Yangfeng Ji

University of Virginia — United States

Computer Science · Physical Sciences

28h-index4.0kcitations131works0.12yr avg
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Research Topics

Topic Modeling(87), Natural Language Processing Techniques(62), Speech and dialogue systems(19), Explainable Artificial Intelligence (XAI)(16), Adversarial Robustness in Machine Learning(15)

Publications131 total

Expert-Grounded Automatic Prompt Engineering for Extracting Lattice Constants of High-Entropy Alloys from Scientific Publications using Large Language Models
2025Open Access
Expert-Grounded Automatic Prompt Engineering for Extracting Lattice Constants of High-Entropy Alloys from Scientific Publications using Large Language Models
arXiv (Cornell University)·2025Open Access
Expert-Grounded Automatic Prompt Engineering for Extracting Lattice Constants of High-Entropy Alloys from Scientific Publications using Large Language Models
ArXiv.org·2025Open Access
Syntactic Blind Spots: How Misalignment Leads to LLMs Mathematical Errors
arXiv (Cornell University)·2025Open Access
IrrMap: A Large-Scale Comprehensive Dataset for Irrigation Method Mapping
2025Open Access
Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection
arXiv (Cornell University)·2025Open Access
CASE: Contrastive Activation for Saliency Estimation
arXiv (Cornell University)·2025Open Access
Monte Carlo Sampling for Analyzing In-Context Examples
arXiv (Cornell University)·2025Open Access
Unsupervised Concept Vector Extraction for Bias Control in LLMs
arXiv (Cornell University)·2025Open Access
In-Context Learning (and Unlearning) of Length Biases
arXiv (Cornell University)·2025Open Access
Syntactic Blind Spots: How Misalignment Leads to LLMs’ Mathematical Errors
2025· 1 citedOpen Access
Do Prevalent Bias Metrics Capture Allocational Harms from LLMs?
2025Open Access
Unsupervised Concept Vector Extraction for Bias Control in LLMs
2025Open Access
The Good, the Bad, and the Debatable: A Survey on the Impacts of Data for In-Context Learning
2025Open Access
Monte Carlo Sampling for Analyzing In-Context Examples
2025Open Access
A Comparative Study of Learning Paradigms in Large Language Models via Intrinsic Dimension
2025Open Access
Optimizing Latent Dimension Allocation in Hierarchical Vaes: Balancing Attenuation and Information Retention for Ood Detection
SSRN Electronic Journal·2025Open Access
In-Context Learning (and Unlearning) of Length Biases
2025Open Access
A Comparative Study of Learning Paradigms in Large Language Models via Intrinsic Dimension
arXiv (Cornell University)·2024Open Access
TPIE: Topology-Preserved Image Editing With Text Instructions
arXiv (Cornell University)·2024Open Access
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Frequent Co-authors

Jacob Eisenstein(12), Hanjie Chen(9), Noah A. Smith(6), Jianfeng Gao(5), Alessandro Sordoni(4), Michel Galley(4), Michael Auli(4), Chris Brockett(4), Margaret Mitchell(4), Bill Dolan(4), Chris Dyer(4), Trevor Cohn(4), Lingpeng Kong(4), Wanyu Du(4), Chenhao Tan(3), Antoine Bosselut(3), Wei Xu(3), Yejin Choi(3), Jian‐Yun Nie(2), Graham Neubig(2)