Yuxuan Jiang

Yuxuan Jiang is a Computer Science PhD student under Dr. Francis Ferraro at the University of Maryland, Baltimore County (UMBC).
His research centers on tool-integrated reasoning, LLM Memorization, and efficient large language models.

His ongoing projects include building large-scale reasoning benchmarks and studying how reasoning efficiency relates to model memory and inference balance.

Previously, Yuxuan earned his M.S. in Computer Science from New York University and B.A. in Information Systems from Beijing Language and Culture University.
He also interned at Xiaomi, where he worked on large-scale dialogue systems and commonsense reasoning integration, and at the National Language Resource Monitoring Center, where he led semantic role labeling and input-correction research.

He has authored several papers on large language model reasoning and evaluation, including works on memorization mitigation and reasoning-step compression.

Yuxuan has a strong background in deep learning, natural language processing, with experience in PyTorch, Hugging Face, TensorFlow, and cloud deployment (AWS / GCP).
He has also been recognized for his contributions to research on reasoning efficiency, skill-aware step pruning, and distilled reasoning models in recent ACL and EMNLP submissions.

Research Interests

        ✓ Tool-Integrated Reasoning
        ✓ Large Language Models Reasoning