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Paper Citation Record · LEDGER

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering

As of 8 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 2 inbound Pith citation observations for arXiv:2506.09645.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.09645 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:47:40.429016Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T04:35:49.207472Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-12T06:06:26.153057Z

Reference resolution

70 of 70 outbound references displayed

  • verified exact0
  • verified fuzzy28
  • unresolved42
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b60b0f9-7b27-411b-ae0c-e5daefc97c73 · outbound

This paper cites GPT-4 Technical Report.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation dc76a1ee-eef8-46bb-b9f0-e2010a6a24b0 · outbound

This paper cites Semantic parsing on freebase from question-answer pairs.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Semantic parsing on freebase from question-answer pairs

Reference 2

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source=pdf_text observed=2026-08-07T04:47:35.562957Z digest=sha256:07a02f74250d904f84938bba17ea0adf40239bb31452ae07a72f91c61402662c

Observation 28080855-5c2d-449d-88ab-a365843f1703 · outbound

This paper cites Freebase: a collaboratively created graph database for structuring human knowledge.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Freebase: a collaboratively created graph database for structuring human knowledge

Reference 3

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source=pdf_text observed=2026-08-07T04:47:35.626404Z digest=sha256:b64a14de9c58711a989e56c16c7ea013464070ea6c651e3080c8a3036a826302

Observation add3c118-c2d1-4643-9d8a-ec44a67bd922 · outbound

This paper cites Language models are few-shot learners.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Language models are few-shot learners

Reference 4

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source=pdf_text observed=2026-08-07T04:47:35.675026Z digest=sha256:19b7d77b7f90343bd870cba9487b1085ae04297199c27d209ce52b933dee6379

Observation 680c345c-f67e-4f2a-abfa-0092744f2d03 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 5

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source=pdf_text observed=2026-08-07T04:47:35.720901Z digest=sha256:88cfd14548c88395cf48b20edc77c671c1864dfa4326f46b959923ebc3a19216

Observation 6a15196b-26f1-42f7-8fdc-5b2bc0ed08ed · outbound

This paper cites Springer Science & Business Media, 2008.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Springer Science & Business Media, 2008

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.233744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:35.761632Z digest=sha256:54f60024b37afca13d32c83ca2f55a04bab310bd8a945f07c774dce67c9ca2f8

Observation 8bb14fe6-fe07-4925-9c4e-0de11bd8ffd2 · outbound

This paper cites Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:35.794225Z digest=sha256:c4e6d2f3356f23f4c19d3b50bbe2d6359d06d9b78a8a41752fa2e295d3967a13

Observation 83f98206-911a-4cc9-a6fe-1baf6a50941e · outbound

This paper cites EWEK-QA : Enhanced web and efficient knowledge graph retrieval for citation-based question answering systems.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering EWEK-QA : Enhanced web and efficient knowledge graph retrieval for citation-based question answering systems

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.223211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:35.818932Z digest=sha256:7cf2232efb17c99473559ed61936a2db490b8f079a2f7ac67c30e3d1c47d4692

Observation 696d674e-afaa-4c44-a338-b84f3db386be · outbound

This paper cites HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics

Reference 9

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T04:47:35.900857Z digest=sha256:f5ffe03c8288169eec2c206309bea269d45846d2ac996e093020ff97d5da923d

Observation 84bf3b83-011f-414b-8f8a-b3bb52a083b6 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Fast Graph Representation Learning with PyTorch Geometric

Reference 10

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T04:47:35.961960Z digest=sha256:26d71a87fae14e656b5ca46c120a34cd4d539dc2c35920caba0a8fbcbe8d01c2

Observation 2e504b99-2af7-4fb9-9937-15b8e5a6bc03 · outbound

This paper cites Towards Foundation Models for Knowledge Graph Reasoning.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Towards Foundation Models for Knowledge Graph Reasoning

Reference 11

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source=pdf_text observed=2026-08-07T04:47:36.017211Z digest=sha256:40e960dd2d7130862d32fdfdeefe975efe2143689b1e61c2b584a13783dfada0

Observation 14e9c7be-2a72-4b2d-a555-2a288d1bec29 · outbound

This paper cites Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation Types.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation Types

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:36.115558Z digest=sha256:3e5a26f6122a393be744999bc2594d3a9d62e905ffbe88d0edc77c96730dc39d

Observation b02ba82e-1a16-403a-8c94-54a7aec3dddf · outbound

This paper cites Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models

Reference 13

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no resolver link, observed 2026-08-07T04:47:36.176716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:36.176716Z digest=sha256:6edca86ba62ff2ff0d4ee395ae954ea5a956cda0eca202085aeda253defae0b2

Observation b3080ddd-96ad-4e88-96f5-54bf4d932816 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:36.267679Z digest=sha256:13959177553ff983719a896dd9973fa5ee80b4c43fe743405c9d810631af7c96

Observation 60435a6d-03ad-4e17-8bcd-c6738d72e2ed · outbound

This paper cites Rela- tional message passing for fully inductive knowledge graph completion.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Rela- tional message passing for fully inductive knowledge graph completion

