On Representing Mixed-Integer Linear Programs by Graph Neural Networks
Ziang Chen, Jialin Liu, Xinshang Wang, W. Yin
2/12/2026
No official code found. Best implementation: liujl11git/GNN-MILP (60 stars, MIT, last commit 2023-08-11).
No official code found. Best implementation: liujl11git/GNN-MILP (60 stars, MIT, last commit 2023-08-11).
Size-Generalizable RNA Structure Evaluation by Exploring Hierarchical Geometries
Positive-Unlabeled Learning by Latent Group-Aware Meta Disambiguation
Sample-Efficient Quality-Diversity by Cooperative Coevolution
Scaling Long Context Training Data by Long-Distance Referrals
HShare: Fast LLM Decoding by Hierarchical Key-Value Sharing
Rethinking Visual Reconstruction: Experience-Based Content Completion Guided by Visual Cues
@article{chen2026representing,
title = {On Representing Mixed-Integer Linear Programs by Graph Neural Networks},
author = {Ziang Chen and Jialin Liu and Xinshang Wang and W. Yin},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:078fc54e3311e18d2e407e927192760e2bb67ae5},
journal = {ICLR 2023 2023}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/078fc54e3311e18d2e407e927192760e2bb67ae5)