Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift | Paper Citation Record

Observation 6ee7aefa-e604-4b28-8133-dd19da9242a5 · outbound

This paper cites Dbpedia: A nucleus for a web of open data,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Dbpedia: A nucleus for a web of open data,

Reference 1

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Observation dffad088-4618-4210-a3ad-f10e46907acf · outbound

This paper cites Yago: a core of semantic knowledge,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Yago: a core of semantic knowledge,

Reference 2

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This paper cites Hkgb: an inclusive, extensible, intelligent, semi- auto-constructed knowledge graph framework for healthcare with clinicians’ expertise incorporated,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Hkgb: an inclusive, extensible, intelligent, semi- auto-constructed knowledge graph framework for healthcare with clinicians’ expertise incorporated,

Reference 3

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Observation c9bd7697-a2ec-47ee-9dd6-66af16acc7d3 · outbound

This paper cites Kgat: Knowledge graph attention network for recommendation,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Kgat: Knowledge graph attention network for recommendation,

Reference 4

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Observation 0ff36f2c-e858-4ee8-8fc2-2392bca09656 · outbound

This paper cites Relational learning analysis of social politics using knowledge graph embedding,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Relational learning analysis of social politics using knowledge graph embedding,

Reference 5

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Observation b1ae3cb2-3d48-46d2-8e8b-ce9b23016219 · outbound

This paper cites A comprehensive overview of knowledge graph completion,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift A comprehensive overview of knowledge graph completion,

Reference 6

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Observation 9c7133c8-2804-488d-bc9d-1ec8c3986130 · outbound

This paper cites A review: Knowledge reasoning over knowledge graph,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift A review: Knowledge reasoning over knowledge graph,

Reference 7

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Observation 2192f226-938a-4736-820b-694caa6f6d99 · outbound

This paper cites A survey on knowl- edge graph embedding: Approaches, applications and bench- marks,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift A survey on knowl- edge graph embedding: Approaches, applications and bench- marks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:56.043159Z

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Observation 61ec0607-e2cb-4cc8-973c-f37759d5415a · outbound

This paper cites Differentiable learning of logical rules for knowledge base reasoning,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Differentiable learning of logical rules for knowledge base reasoning,

Reference 9

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Observation cf39f5ee-d766-43f6-9faa-71b57794cb1d · outbound

This paper cites Sparsity and noise: Where knowledge graph embeddings fall short,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Sparsity and noise: Where knowledge graph embeddings fall short,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:55.578590Z

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Observation 2a2946c5-6f60-40f5-a799-be6025232133 · outbound

This paper cites From local structures to size generalization in graph neural networks,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift From local structures to size generalization in graph neural networks,

Reference 11

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Observation 083b2ede-d9e3-4800-9aa6-353a33984bd6 · outbound

This paper cites Size-invariant graph representations for graph classification extrapolations,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Size-invariant graph representations for graph classification extrapolations,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:55.154969Z

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Observation 7cc31c97-169a-40c7-b534-905a35d8ba84 · outbound

This paper cites Logical rule learning,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Logical rule learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:54.967133Z

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Observation 5aa6c712-bab8-449f-9052-00f24c9f3469 · outbound

This paper cites Ood-gnn: Out-of- distribution generalized graph neural network,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Ood-gnn: Out-of- distribution generalized graph neural network,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:54.749676Z

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Observation 0374e134-a2ea-4748-a021-96f71487f888 · outbound

This paper cites Rnnlogic: Learning logic rules for reasoning on knowledge graphs,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Rnnlogic: Learning logic rules for reasoning on knowledge graphs,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:54.693784Z

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Observation ffea885d-e642-4e71-bb27-c1eedb11d429 · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 16

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Observation 88b84502-c750-4994-82a1-0dbcf7e58bc5 · outbound

This paper cites Pretrained Transformers Improve Out-of-Distribution Robustness.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Pretrained Transformers Improve Out-of-Distribution Robustness

