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20242026
most citedOpportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research

10 citations · 11 across the 7 of their papers we have counts for

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cs.CL202610 cited

Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research

Tianyang Zhong, Zhenyuan Yang, Zhengliang Liu +11

Low-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity. Despite their significance, these languages face…

cs.CL2025

Evaluation of OpenAI o1: Opportunities and Challenges of AGI

Tianyang Zhong, Zhengliang Liu, Yi Pan +73

This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, includi…

cs.CL2025

E-Pruner: Towards Efficient, Economical, and Effective Layer Pruning for Large Language Models

Tao Yuan, Haoli Bai, Yinfei Pan +5

With the increasing size of large language models, layer pruning has gained increased attention as a hardware-friendly approach for model compression. However, existing layer pruni…

cs.CL2024

QueEn: A Large Language Model for Quechua-English Translation

Junhao Chen, Peng Shu, Yiwei Li +7

Recent studies show that large language models (LLMs) are powerful tools for working with natural language, bringing advances in many areas of computational linguistics. However, t…

cs.CL2024

Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translation

Peng Shu, Junhao Chen, Zhengliang Liu +13

Large Language Models (LLMs) have demonstrated remarkable success across a wide range of tasks and domains. However, their performance in low-resource language translation, particu…

cs.CL2024

Towards Next-Generation Medical Agent: How o1 is Reshaping Decision-Making in Medical Scenarios

Shaochen Xu, Yifan Zhou, Zhengliang Liu +19

Artificial Intelligence (AI) has become essential in modern healthcare, with large language models (LLMs) offering promising advances in clinical decision-making. Traditional model…