6 citations · 11 across the 9 of their papers we have counts for
11 papers
Dissecting Neuro-Symbolic Quality Assurance for Synthetic Oncology Data Generation
Laxmigayathri Challa, Yuhan Zhou, Ana Cleveland +1
Synthetic clinical data generation with large language models addresses the scarcity that limits cancer staging research, but oncology hallucinations are categorically harmful: one…
MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation
Haoxuan Zhang, Ruochi Li, Yang Zhang +4
The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Model and Data Cards is not scal…
LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation
Huyen Nguyen, Haoxuan Zhang, Yang Zhang +2
Reliable evaluation of large language model (LLM)-generated summaries remains an open challenge, particularly across heterogeneous domains and document lengths. We conduct a compre…
LongSumEval: Question-Answering Based Evaluation and Feedback-Driven Refinement for Long Document Summarization
Huyen Nguyen, Haoxuan Zhang, Yang Zhang +2
Evaluating long document summaries remains the primary bottleneck in summarization research. Existing metrics correlate weakly with human judgments and produce aggregate scores wit…
RoTRAG: Rule of Thumb Reasoning for Conversation Harm Detection with Retrieval-Augmented Generation
Juhyeon Lee, Wonduk Seo, Junseo Koh +3
Detecting harmful content in multi turn dialogue requires reasoning over the full conversational context rather than isolated utterances. However, most existing methods rely mainly…
AdaQE-CG: Adaptive Query Expansion for Web-Scale Generative AI Model and Data Card Generation
Haoxuan Zhang, Ruochi Li, Zhenni Liang +7
Transparent and standardized documentation is essential for building trustworthy generative AI (GAI) systems. However, existing automated methods for generating model and data card…
ReviewGuard: Enhancing Deficient Peer Review Detection via LLM-Driven Data Augmentation
Haoxuan Zhang, Ruochi Li, Sarthak Shrestha +6
Peer review serves as the gatekeeper of science, yet the surge in submissions and widespread adoption of large language models (LLMs) in scholarly evaluation present unprecedented…
Unveiling the Merits and Defects of LLMs in Automatic Review Generation for Scientific Papers
Ruochi Li, Haoxuan Zhang, Edward Gehringer +3
The surge in scientific submissions has placed increasing strain on the traditional peer-review process, prompting the exploration of large language models (LLMs) for automated rev…
Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator
Haoxuan Zhang, Ruochi Li, Yang Zhang +4
Large language models (LLMs) are increasingly used in scientific research and discovery, supporting tasks ranging from literature retrieval and synthesis to hypothesis generation,…
A Comparative Study of Quality Evaluation Methods for Text Summarization
Huyen Nguyen, Haihua Chen, Lavanya Pobbathi +1
Evaluating text summarization has been a challenging task in natural language processing (NLP). Automatic metrics which heavily rely on reference summaries are not suitable in many…
A Survey on Data Quality Dimensions and Tools for Machine Learning
Yuhan Zhou, Fengjiao Tu, Kewei Sha +2
Machine learning (ML) technologies have become substantial in practically all aspects of our society, and data quality (DQ) is critical for the performance, fairness, robustness, s…