Reference 17

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Observation ce0029f8-b1e9-4cd9-9d2d-24424667c354 · outbound

This paper cites Deep stable learning for out-of-distribution generalization,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Deep stable learning for out-of-distribution generalization,

Reference 18

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Observation 89e20911-dcad-4861-8153-5406a362e8ba · outbound

This paper cites Rlogic: Recursive logical rule learning from knowledge graphs,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Rlogic: Recursive logical rule learning from knowledge graphs,

Reference 19

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Observation e4f29279-3657-47ea-b7b6-5e503efab8ce · outbound

This paper cites The mean and variance of the distribution of shortest path lengths of random regular graphs,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift The mean and variance of the distribution of shortest path lengths of random regular graphs,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:54.390198Z

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Observation a708f85f-3254-4a6d-a280-c99b900a3f69 · outbound

This paper cites Translating embeddings for modeling multi- relational data,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Translating embeddings for modeling multi- relational data,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:54.243071Z

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Observation 513eb61f-a40e-4da9-a4c2-bc6fb649c557 · outbound

This paper cites Knowledge graph embedding by translating on hyperplanes,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Knowledge graph embedding by translating on hyperplanes,

Reference 22

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Observation e2e7b553-0f91-4d84-a83f-e5a7183d022c · outbound

This paper cites Learning entity and relation embeddings for knowledge graph completion,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Learning entity and relation embeddings for knowledge graph completion,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:54.049631Z

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Observation 565d3b62-d47e-45e5-92ba-7dedd69c6d21 · outbound

This paper cites RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

Reference 24

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Observation 023807c5-6d42-468a-b11b-31d7edc05e4b · outbound

This paper cites A three-way model for collective learning on multi-relational data.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift A three-way model for collective learning on multi-relational data

Reference 25

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T19:39:53.783325Z

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This paper cites Embedding Entities and Relations for Learning and Inference in Knowledge Bases.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Embedding Entities and Relations for Learning and Inference in Knowledge Bases

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T19:39:42.394591Z

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Observation 6559f0a5-8ccc-40a3-a4e6-1677d81fda62 · outbound

This paper cites Complex embeddings for simple link prediction,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Complex embeddings for simple link prediction,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:53.693269Z

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Observation f65556de-5274-45e3-a978-3a78e9b7b404 · outbound

This paper cites Modeling relational data with graph convolu- tional networks,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Modeling relational data with graph convolu- tional networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:53.555328Z

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Observation d23ab742-6c4b-4afa-8f95-64b3564d50ae · outbound

This paper cites Robust embedding with multi-level structures for link prediction.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Robust embedding with multi-level structures for link prediction

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:53.465503Z

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Observation 81c21e55-7a58-431c-abd9-61ed47e93532 · outbound

This paper cites Composition- based multi-relational graph convolutional networks,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Composition- based multi-relational graph convolutional networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:53.337612Z

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This paper cites Inductive relation prediction by subgraph reasoning,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Inductive relation prediction by subgraph reasoning,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:53.241407Z

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This paper cites Neural bellman- ford networks: A general graph neural network framework for link prediction,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Neural bellman- ford networks: A general graph neural network framework for link prediction,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:53.127266Z

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Observation 52ba68b8-6f3b-46c4-86f0-085ce4cfa4f1 · outbound

This paper cites A* net: A scalable path-based reasoning approach for knowledge graphs,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift A* net: A scalable path-based reasoning approach for knowledge graphs,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:53.010360Z

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This paper cites Knowledge graph reasoning with relational digraph,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Knowledge graph reasoning with relational digraph,

Reference 34

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Observation 63bf1d0b-5e77-4aa9-a8cc-8b956b6f70b6 · outbound

This paper cites Inductive logic programming: Theory and methods,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Inductive logic programming: Theory and methods,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:52.706046Z

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This paper cites an unresolved cited work.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Unresolved cited work

Reference 36

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This paper cites End-to-end differentiable proving,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift End-to-end differentiable proving,

