9 citations · 15 across the 6 of their papers we have counts for
6 papers
Human-Calibrated Automated Testing and Validation of Generative Language Models
Agus Sudjianto, Aijun Zhang, Srinivas Neppalli +2
This paper introduces a comprehensive framework for the evaluation and validation of generative language models (GLMs), with a focus on Retrieval-Augmented Generation (RAG) systems…
Towards a framework on tabular synthetic data generation: a minimalist approach: theory, use cases, and limitations
Yueyang Shen, Agus Sudjianto, Arun Prakash R +5
We propose and study a minimalist approach towards synthetic tabular data generation. The model consists of a minimalistic unsupervised SparsePCA encoder (with contingent clusterin…
Model Validation Practice in Banking: A Structured Approach for Predictive Models
Agus Sudjianto, Aijun Zhang
This paper presents a comprehensive overview of model validation practices and advancement in the banking industry based on the experience of managing Model Risk Management (MRM) s…
Automatic Generation of Behavioral Test Cases For Natural Language Processing Using Clustering and Prompting
Ying Li, Rahul Singh, Tarun Joshi +1
Recent work in behavioral testing for natural language processing (NLP) models, such as Checklist, is inspired by related paradigms in software engineering testing. They allow eval…
Interpretable Machine Learning based on Functional ANOVA Framework: Algorithms and Comparisons
Linwei Hu, Vijayan N. Nair, Agus Sudjianto +2
In the early days of machine learning (ML), the emphasis was on developing complex algorithms to achieve best predictive performance. To understand and explain the model results, o…
Enhancing Robustness of Gradient-Boosted Decision Trees through One-Hot Encoding and Regularization
Shijie Cui, Agus Sudjianto, Aijun Zhang +1
Gradient-boosted decision trees (GBDT) are widely used and highly effective machine learning approach for tabular data modeling. However, their complex structure may lead to low ro…