9 citations · 9 across the 4 of their papers we have counts for
19 papers
Is Conformal Factuality for RAG-based LLMs Robust? Novel Metrics and Systematic Insights
Yi Chen, Daiwei Chen, Sukrut Madhav Chikodikar +2
Large language models (LLMs) frequently hallucinate, limiting their reliability in knowledge-intensive applications. Retrieval-augmented generation (RAG) and conformal factuality h…
Why GRPO Needs Normalization: A Local-Curvature Perspective on Adaptive Gradients
Cheng Ge, Caitlyn Heqi Yin, Hao Liang +1
Reinforcement learning (RL) has become a key driver of language model reasoning. Among RL algorithms, Group Relative Policy Optimization (GRPO) is the de facto standard, avoiding t…
From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence
Tianyang Wang, Yunze Wang, Jun Zhou +16
Uncertainty quantification (UQ) is a critical aspect of artificial intelligence (AI) systems, particularly in high-risk domains such as healthcare, autonomous systems, and financia…
Deep Learning, Machine Learning, Advancing Big Data Analytics and Management
Weiche Hsieh, Ziqian Bi, Keyu Chen +23
Advancements in artificial intelligence, machine learning, and deep learning have catalyzed the transformation of big data analytics and management into pivotal domains for researc…
A Comprehensive Survey and Guide to Multimodal Large Language Models in Vision-Language Tasks
Chia Xin Liang, Pu Tian, Caitlyn Heqi Yin +7
This survey and application guide to multimodal large language models(MLLMs) explores the rapidly developing field of MLLMs, examining their architectures, applications, and impact…
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…