Reference 37

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Observation c01d00bd-a01e-4fad-9777-8f7294d9c13c · outbound

This paper cites Drum: End-to-end differentiable rule mining on knowledge graphs,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Drum: End-to-end differentiable rule mining on knowledge graphs,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:52.304724Z

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Observation 0d20323e-cbbe-4212-af75-86ee12b9705a · outbound

This paper cites Neural compositional rule learning for knowledge graph reasoning,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Neural compositional rule learning for knowledge graph reasoning,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:52.147149Z

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This paper cites Learning to gener- alize: Meta-learning for domain generalization,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Learning to gener- alize: Meta-learning for domain generalization,

Reference 40

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This paper cites Domain generalization with adversarial feature learning,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Domain generalization with adversarial feature learning,

Reference 41

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Observation 4ada9ba5-5ae1-4e75-bb2d-cf74fcd71f25 · outbound

This paper cites Domain generalization via model-agnostic learning of semantic features,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Domain generalization via model-agnostic learning of semantic features,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:51.657009Z

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Observation c54b6da8-9ad2-427d-b70d-dcf310020087 · outbound

This paper cites Domain generalization via multidomain discriminant analysis,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Domain generalization via multidomain discriminant analysis,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:51.458021Z

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Observation f2fd0c35-95a6-4976-84a7-915abaa7d82e · outbound

This paper cites Efficient domain gener- alization via common-specific low-rank decomposition,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Efficient domain gener- alization via common-specific low-rank decomposition,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:51.247571Z

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This paper cites Learning to op- timize domain specific normalization for domain generalization,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Learning to op- timize domain specific normalization for domain generalization,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:51.080361Z

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Observation 49d1a1b3-9732-4be5-b7fb-ab277aeedc9e · outbound

This paper cites Domain generalization by solving jigsaw puzzles,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Domain generalization by solving jigsaw puzzles,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:50.934130Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0b391a25-fedf-40c4-b0af-7d836fcd27ed · outbound

This paper cites Generalizing Across Domains via Cross-Gradient Training.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Generalizing Across Domains via Cross-Gradient Training

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T19:39:44.364610Z

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Observation acaeab69-d8a8-4ba0-be08-485ec20d0c1c · outbound

This paper cites Generalizing to unseen domains via adversarial data augmentation,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Generalizing to unseen domains via adversarial data augmentation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:50.742615Z

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This paper cites Episodic training for domain generalization,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Episodic training for domain generalization,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:50.469301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b910051e-54ff-4348-ac93-0a02f1a7640a · outbound

This paper cites Invariant Risk Minimization.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Invariant Risk Minimization

Reference 50

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Observation 7b6262af-8492-4b4d-a689-b724ec2f686b · outbound

This paper cites Stable prediction with model misspecification and agnostic distribution shift,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Stable prediction with model misspecification and agnostic distribution shift,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:50.290035Z

Source-reported events for the cited work

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Observation 0235fd4e-0e84-45d2-af0e-2306325c1f54 · outbound

This paper cites Stable learning via sample reweighting,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Stable learning via sample reweighting,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:50.136391Z

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Observation 814da830-cfba-4866-89ef-0d59a9e8b388 · outbound

This paper cites A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T19:39:44.889929Z

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Observation c0441bad-1bae-4e3d-80a3-986e9cb7130a · outbound

This paper cites Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature Perspective.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature Perspective

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:39:46.713857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 56fbcf61-4b56-47e8-be5a-8ef9a9c31e6a · outbound

This paper cites Sound and complete forward and backward chainings of graph rules,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Sound and complete forward and backward chainings of graph rules,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:49.984320Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8d7fd6de-f94e-410c-8968-f5c6c3a1741b · outbound

This paper cites Amie: association rule mining under incomplete evidence in ontological knowledge bases,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Amie: association rule mining under incomplete evidence in ontological knowledge bases,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:49.817566Z

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Observation 23bd9473-2de0-40fa-8d32-ed8cab1a5923 · outbound

