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20242026
most citedUnmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation

89 citations · 148 across the 23 of their papers we have counts for

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Showing cs.AIShow all

6 papers · 1 filter

cs.AI2026

Agents' Last Exam

Yiyou Sun, Xinyang Han, Weichen Zhang +355

Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…

cs.AI2025

Developing Large Language Models for Clinical Research Using One Million Clinical Trials

Zifeng Wang, Jiacheng Lin, Qiao Jin +5

Developing artificial intelligence (AI) for clinical research requires a comprehensive data foundation that supports model training and rigorous evaluation. Here, we introduce Tria…

cs.AI2024

Beyond Multiple-Choice Accuracy: Real-World Challenges of Implementing Large Language Models in Healthcare

Yifan Yang, Qiao Jin, Qingqing Zhu +5

Large Language Models (LLMs) have gained significant attention in the medical domain for their human-level capabilities, leading to increased efforts to explore their potential in…

cs.AI2024★ 2 cited

Entry-level guide to the use of large language models for medical research

Qiao Jin, Nicholas Wan, Robert Leaman +20

Frontier large language models (LLMs), such as GPT-5, Claude 4.5, Gemini 3, Llama 4, and DeepSeek-R1, represent a transformative class of AI tools capable of revolutionizing variou…

cs.AI2024★ 5 cited

Adversarial Attacks on Large Language Models in Medicine

Yifan Yang, Qiao Jin, Furong Huang +1

The integration of Large Language Models (LLMs) into healthcare applications offers promising advancements in medical diagnostics, treatment recommendations, and patient care. Howe…

cs.AI2024★ 2 cited

GeneAgent: Self-verification Language Agent for Gene Set Knowledge Discovery using Domain Databases

Zhizheng Wang, Qiao Jin, Chih-Hsuan Wei +6

Gene set knowledge discovery is essential for advancing human functional genomics. Recent studies have shown promising performance by harnessing the power of Large Language Models…