{"total":14,"rows":[{"id":"2403.01232","title":"Polynormer: Polynomial-Expressive Graph Transformer in Linear Time","created":"2024-03-02","cited_by_count":65,"area":null},{"id":"2502.14546","title":"Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks","created":"2025-02-20","cited_by_count":53,"area":null},{"id":"2405.19121","title":"Spatio-Spectral Graph Neural Networks","created":"2024-05-29","cited_by_count":17,"area":null},{"id":"2509.26476","title":"Regression Language Models for Code","created":"2025-09-30","cited_by_count":11,"area":null},{"id":"2407.20912","title":"What Are Good Positional Encodings for Directed Graphs?","created":"2024-07-30","cited_by_count":8,"area":null},{"id":"2506.16404","title":"Generating Directed Graphs with Dual Attention and Asymmetric Encoding","created":"2025-06-19","cited_by_count":3,"area":null},{"id":"2504.13266","title":"Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs","created":"2025-04-17","cited_by_count":2,"area":null},{"id":"2410.06460","title":"A Benchmark on Directed Graph Representation Learning in Hardware Designs","created":"2024-10-09","cited_by_count":1,"area":null},{"id":"2510.10209","title":"LOOPerSet: A Large-Scale Dataset for Data-Driven Polyhedral Compiler Optimization","created":"2025-10-11","cited_by_count":1,"area":null},{"id":"2605.29357","title":"PassNet: Scaling Large Language Models for Graph Compiler Pass Generation","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2403.16557","title":"Accelerating Federated Learning by Selecting Beneficial Herd of Local Gradients","created":"2024-03-25","cited_by_count":0,"area":null},{"id":"2405.16623","title":"Graph neural networks with configuration cross-attention for tensor compilers","created":"2024-05-26","cited_by_count":0,"area":null},{"id":"2506.08618","title":"HSG-12M: A Large-Scale Benchmark of Spatial Multigraphs from the Energy Spectra of Non-Hermitian Crystals","created":"2025-06-10","cited_by_count":0,"area":null},{"id":"2608.21555","title":"Tensor Seeks Layout: Formalizing Layout Selection for ML Compilers","created":"2026-08-21","cited_by_count":0,"area":null}],"next_cursor":null}