This paper cites Robust covariate shift regression,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Robust covariate shift regression,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:49.651950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 327c6e0f-e4af-4a38-8abc-1a6533074e5b · outbound

This paper cites Learning under nonstationarity: covariate shift and class-balance change,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Learning under nonstationarity: covariate shift and class-balance change,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:49.459716Z

Source-reported events for the cited work

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Observation 30d62e01-715c-471a-ba67-d3498bcbf010 · outbound

This paper cites A theoretical anal- ysis on independence-driven importance weighting for covariate- shift generalization,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift A theoretical anal- ysis on independence-driven importance weighting for covariate- shift generalization,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:49.317976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 95eed147-61c4-40d7-a767-1db42c6da750 · outbound

This paper cites An empirical study on robustness to spurious correlations using pre-trained language models,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift An empirical study on robustness to spurious correlations using pre-trained language models,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:49.135317Z

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Observation 7fb754a4-f9ba-40ff-882a-fdef33efb373 · outbound

This paper cites When does e (xk· yl)= e (xk)· e (yl) imply independence?.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift When does e (xk· yl)= e (xk)· e (yl) imply independence?

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:48.929508Z

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Observation 1e22d6e5-8340-400a-8022-466a3ac89e9b · outbound

This paper cites Approximate residual balancing: debiased inference of average treatment effects in high dimensions,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Approximate residual balancing: debiased inference of average treatment effects in high dimensions,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:48.754232Z

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Observation c043b3c1-0c24-4fe1-92b6-0dfb09dd0f56 · outbound

This paper cites Covariate balancing propensity score for a continuous treatment: Application to the efficacy of political advertisements,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Covariate balancing propensity score for a continuous treatment: Application to the efficacy of political advertisements,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:48.565042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e76471af-6a10-48ac-a118-6b63758c6256 · outbound

This paper cites Hollander, D.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Hollander, D

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-06T19:39:45.617092Z

Source-reported events for the cited work

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Observation 66404a46-aeab-4fa7-a4e2-565cad9a11e5 · outbound

This paper cites Spitzer, Principles of random walk.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Spitzer, Principles of random walk

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:48.373247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3a31785a-32b4-4a0e-b246-2547e3e79fe1 · outbound

This paper cites Learning distributed representations of con- cepts,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Learning distributed representations of con- cepts,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:48.179055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 57aeb332-b1a7-43db-a857-36c256802ba2 · outbound

This paper cites Statistical predicate invention,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Statistical predicate invention,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:48.009884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 739d4d69-6e43-4bd7-926a-98dd9b8e5066 · outbound

This paper cites Convo- lutional 2d knowledge graph embeddings,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Convo- lutional 2d knowledge graph embeddings,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:47.815070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation eef193c0-103b-4132-bf76-0b07e28dd8a7 · outbound

This paper cites Observed versus latent features for knowledge base and text inference,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Observed versus latent features for knowledge base and text inference,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:47.570461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e767d618-fe5d-4205-9264-4a14530cae85 · outbound

This paper cites Arnetminer: extraction and mining of academic social networks,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Arnetminer: extraction and mining of academic social networks,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:47.393724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ddbe615e-ce41-44b2-8b80-e055de93010a · outbound

This paper cites Geotext: an intelligent dynamic geometry textbook,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Geotext: an intelligent dynamic geometry textbook,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:47.201143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f1be99e8-8c73-4fd7-b568-7ade5f8ac4f9 · outbound

This paper cites Pytorch: An im- perative style, high-performance deep learning library,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Pytorch: An im- perative style, high-performance deep learning library,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:47.071276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bf32587e-590d-41d7-ab70-2f84f803ba2a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Adam: A Method for Stochastic Optimization

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-06T19:39:46.431360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6c95a57-11dc-4f38-923d-d40adde9dee4 · outbound

This paper cites Heterogeneous information networks: the past, the present, and the future,.

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift Heterogeneous information networks: the past, the present, and the future,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:39:46.922795Z

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