Deep Sparse Latent Feature Models for Knowledge Graph Completion | Paper Citation Record

Observation c76a4f91-4281-4117-8061-b5d2d2638ec0 · outbound

This paper cites Mixed membership stochastic blockmodels.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Mixed membership stochastic blockmodels

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.333336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6af2e037-4670-4e51-be44-532f8069cd77 · outbound

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

Deep Sparse Latent Feature Models for Knowledge Graph Completion Dbpedia: A nucleus for a web of open data

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.303630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d044f9f7-377f-48b4-9166-be5b3bb1e99b · outbound

This paper cites TuckER: Tensor Factorization for Knowledge Graph Completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion TuckER: Tensor Factorization for Knowledge Graph Completion

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.323010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98da3117-9164-4a0c-b4b6-971891056276 · outbound

This paper cites Reverse engineering self-supervised learning.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Reverse engineering self-supervised learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.280692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e2f1e313-d2bf-4ff3-a027-35a16c516657 · outbound

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

Deep Sparse Latent Feature Models for Knowledge Graph Completion Translating embeddings for modeling multi-relational data

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.341830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e226234-58f4-498f-b4e6-bfb44ee71ea2 · outbound

This paper cites Generating Sentences from a Continuous Space.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Generating Sentences from a Continuous Space

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.349940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8a36955-b135-448a-abaa-b336a84adfd0 · outbound

This paper cites Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completion

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.357965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8224b9f-ec21-470e-94d2-00fe4fd4c96a · outbound

This paper cites Dipping PLMs Sauce: Bridging Structure and Text for Effective Knowledge Graph Completion via Conditional Soft Prompting.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Dipping PLMs Sauce: Bridging Structure and Text for Effective Knowledge Graph Completion via Conditional Soft Prompting

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.366324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 843a0525-b94c-447c-9f03-d1d492e8739d · outbound

This paper cites HittER: Hierarchical transformers for knowledge graph embeddings.

Deep Sparse Latent Feature Models for Knowledge Graph Completion HittER: Hierarchical transformers for knowledge graph embeddings

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.248767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8db26c54-ab6b-401a-93ea-dc29c7ba6050 · outbound

This paper cites A simple frame- work for contrastive learning of visual representations.

Deep Sparse Latent Feature Models for Knowledge Graph Completion A simple frame- work for contrastive learning of visual representations

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.231361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ed2ec9c4-81cb-4f9b-97f5-05a89da7dfc2 · outbound

This paper cites A direct formulation for sparse pca using semidefinite programming.

Deep Sparse Latent Feature Models for Knowledge Graph Completion A direct formulation for sparse pca using semidefinite programming

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.213104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ba360ca8-4358-4639-8db4-59911b521c8b · outbound

This paper cites Inductive entity representations from text via link prediction.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Inductive entity representations from text via link prediction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.191807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0293d121-b2c1-4713-82cf-db6e4a3055e0 · outbound

This paper cites Convolutional 2d knowledge graph embeddings.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Convolutional 2d knowledge graph embeddings

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.408213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aaf061ed-7792-4f8f-b496-1cf595eb8193 · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding.

Deep Sparse Latent Feature Models for Knowledge Graph Completion BERT: Pre-training of deep bidirectional transformers for language understanding

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.162163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 21aa8318-577d-4e21-a297-edcd8eb85f75 · outbound

This paper cites Knowledge vault: A web-scale approach to proba- bilistic knowledge fusion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Knowledge vault: A web-scale approach to proba- bilistic knowledge fusion

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.138186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e2133dcb-ad03-4c36-90c7-706fbc5dbc33 · outbound

This paper cites Implicit reparameterization gradients.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Implicit reparameterization gradients

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.431941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7f34773-6545-49b9-b47a-c58b6fdedf62 · outbound

This paper cites Infinite latent feature models and the indian buffet process.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Infinite latent feature models and the indian buffet process

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.096512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0a2e783a-8385-489e-ad78-0b012bdcf650 · outbound

This paper cites The indian buffet process: An introduction and review.

Deep Sparse Latent Feature Models for Knowledge Graph Completion The indian buffet process: An introduction and review

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.076185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cd5187a1-3447-49d2-b202-780ef22ac3bf · outbound

This paper cites Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.055486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 22d585ae-7292-441a-9f1f-fb11a7368b16 · outbound

This paper cites beta-vae: Learning basic visual concepts with a constrained variational framework.

Deep Sparse Latent Feature Models for Knowledge Graph Completion beta-vae: Learning basic visual concepts with a constrained variational framework

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.457988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ba42529-b899-4ca0-bf8e-2348ebba0b6a · outbound

This paper cites Learning deep representations by mutual information estimation and maximization.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Learning deep representations by mutual information estimation and maximization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.468843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5d8ac82-561d-49c3-b874-e6b9abb138c7 · outbound

This paper cites Stochastic blockmodels: First steps.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Stochastic blockmodels: First steps

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.485109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b9e383a-bc13-4d97-90bc-a8006f4f8846 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Categorical Reparameterization with Gumbel-Softmax

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.493179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a7cabb4-eb53-4b13-abe7-462766a46448 · outbound

This paper cites A modified principal component technique based on the lasso.

