Papers › A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs

A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs

7 Jun 2022NeurIPS 2023 11arXiv:2206.04798archive 2025-07-28

Zhaocheng Zhu, Xinyu Yuan, Mikhail Galkin, Sophie Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang

Reasoning on large-scale knowledge graphs has been long dominated by embedding methods. While path-based methods possess the inductive capacity that embeddings lack, their scalability is limited by the exponential number of paths. Here we present A*Net, a scalable path-based method for knowledge graph reasoning. Inspired by the A* algorithm for shortest path problems, our A*Net learns a priority function to select important nodes and edges at each iteration, to reduce time and memory footprint for both training and inference. The ratio of selected nodes and edges can be specified to trade off between performance and efficiency. Experiments on both transductive and inductive knowledge graph reasoning benchmarks show that A*Net achieves competitive performance with existing state-of-the-art path-based methods, while merely visiting 10% nodes and 10% edges at each iteration. On a million-scale dataset ogbl-wikikg2, A*Net not only achieves a new state-of-the-art result, but also converges faster than embedding methods. A*Net is the first path-based method for knowledge graph reasoning at such scale.

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bincount DeepGraphLearning/AStarNet/reasoning/functional.py official repository unverified MIT (permissive) · 4efd55e35064eee0 · report
get_entity_types DeepGraphLearning/AStarNet/script/chat.py official repository unverified MIT (permissive) · 087b2ca22ed58ea1 · report
get_root_logger DeepGraphLearning/AStarNet/reasoning/util.py official repository unverified MIT (permissive) · 70a68fd646c6e4a7 · report
get_wikidata_id DeepGraphLearning/AStarNet/script/chat.py official repository unverified MIT (permissive) · 469d65c572e7ba76 · report
load_config DeepGraphLearning/AStarNet/reasoning/util.py official repository unverified MIT (permissive) · 30326895d5ac5a09 · report
multikey_argsort DeepGraphLearning/AStarNet/reasoning/functional.py official repository unverified MIT (permissive) · 3e66de0bc577cdf1 · report
variadic_topks DeepGraphLearning/AStarNet/reasoning/functional.py official repository unverified MIT (permissive) · ad69c1e9f5dc269f · report

Tasks

Knowledge Graphs

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Link Property Prediction ogbl-wikikg2 A*Net Ext. data No #11 of 30 Archive leaderboard report
Link Property Prediction ogbl-wikikg2 A*Net Number of params 6831201 #11 of 30 Archive leaderboard report
Link Property Prediction ogbl-wikikg2 A*Net Test MRR 0.6711 ± 0.0045 #11 of 30 Archive leaderboard report
Link Property Prediction ogbl-wikikg2 A*Net Validation MRR 0.6796 ± 0.0070 #11 of 30 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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