most citedFrom Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence

9 citations · 20 across the 9 of their papers we have counts for

collaborators
Showing cs.CLShow all

8 papers · 1 filter

cs.CL20251 cited

Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models

Junjie Yang, Junhao Song, Xudong Han +9

Knowledge distillation (KD) is a technique for transferring knowledge from complex teacher models to simpler student models, significantly enhancing model efficiency and accuracy.…

cs.CL20246 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…

cs.CL2024

Deep Learning and Machine Learning -- Natural Language Processing: From Theory to Application

Keyu Chen, Cheng Fei, Ziqian Bi +23

With a focus on natural language processing (NLP) and the role of large language models (LLMs), we explore the intersection of machine learning, deep learning, and artificial intel…

cs.CL20244 cited

Large Language Model Benchmarks in Medical Tasks

Lawrence K. Q. Yan, Qian Niu, Ming Li +16

With the increasing application of large language models (LLMs) in the medical domain, evaluating these models' performance using benchmark datasets has become crucial. This paper…

cs.CL20241 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.CL2024

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…