Causal Learning in Question Quality Improvement. - Yichuan Li 001; Ruocheng Guo; Weiying Wang; Huan Liu 001 (Bench, 2019)

Graph Neural Networks with High-order Feature Interactions. - Kaize Ding; Yichuan Li 001; Jundong Li; Chenghao Liu; Huan Liu 001 (CoRR, 2019)

Toward A Multilingual and Multimodal Data Repository for COVID-19 Disinformation. - Yichuan Li 001; Bohan Jiang; Kai Shu; Huan Liu 001 (IEEE BigData, 2020)

Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics. - Kaize Ding; Kai Shu; Yichuan Li 001; Amrita Bhattacharjee; Huan Liu 001 (CIKM (Workshops), 2020)

IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data. - Ruocheng Guo; Jundong Li; Yichuan Li 001; K. Selçuk Candan; Adrienne Raglin; Huan Liu 001 (IJCAI, 2020)

Early Detection of Fake News with Multi-source Weak Social Supervision. - Kai Shu; Guoqing Zheng; Yichuan Li 001; Subhabrata Mukherjee; Ahmed Hassan Awadallah; Scott W. Ruston; Huan Liu 001 (ECML/PKDD (3), 2020)

Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News. - Kai Shu; Guoqing Zheng; Yichuan Li 001; Subhabrata Mukherjee; Ahmed Hassan Awadallah; Scott W. Ruston; Huan Liu 001 (CoRR, 2020)

MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 Disinformation. - Yichuan Li 001; Bohan Jiang; Kai Shu; Huan Liu 001 (CoRR, 2020)

Fact-Enhanced Synthetic News Generation. - Kai Shu; Yichuan Li 001; Kaize Ding; Huan Liu 001 (AAAI, 2021)

Multi-Source Domain Adaptation with Weak Supervision for Early Fake News Detection. - Yichuan Li 001; Kyumin Lee; Nima Kordzadeh; Brenton D. Faber; Cameron Fiddes; Elaine Chen; Kai Shu (IEEE BigData, 2021)

Reducing and Exploiting Data Augmentation Noise through Meta Reweighting Contrastive Learning for Text Classification. - Guanyi Mou; Yichuan Li 001; Kyumin Lee (IEEE BigData, 2021)

GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs. - Yichuan Li 001; Kaize Ding; Kyumin Lee (EMNLP (Findings), 2023)

KEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness. - Yichuan Li 001; Jialong Han; Kyumin Lee; Chengyuan Ma; Benjamin Z. Yao; Xiaohu Liu (EMNLP (Findings), 2023)

What Boosts Fake News Dissemination on Social Media? A Causal Inference View. - Yichuan Li 001; Kyumin Lee; Nima Kordzadeh; Ruocheng Guo (PAKDD (4), 2023)

KEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness. - Yichuan Li 001; Jialong Han; Kyumin Lee; Chengyuan Ma; Benjamin Z. Yao; Derek Liu (CoRR, 2023)

Empowering Large Language Models for Textual Data Augmentation. - Yichuan Li 001; Kaize Ding; Jianling Wang; Kyumin Lee (ACL (Findings), 2024)

Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning. - Zhengyu Hu; Yichuan Li 001; Zhengyu Chen 001; Jingang Wang; Han Liu; Kyumin Lee; Kaize Ding (EMNLP (Findings), 2024)

MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning. - Yichuan Li 001; Xiyao Ma; Sixing Lu; Kyumin Lee; Xiaohu Liu; Chenlei Guo (ICLR, 2024)

ALERT: An LLM-powered Benchmark for Automatic Evaluation of Recommendation Explanations. - Yichuan Li 001; Xinyang Zhang 002; Chenwei Zhang; Mao Li; Tianyi Liu; Pei Chen; Yifan Gao 001; Kyumin Lee; Kaize Ding; Zhengyang Wang; Zhihan Zhang 001; Jingbo Shang; et al. (NAACL (Long Papers), 2025)

FaithfulPersona: Balancing Faithfulness and Personalization in Code Explanations through Self-Critique. - Zhuang Luo; Yichuan Li 001; Zexing Xu; Kyumin Lee; S. Rasoul Etesami 001 (NAACL (Findings), 2025)

IHEval: Evaluating Language Models on Following the Instruction Hierarchy. - Zhihan Zhang 001; Shiyang Li; Zixuan Zhang; Xin Liu 039; Haoming Jiang; Xianfeng Tang; Yifan Gao 001; Zheng Li 018; Haodong Wang; Zhaoxuan Tan; Yichuan Li 001; Qingyu Yin; et al. (NAACL (Long Papers), 2025)

From Critique to Clarity: A Pathway to Faithful and Personalized Code Explanations with Large Language Models. - Zexing Xu; Zhuang Luo; Yichuan Li 001; Kyumin Lee; S. Rasoul Etesami 001 (CoRR, 2025)