Deep Sparse Latent Feature Models for Knowledge Graph Completion A modified principal component technique based on the lasso

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:59.007628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8f5dfb43-f7c8-4096-89d5-9d6114d0d59d · outbound

This paper cites Supervised contrastive learning.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Supervised contrastive learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.506372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d65232b-69dc-4b4c-ae1a-cc0d81b9a17e · outbound

This paper cites Multi-task learning for knowl- edge graph completion with pre-trained language models.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Multi-task learning for knowl- edge graph completion with pre-trained language models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.973114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d37aaec4-32a5-4464-8f4b-8b5a5893dc4f · outbound

This paper cites Auto-Encoding Variational Bayes.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Auto-Encoding Variational Bayes

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.519671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f424b7ff-67c9-4cb5-b63f-8108ad25e413 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Semi-Supervised Classification with Graph Convolutional Networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.525499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9104574d-919e-4f69-88f9-ec0b10c98e1c · outbound

This paper cites Statistical predicate invention.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Statistical predicate invention

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.955638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 696c9292-a718-4b78-8ea1-f082e79c557a · outbound

This paper cites Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-12T14:07:58.163390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 31c22cb7-37f0-4e8e-af40-488c4d1f66f8 · outbound

This paper cites Bayesian methods for graph clustering.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Bayesian methods for graph clustering

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.934273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0db8b9db-69dc-49cf-9c86-c756b25781f1 · outbound

This paper cites Overlapping stochastic block models with application to the french political blogosphere.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Overlapping stochastic block models with application to the french political blogosphere

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.913668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cf2d9ce7-6614-438c-bfdb-d7c9725628be · outbound

This paper cites KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse Transformation.

Deep Sparse Latent Feature Models for Knowledge Graph Completion KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse Transformation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.563334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f9c986f-603e-419e-8255-72765903b4ee · outbound

This paper cites an unresolved cited work.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-12T14:07:58.882170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 405e01db-fdc2-4574-8eb2-8f3d86a303e5 · outbound

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

Deep Sparse Latent Feature Models for Knowledge Graph Completion Learning entity and relation embeddings for knowledge graph completion

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.576572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da6c46a3-9103-4d3d-ae06-f483eb7c728b · outbound

This paper cites The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables.

Deep Sparse Latent Feature Models for Knowledge Graph Completion The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.586699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14aeb47f-8c72-4128-9bd0-37c2a5220e22 · outbound

This paper cites A* sampling.Advances in neural information processing systems, 27, 2014.

Deep Sparse Latent Feature Models for Knowledge Graph Completion A* sampling.Advances in neural information processing systems, 27, 2014

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.591833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8dbed17-f0f0-4125-9c67-ebaf34ab58e5 · outbound

This paper cites Stochastic blockmodels meet graph neural networks.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Stochastic blockmodels meet graph neural networks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.820293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation efaaa29c-390a-49c9-b16c-f2ef6739b4ec · outbound

This paper cites Nonparametric latent feature models for link prediction.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Nonparametric latent feature models for link prediction

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.796396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9ff25a3a-d98e-4262-b42c-2cef8cd05743 · outbound

This paper cites Stick-Breaking Variational Autoencoders.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Stick-Breaking Variational Autoencoders

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.614542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3b4ce15-6271-4acb-89be-3f9a257b2780 · outbound

This paper cites Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.620230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ef94036-76b4-43a2-9121-b7356111fbcb · outbound

This paper cites Communities in networks.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Communities in networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.772820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d6f90500-0a7c-48ec-a3e9-1b083cc2f15a · outbound

This paper cites Improving knowledge graph completion with generative hard negative mining.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Improving knowledge graph completion with generative hard negative mining

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.751965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0bef2dcd-69c4-456e-b3a3-5e306b0511b8 · outbound

This paper cites Variational inference with normalizing flows.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Variational inference with normalizing flows

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.638610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88f67b23-e747-46a9-93b6-c40c5b012205 · outbound

This paper cites Modeling relational data with graph convolutional networks.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Modeling relational data with graph convolutional networks

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.644261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 228acbf0-57ca-459a-bde4-9ccec61e04b3 · outbound

This paper cites Reasoning with neural tensor networks for knowledge base completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Reasoning with neural tensor networks for knowledge base completion

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.654029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3a85480-c285-4291-b005-8c05d7557e7f · outbound

This paper cites Stochas- tic block models with multiple continuous attributes.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Stochas- tic block models with multiple continuous attributes

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.692617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5dc71901-7c3a-4b44-a2ee-1b53e6ba548d · outbound

