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Xuying Ning

Ph.D. in Computer Science · University of Illinois Urbana-Champaign

Hi! I am Xuying Ning (宁徐瑛). I am a CS PhD student at the University of Illinois Urbana-Champaign (UIUC), advised by Prof. Jingrui He, and I also closely work with Prof. Hanghang Tong. Prior to this, I received my B.Eng. in Artificial Intelligence from Xi'an Jiaotong University, where I was enrolled in the Honors Youth Program at the age of 15 and the Artificial Intelligence Experimental Class. I also spent time as a visiting student at Columbia University in 2022. I had the privilege of working with Prof. Nanning Zheng and Prof. Qinghua Zheng.

My goal is to build AI agents that are more capable and better aligned with human goals and values. Recently, I have been interested in how AI agents reason, act, and evolve in changing environments. I also explore better human–agent collaboration and more possibilities in omnimodal intelligence.

Selected Publications

Selected papers and preprints. See a fuller list on Google Scholar.

* denotes equal contribution.

2026
EvoHarness-RL: Learning Self-Evolving Runtime Harness for Long-Horizon LLM Agents
COLM 2026 LLA Workshop
Work in Progress

Xuying Ning, Dongqi Fu, Tianxin Wei, Hanqing Zeng, Yuanchen Bei, Bingxuan Li, Zihao Li, Qifan Wang, Xiang Shen, Yifan Wu, Jiayi Liu, Hong Li, Yinglong Xia, Xiangjun Fan, Hanghang Tong, Jingrui He

Key Insight: Optimizes agent harness coordination with reinforcement learning for sustained self-improvement on long-horizon tasks.

Paper

agent llm memory
Code as Agent Harness
arXiv 2026

Xuying Ning, Katherine Tieu, Dongqi Fu, Tianxin Wei, Zihao Li, Yuanchen Bei, Jiaru Zou, Mengting Ai, Zhining Liu, Ting-Wei Li, Lingjie Chen, Yanjun Zhao, Ke Yang, Bingxuan Li, Cheng Qian, Gaotang Li, Xiao Lin, Zhichen Zeng, Ruizhong Qiu, Sirui Chen, Yifan Sun, Xiyuan Yang, Ruida Wang, Rui Pan, Chenyuan Yang, Dylan Zhang, Liri Fang, Zikun Cui, Yang Cao, Pan Chen, Dorothy Sun, Ren Chen, Mahesh Srinivasan, Nipun Mathur, Yinglong Xia, Hong Li, Hong Yan, Pan Lu, Lingming Zhang, Tong Zhang, Hanghang Tong, Jingrui He

Key Insight: Treats executable code as a harness for agent deployment, evaluation, and improvement.

Paper Code

agent llm survey
MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chains
ICLR 2026 Oral (Top 1%)

Xuying Ning*, Dongqi Fu*, Tianxin Wei*, Mengting Ai, Jiaru Zou, Ting-Wei Li, Hanghang Tong, Yada Zhu, Hendrik Hamann, Jingrui He

Key Insight: Structured long reasoning chains for multimodal agentic search.

Paper Code

agentic search multimodal llm
Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory
arXiv 2025

Tianxin Wei, Noveen Sachdeva, Benjamin Coleman, Zhankui He, Yuarchen Bei, Xuying Ning, Mengting Ai, Yunzhe Li, Jingrui He, Ed H. Chi, Chi Wang, Shuo Chen, Fernando Pereira, Wang-Cheng Kang, Derek Zhiyuan Cheng

Key Insight: LLM agents that autonomously build and refine memory from experience at test time.

Paper Code

agent memory
Mem-Gallery: Benchmarking Multimodal Long-Term Conversational Memory for MLLM Agents
ACL 2026 Main

Yuanchen Bei, Tianxin Wei, Xuying Ning, Yanjun Zhao, Zhining Liu, Xiao Lin, Yada Zhu, Hendrik Hamann, Jingrui He, Hanghang Tong

Key Insight: Benchmark exposing MLLM agents' failure in long-term multimodal conversational memory.

Paper Code

agent multimodal memory
PaperMind: Benchmarking Agentic Reasoning and Critique over Scientific Papers in Multimodal LLMs
ACL 2026 Findings

Yanjun Zhao*, Tianxin Wei, Jiaru Zou, Xuying Ning, Yuanchen Bei, Lingjie Chen, Simmi Rana, Wendy H. Yang, Hanghang Tong, Jingrui He

Key Insight: Benchmark for evaluating multimodal LLM reasoning and critique over scientific papers.

Paper Code

agent multimodal
AdaFuse: Adaptive Ensemble Decoding with Test-Time Scaling for LLMs
ACL 2026 Main

Chengming Cui*, Tianxin Wei, Ziyi Chen, Ruizhong Qiu, Zhichen Zeng, Zhining Liu, Xuying Ning, Duo Zhou, Jingrui He

Key Insight: Fuses multiple LLM outputs adaptively at decode time via test-time scaling.

Paper Code

llm reasoning
CoFiRec: Coarse-to-Fine Tokenization for Generative Recommendation
RecSys 2026

Tianxin Wei*, Xuying Ning*, Xuxing Chen, Ruizhong Qiu, Yupeng Hou, Yan Xie, Shuang Yang, Zhigang Hua, Jingrui He

Key Insight: Hierarchical tokenization bridging semantics and collaboration for generative recommendation.

Paper Code

recommendation generative
2025
Graph4MM: Weaving Multimodal Learning with Structural Information
ICML 2025

Xuying Ning, Dongqi Fu, Tianxin Wei, Wujiang Xu, Jingrui He

Key Insight: Graph structure as inductive bias for richer multimodal representations.

Paper Code

multimodal graph
I²VAE: Interest Information Augmentation with Variational Regularizers for Cross-Domain Sequential Recommendation
UAI 2025

Xuying Ning, Wujiang Xu, Tianxin Wei, Xiaolei Liu

Key Insight: Variational interest augmentation for cross-domain sequential recommendation.

Paper Code

recommendation
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
EMNLP 2025 Main

Junyu Zhang, Runpei Dong, Han Wang, Xuying Ning, Haoran Geng, Peihao Li, Xialin He, Yutong Bai, Jitendra Malik, Saurabh Gupta, Huan Zhang

Key Insight: Modulates slow-to-fast reasoning at test time to improve both reasoning accuracy and efficiency.

Paper Code

llm reasoning
SLMRec: Empowering Small Language Models for Sequential Recommendation
ICLR 2025

Wujiang Xu, Qitian Wu, Zujie Liang, Jiaojiao Han, Xuying Ning, Wenfang Lin, Linxun Chen, Feng Wei, Yongfeng Zhang

Key Insight: Distills large language models into efficient small models for sequential recommendation.

Paper Code

recommendation llm

Xuying Ning

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