex and d…

cs.CL202318 cited

PolicyGPT: Automated Analysis of Privacy Policies with Large Language Models

Chenhao Tang, Zhengliang Liu, Chong Ma +8

Privacy policies serve as the primary conduit through which online service providers inform users about their data collection and usage procedures. However, in a bid to be comprehe…

cs.CL202330 cited

Radiology-Llama2: Best-in-Class Large Language Model for Radiology

Zhengliang Liu, Yiwei Li, Peng Shu +18

This paper introduces Radiology-Llama2, a large language model specialized for radiology through a process known as instruction tuning. Radiology-Llama2 is based on the Llama2 arch…

cs.CL20231 cited

Heterogeneous-Branch Collaborative Learning for Dialogue Generation

Yiwei Li, Shaoxiong Feng, Bin Sun +1

With the development of deep learning, advanced dialogue generation methods usually require a greater amount of computational resources. One promising approach to obtaining a high-…