Yichuan Li

31 papers A* 3B 1Journal 13Unranked 14
YearRankTypeTitle / Venue / Authors
2025 — conf
ALERT: An LLM-powered Benchmark for Automatic Evaluation of Recommendation Explanations.
NAACL (Long Papers)
Yichuan Li, Xinyang Zhang, Chenwei Zhang, Mao Li, Tianyi Liu, Pei Chen, Yifan Gao, Kyumin Lee, Kaize Ding, Zhengyang Wang, Zhihan Zhang, Jingbo Shang, Xian Li, Trishul Chilimbi
2025 — conf
FaithfulPersona: Balancing Faithfulness and Personalization in Code Explanations through Self-Critique.
NAACL (Findings)
Zhuang Luo, Yichuan Li, Zexing Xu, Kyumin Lee, S. Rasoul Etesami
2025 J jnl
From Critique to Clarity: A Pathway to Faithful and Personalized Code Explanations with Large Language Models.
CoRR
Zexing Xu, Zhuang Luo, Yichuan Li, Kyumin Lee, S. Rasoul Etesami
2025 — conf
IHEval: Evaluating Language Models on Following the Instruction Hierarchy.
NAACL (Long Papers)
Zhihan Zhang, Shiyang Li, Zixuan Zhang, Xin Liu, Haoming Jiang, Xianfeng Tang, Yifan Gao, Zheng Li, Haodong Wang, Zhaoxuan Tan, Yichuan Li, Qingyu Yin, Bing Yin, Meng Jiang
2025 J jnl
IHEval: Evaluating Language Models on Following the Instruction Hierarchy.
CoRR
Zhihan Zhang, Shiyang Li, Zixuan Zhang, Xin Liu, Haoming Jiang, Xianfeng Tang, Yifan Gao, Zheng Li, Haodong Wang, Zhaoxuan Tan, Yichuan Li, Qingyu Yin, Bing Yin, Meng Jiang
2025 B conf
LLM Profiling and Fine-Tuning with Limited Neighbor Information for Node Classification on Text-Attributed Graphs.
IEEE Big Data
Xinyi Fang, Kyumin Lee, Yichuan Li
2024 — conf
Empowering Large Language Models for Textual Data Augmentation.
ACL (Findings)
Yichuan Li, Kaize Ding, Jianling Wang, Kyumin Lee
2024 J jnl
Empowering Large Language Models for Textual Data Augmentation.
CoRR
Yichuan Li, Kaize Ding, Jianling Wang, Kyumin Lee
2024 — conf
Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning.
EMNLP (Findings)
Zhengyu Hu, Yichuan Li, Zhengyu Chen, Jingang Wang, Han Liu, Kyumin Lee, Kaize Ding
2024 J jnl
Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning.
CoRR
Zhengyu Hu, Yichuan Li, Zhengyu Chen, Jingang Wang, Han Liu, Kyumin Lee, Kaize Ding
2024 A* conf
MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning.
ICLR
Yichuan Li, Xiyao Ma, Sixing Lu, Kyumin Lee, Xiaohu Liu, Chenlei Guo
2024 J jnl
MEND: Meta dEmonstratioN Distillation for Efficient and Effective In-Context Learning.
CoRR
Yichuan Li, Xiyao Ma, Sixing Lu, Kyumin Lee, Xiaohu Liu, Chenlei Guo
2024 J jnl
Reducing and Exploiting Data Augmentation Noise through Meta Reweighting Contrastive Learning for Text Classification.
CoRR
Guanyi Mou, Yichuan Li, Kyumin Lee
2023 — conf
GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs.
EMNLP (Findings)
Yichuan Li, Kaize Ding, Kyumin Lee
2023 J jnl
GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs.
CoRR
Yichuan Li, Kaize Ding, Kyumin Lee
2023 — conf
KEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness.
EMNLP (Findings)
Yichuan Li, Jialong Han, Kyumin Lee, Chengyuan Ma, Benjamin Z. Yao, Xiaohu Liu
2023 J jnl
KEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness.
CoRR
Yichuan Li, Jialong Han, Kyumin Lee, Chengyuan Ma, Benjamin Z. Yao, Derek Liu
2023 — conf
What Boosts Fake News Dissemination on Social Media? A Causal Inference View.
PAKDD (4)
Yichuan Li, Kyumin Lee, Nima Kordzadeh, Ruocheng Guo
2021 A* conf
Fact-Enhanced Synthetic News Generation.
AAAI
Kai Shu, Yichuan Li, Kaize Ding, Huan Liu
2021 — conf
Multi-Source Domain Adaptation with Weak Supervision for Early Fake News Detection.
IEEE BigData
Yichuan Li, Kyumin Lee, Nima Kordzadeh, Brenton D. Faber, Cameron Fiddes, Elaine Chen, Kai Shu
2021 — conf
Reducing and Exploiting Data Augmentation Noise through Meta Reweighting Contrastive Learning for Text Classification.
IEEE BigData
Guanyi Mou, Yichuan Li, Kyumin Lee
2020 — conf
Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics.
CIKM (Workshops)
Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, Huan Liu
2020 J jnl
Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics.
CoRR
Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, Huan Liu
2020 — conf
Early Detection of Fake News with Multi-source Weak Social Supervision.
ECML/PKDD (3)
Kai Shu, Guoqing Zheng, Yichuan Li, Subhabrata Mukherjee, Ahmed Hassan Awadallah, Scott W. Ruston, Huan Liu
2020 J jnl
Fact-Enhanced Synthetic News Generation.
CoRR
Kai Shu, Yichuan Li, Kaize Ding, Huan Liu
2020 A* conf
IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data.
IJCAI
Ruocheng Guo, Jundong Li, Yichuan Li, K. Selçuk Candan, Adrienne Raglin, Huan Liu
2020 J jnl
Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News.
CoRR
Kai Shu, Guoqing Zheng, Yichuan Li, Subhabrata Mukherjee, Ahmed Hassan Awadallah, Scott W. Ruston, Huan Liu
2020 J jnl
MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 Disinformation.
CoRR
Yichuan Li, Bohan Jiang, Kai Shu, Huan Liu
2020 — conf
Toward A Multilingual and Multimodal Data Repository for COVID-19 Disinformation.
IEEE BigData
Yichuan Li, Bohan Jiang, Kai Shu, Huan Liu
2019 — conf
Causal Learning in Question Quality Improvement.
Bench
Yichuan Li, Ruocheng Guo, Weiying Wang, Huan Liu
2019 J jnl
Graph Neural Networks with High-order Feature Interactions.
CoRR
Kaize Ding, Yichuan Li, Jundong Li, Chenghao Liu, Huan Liu