2 citations · 2 across the 4 of their papers we have counts for
6 papers
Lexical Perturbations Disrupt LLM Reasoning: An Empirical Study of Attention Diversion
Jiaqian Zhu, Yang Zhang, Junhua Ding +1
Large Language Models (LLMs) achieve strong reasoning performance, but their robustness to realistic lexical corruption remains poorly understood. We evaluate four open-weight inst…
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…
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,…
Efficient Fine-Tuning of Large Language Models for Automated Medical Documentation
Hui Yi Leong, Yi Fan Gao, Ji Shuai +2
Scientific research indicates that for every hour spent in direct patient care, physicians spend nearly two additional hours on administrative tasks, particularly on electronic hea…