Weikai Li

According to our database, Weikai Li authored at least 13 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Choosing How to Remember: Adaptive Memory Structures for LLM Agents.

Mingfei Lu, Mengjia Wu, Feng Liu, Jiawei Xu, Weikai Li, Haoyang Wang, Zhengdong Hu, Ying Ding, Yizhou Sun, Jie Lu, Yi Zhang

CoRR, February, 2026

Report for NSF Workshop on AI for Electronic Design Automation.

Deming Chen, Vijay Ganesh, Weikai Li, Yingyan Celine Lin, Yong Liu, Subhasish Mitra, David Z. Pan, Ruchir Puri, Jason Cong, Yizhou Sun

CoRR, January, 2026

From Newborn to Impact: Bias-Aware Citation Prediction.

Mingfei Lu, Mengjia Wu, Jiawei Xu, Weikai Li, Feng Liu, Ying Ding, Yizhou Sun, Jie Lu, Yi Zhang

Proceedings of the ACM Web Conference 2026, 2026

2025

A Multimodal LLM Approach for Visual Question Answering on Multiparametric 3D Brain MRI.

Arvind Murari Vepa, Yannan Yu, Jingru Gan, Anthony Cuturrufo, Weikai Li, Wei Wang, Fabien Scalzo, Yizhou Sun

CoRR, September, 2025

Iceberg: Enhancing HLS Modeling with Synthetic Data.

Zijian Ding, Tung Nguyen, Weikai Li, Aditya Grover, Yizhou Sun, Jason Cong

CoRR, July, 2025

How Post-Training Reshapes LLMs: A Mechanistic View on Knowledge, Truthfulness, Refusal, and Confidence.

Hongzhe Du, Weikai Li, Min Cai, Karim Saraipour, Zimin Zhang, Himabindu Lakkaraju, Yizhou Sun, Shichang Zhang

CoRR, April, 2025

Hierarchical Mixture of Experts: Generalizable Learning for High-Level Synthesis.

Weikai Li, Ding Wang, Zijian Ding, Atefeh Sohrabizadeh, Zongyue Qin, Jason Cong, Yizhou Sun

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Fast Inference of Removal-Based Node Influence.

Weikai Li, Zhiping Xiao, Xiao Luo, Yizhou Sun

Proceedings of the ACM on Web Conference 2024, 2024

Learning to Compare Hardware Designs for High-Level Synthesis.

Yunsheng Bai, Atefeh Sohrabizadeh, Zijian Ding, Rongjian Liang, Weikai Li, Ding Wang, Haoxing Ren, Yizhou Sun, Jason Cong

Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD, 2024

KoLA: Carefully Benchmarking World Knowledge of Large Language Models.

Jifan Yu, Xiaozhi Wang, Shangqing Tu, Shulin Cao, Daniel Zhang-Li, Xin Lv, Hao Peng, Zijun Yao, Xiaohan Zhang, Hanming Li, Chunyang Li, Zheyuan Zhang, Yushi Bai, Yantao Liu, Amy Xin, Kaifeng Yun, Linlu Gong, Nianyi Lin, Jianhui Chen, Zhili Wu, Yunjia Qi, Weikai Li, Yong Guan, Kaisheng Zeng, Ji Qi, Hailong Jin, Jinxin Liu, Yu Gu, Yuan Yao, Ning Ding, Lei Hou, Zhiyuan Liu, Bin Xu, Jie Tang, Juanzi Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Efficient Task Transfer for HLS DSE.

Zijian Ding, Atefeh Sohrabizadeh, Weikai Li, Zongyue Qin, Yizhou Sun, Jason Cong

Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, 2024

2023

When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks.

Hao Peng, Xiaozhi Wang, Jianhui Chen, Weikai Li, Yunjia Qi, Zimu Wang, Zhili Wu, Kaisheng Zeng, Bin Xu, Lei Hou, Juanzi Li

CoRR, 2023

2022

Rethinking the Setting of Semi-supervised Learning on Graphs.

Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, Jie Tang

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022