9 citations · 10 across the 7 of their papers we have counts for
7 papers
Zeta: Dual Whitening for Matrix Optimization via Coordinate-Adaptive Preconditioning
Kaiwen Chen, Shuhai Zhang, Zimo Liu +7
Large-scale neural network training increasingly relies on matrix-aware optimizers that exploit the structure of weight parameters beyond element-wise adaptation. However, existing…
Navigating the Shift: A Comparative Analysis of Web Search and Generative AI Response Generation
Mahe Chen, Xiaoxuan Wang, Kaiwen Chen +1
The rise of generative AI as a primary information source presents a paradigm shift from traditional web search. This paper presents a large-scale empirical study quantifying the f…
Relational Deep Dive: Error-Aware Queries Over Unstructured Data
Daren Chao, Kaiwen Chen, Naiqing Guan +1
Unstructured data is pervasive, but analytical queries demand structured representations, creating a significant extraction challenge. Existing methods like RAG lack schema awarene…
Generative Engine Optimization: How to Dominate AI Search
Mahe Chen, Xiaoxuan Wang, Kaiwen Chen +1
The rapid adoption of generative AI-powered search engines like ChatGPT, Perplexity, and Gemini is fundamentally reshaping information retrieval, moving from traditional ranked lis…
Reliable Text-to-SQL with Adaptive Abstention
Kaiwen Chen, Yueting Chen, Xiaohui Yu +1
Large language models (LLMs) have revolutionized natural language interfaces for databases, particularly in text-to-SQL conversion. However, current approaches often generate unrel…
AXOLOTL: Fairness through Assisted Self-Debiasing of Large Language Model Outputs
Sana Ebrahimi, Kaiwen Chen, Abolfazl Asudeh +2
Pre-trained Large Language Models (LLMs) have significantly advanced natural language processing capabilities but are susceptible to biases present in their training data, leading…
Can Large Language Models Design Accurate Label Functions?
Naiqing Guan, Kaiwen Chen, Nick Koudas
Programmatic weak supervision methodologies facilitate the expedited labeling of extensive datasets through the use of label functions (LFs) that encapsulate heuristic data sources…