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20242026
most citedFrom Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models

5 citations · 25 across the 21 of their papers we have counts for

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cs.CL2025

47B Mixture-of-Experts Beats 671B Dense Models on Chinese Medical Examinations

Chiung-Yi Tseng, Danyang Zhang, Tianyang Wang +8

The rapid advancement of large language models(LLMs) has prompted significant interest in their potential applications in medical domains. This paper presents a comprehensive bench…

cs.CL2025

Exploring Efficiency Frontiers of Thinking Budget in Medical Reasoning: Scaling Laws between Computational Resources and Reasoning Quality

Ziqian Bi, Lu Chen, Junhao Song +15

This study presents the first comprehensive evaluation of thinking budget mechanisms in medical reasoning tasks, revealing fundamental scaling laws between computational resources…

cs.CL2025

Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Object-Oriented Programming

Tianyang Wang, Ziqian Bi, Keyu Chen +12

Object-Oriented Programming (OOP) has become a crucial paradigm for managing the growing complexity of modern software systems, particularly in fields like machine learning, deep l…

cs.CL2025

Is GPT-OSS Good? A Comprehensive Evaluation of OpenAI's Latest Open Source Models

Ziqian Bi, Keyu Chen, Chiung-Yi Tseng +9

In August 2025, OpenAI released GPT-OSS models, its first open weight large language models since GPT-2 in 2019, comprising two mixture of experts architectures with 120B and 20B p…

cs.CL20251 cited

Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Unveiling AI's Potential Through Tools, Techniques, and Applications

Pohsun Feng, Ziqian Bi, Yizhu Wen +14

Artificial intelligence (AI), machine learning, and deep learning have become transformative forces in big data analytics and management, enabling groundbreaking advancements acros…

cs.CL20255 cited

From Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models

Charles Zhang, Benji Peng, Xintian Sun +14

Word embeddings and language models have transformed natural language processing (NLP) by facilitating the representation of linguistic elements in continuous vector spaces. This r…