This paper cites Rotate: Knowledge graph em- bedding by relational rotation in complex space.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Rotate: Knowledge graph em- bedding by relational rotation in complex space

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.675081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 15992681-6ce7-4682-a2d5-2f37ca7dd063 · outbound

This paper cites Kracl: Contrastive learning with graph context modeling for sparse knowledge graph completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Kracl: Contrastive learning with graph context modeling for sparse knowledge graph completion

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.656262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ad80576f-36a7-4280-83fd-b184886bef61 · outbound

This paper cites Stick-breaking construction for the indian buffet process.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Stick-breaking construction for the indian buffet process

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.636081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 23ddcdde-fb2c-4ec5-82b2-251929acb04e · outbound

This paper cites Representing text for joint embedding of text and knowledge bases.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Representing text for joint embedding of text and knowledge bases

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.612387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5046717f-bfb7-47cc-9757-783f00d1394e · outbound

This paper cites Composition-based Multi-Relational Graph Convolutional Networks.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Composition-based Multi-Relational Graph Convolutional Networks

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.697201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3b6b53f-c3c0-4118-b4cc-63d4fc4a472d · outbound

This paper cites Wikidata: a free collaborative knowledgebase.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Wikidata: a free collaborative knowledgebase

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.703340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a347473-492b-4464-94cb-2706edc8ed65 · outbound

This paper cites Structure- augmented text representation learning for efficient knowledge graph completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Structure- augmented text representation learning for efficient knowledge graph completion

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.580599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 01a4448f-edd6-46d0-b265-e7cee5ebb02c · outbound

This paper cites Simkgc: Simple contrastive knowledge graph completion with pre-trained language models.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Simkgc: Simple contrastive knowledge graph completion with pre-trained language models

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.556490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0bb263bc-04f4-4e83-b6c2-4a058b0e31fb · outbound

This paper cites Kepler: A unified model for knowledge embedding and pre-trained language representation.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Kepler: A unified model for knowledge embedding and pre-trained language representation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.535009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ebb73c37-1618-4f8d-8095-52aab0fccff2 · outbound

This paper cites KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.742280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08fd125f-71a8-4074-8fe4-9c4d49ab2dc1 · outbound

This paper cites Representation learning of knowledge graphs with entity descriptions.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Representation learning of knowledge graphs with entity descriptions

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.752663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 847bed4a-00d1-445f-a7d4-a9a2a5bee464 · outbound

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

Deep Sparse Latent Feature Models for Knowledge Graph Completion Embedding Entities and Relations for Learning and Inference in Knowledge Bases

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.760048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfe171ef-1168-4684-8027-73d0f918db45 · outbound

This paper cites Enhancing text-based knowledge graph completion with zero-shot large language models: A focus on semantic enhancement.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Enhancing text-based knowledge graph completion with zero-shot large language models: A focus on semantic enhancement

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.486764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c42a8f95-8f15-485f-933c-95f55de2b365 · outbound

This paper cites Knowledge graph embedding and completion based on entity community and local importance.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Knowledge graph embedding and completion based on entity community and local importance

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.461407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5c89d46d-05cd-41dd-aeef-237ea7def880 · outbound

This paper cites KG-BERT: BERT for Knowledge Graph Completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion KG-BERT: BERT for Knowledge Graph Completion

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.787496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c1e8f19-2f59-47dd-a3e1-04d298a05388 · outbound

This paper cites Exploring Large Language Models for Knowledge Graph Completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Exploring Large Language Models for Knowledge Graph Completion

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.794183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c757c233-4aca-4a7f-97c9-445fabd6778c · outbound

This paper cites Native: Multi-modal knowledge graph completion in the wild.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Native: Multi-modal knowledge graph completion in the wild

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.437707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b01d99e4-de0f-4b5d-88c3-4ff75d9b757b · outbound

This paper cites Making large language models perform better in knowledge graph completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Making large language models perform better in knowledge graph completion

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-12T14:07:57.809572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57359eba-ecfb-44e3-86c3-3b781767fbef · outbound

This paper cites Rethinking graph convolutional networks in knowledge graph completion.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Rethinking graph convolutional networks in knowledge graph completion

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:07:58.393797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 967c627b-e970-4219-bb05-bb967fa9f354 · outbound

This paper cites Max-Margin Nonparametric Latent Feature Models for Link Prediction.

Deep Sparse Latent Feature Models for Knowledge Graph Completion Max-Margin Nonparametric Latent Feature Models for Link Prediction

Reference 67

Resolution: verified exact; local_arxiv, observed 2026-08-12T14:07:57.912390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e3b10521-3c75-4bf3-825c-66b7eec15f2d · outbound

This paper cites location-scale.

Deep Sparse Latent Feature Models for Knowledge Graph Completion location-scale

Reference 68

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T14:07:58.370935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers