Yiyang Li

Yiyang Li

PhD Student

University of Notre Dame

About

My name is Yiyang (Ian) Li, a second-year Ph.D. student in the Department of Computer Science and Engineering at the University of Notre Dame. My advisor is Prof. Yanfang (Fanny) Ye. Before joining Notre Dame, I received my B.E. degree in Artificial Intelligence from Northeastern University (China) in 2024.

My research focuses on agentic AI systems and large foundation models, with the goal of enabling models to reason, act, and collaborate effectively in complex, real-world environments. I am particularly interested in agent system optimization, retrieval-augmented generation and knowledge-guided reasoning, as well as efficient large foundation models. For more details, please check my CV here.

News

2026-01

One paper is accepted to EACL 2026 Findings.

2025-10

We have released LLMs4ALL, an extensive survey on LLMs for research and applications in academic disciplines.

2025-05

NGQA is accepted to ACL 2025 main conference.

Selected Publications

LongDA: Benchmarking LLM Agents for Long-Document Data Analysis

LongDA: Benchmarking LLM Agents for Long-Document Data Analysis

Yiyang Li, Zheyuan Zhang, Tianyi Ma, Zehong Wang, Keerthiram Murugesan, Chuxu Zhang, Yanfang Ye

Preprint 2026

This paper introduces LongDA, a benchmark and agent framework for evaluating data analysis agents using complex, real-world datasets and documentation.

DOI
Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use

Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use

Yiyang Li, Zehong Wang, Zhengqing Yuan, Zheyuan Zhang, Keerthiram Murugesan, Chuxu Zhang, Yanfang Ye

EACL Findings 2026

This paper introduces LAMI, an interpretable graph-language model designed to detect illicit drug use among youth by modeling survey text to structured representations.

DOI
NGQA: a nutritional graph question answering benchmark for personalized health-aware nutritional reasoning

NGQA: a nutritional graph question answering benchmark for personalized health-aware nutritional reasoning

Zheyuan Zhang, Yiyang Li, Nhi Ha Lan Le, Zehong Wang, Tianyi Ma, Vincent Galassi, Keerthiram Murugesan, Nuno Moniz, Werner Geyer, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

ACL 2025

NGQA is a novel question answering benchmark designed to evaluate models' capabilities in personalized health-aware nutritional reasoning using knowledge graphs.

DOI

Teaching

Courses I have taught or assisted with.

Computer Security

2026 Spring

Teaching Assistant

UndergraduateCSE-40567

Introduction to Artificial Intelligence

2024 Fall

Teaching Assistant

UndergraduateCSE-30124