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.211642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:36.324084Z digest=sha256:c8711dc43f9e322af5ee1a35f485c233d395fcdf10a407cd44813b6ca3f1d9fe

Observation b3090267-438c-43c5-9817-66a22fac3270 · outbound

This paper cites Exploring network structure, dynamics, and function using networkx.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Exploring network structure, dynamics, and function using networkx

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:36.420767Z digest=sha256:0590adce294e97e756d0b9e0f9fe34162f7c443404033e678e86f7d781b98f5b

Observation 7a7fd096-0af0-4fb0-b4f8-de98bb3fe960 · outbound

This paper cites Inductive representation learning on large graphs.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Inductive representation learning on large graphs

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.195591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:36.470357Z digest=sha256:924b4fb1c71c41e71d10c28e4c86ce4523c393204919912d39683cfba4606416

Observation 5181610a-b387-47db-84bc-e212cbe4b65f · outbound

This paper cites G-retriever: Retrieval-augmented generation for textual graph understanding and question answering.Advances in Neural Information Processing Systems, 37:132876–132907, 2024.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering G-retriever: Retrieval-augmented generation for textual graph understanding and question answering.Advances in Neural Information Processing Systems, 37:132876–132907, 2024

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:36.580762Z digest=sha256:0e2e0f6c725dcc5597d8a7c83d08ffb11b64538aac28acbced1134592b26ab68

Observation 657094fa-72c3-41cd-af46-29b58b16db0f · outbound

This paper cites Knowledge graphs.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Knowledge graphs

Reference 19

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T04:47:36.629133Z digest=sha256:c308a53c6dbd4f653eaf58b3d3657ed1af8aab1835817dbf7bbced2a9ef7e145

Observation 0e971bff-4b9b-4c5c-ba35-c5e5e0ec0384 · outbound

This paper cites Towards reasoning in large language models: A survey.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Towards reasoning in large language models: A survey

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.174449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:36.687834Z digest=sha256:94cc36fef66da23928aadf7befa7b53d212172fa553b535b18c20fc83feb914a

Observation 2f0f03c4-991b-4237-a49f-d908954ddb13 · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 21

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T04:47:36.770322Z digest=sha256:9f2939970aaa89952c4f33675dcd2e15ad6b93890ddd07913e3f981f3ff51c6a

Observation d22116a6-75aa-4ad8-871a-3f2cb06818b2 · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Batch normalization: Accelerating deep network training by reducing internal covariate shift

Reference 22

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source=pdf_text observed=2026-08-07T04:47:36.839879Z digest=sha256:d5a0a880069f1191091c85e1280bfe05db5178c4a72aa9920a3ab51ea85aeecc

Observation 2f0ec49d-10ee-40cf-97df-55b7ee95dd32 · outbound

This paper cites Survey of hallucination in natural language generation.ACM Computing Surveys, 55(12), 2023.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Survey of hallucination in natural language generation.ACM Computing Surveys, 55(12), 2023

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:36.908428Z digest=sha256:7bbcf190bd98cad8993fa07ba4503b4a80f8ebd7a88f7e67cddfe08870c5f1a8

Observation 814650eb-78cb-4a58-9e8c-50f253b7efcf · outbound

This paper cites Structgpt: A general framework for large language model to reason over structured data.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Structgpt: A general framework for large language model to reason over structured data

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.149443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:36.964423Z digest=sha256:aacca6944fd04bc7af417037ef9cbbe4f1f1fa8e9e006298a1f0f49fb53a5219

Observation 58aba20a-676a-4785-a2c5-51308776fa3e · outbound

This paper cites KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge Graph.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge Graph

Reference 25

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.028487Z digest=sha256:123c7680e8f6e18df2257fe81646eb430c0bca4986d1e641a93e2375b50593f8

Observation 00f4ebb6-c97f-4b38-8179-9b96929f4969 · outbound

This paper cites Unikgqa: Unified retrieval and reasoning for solving multi-hop question answering over knowledge graph.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Unikgqa: Unified retrieval and reasoning for solving multi-hop question answering over knowledge graph

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.138520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:37.092663Z digest=sha256:5b935acfb768be71a6a21025d278973f8397c0950273afb4a0e29eb3a6d386b4

Observation e66e7667-9ad3-455a-8e30-50cffcc77095 · outbound

This paper cites Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.174141Z digest=sha256:d04648367e26b5a53c164ce3baa7ffc38d519ca7bc652cdd757dfdca2cce17b8

Observation ac24dc96-bcc9-4128-a7f9-9136e2d4cd59 · outbound

This paper cites Smith, Yejin Choi, and Kentaro Inui.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Smith, Yejin Choi, and Kentaro Inui

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.128715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:37.247319Z digest=sha256:483bd5afa36dcee01439491e9e15300cbba484f8ef9e56d34601953827f56029

Observation 308e4f23-1db1-49b1-bf6e-b71e6be288d3 · outbound

This paper cites KG-GPT: A general framework for reasoning on knowledge graphs using large language models.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering KG-GPT: A general framework for reasoning on knowledge graphs using large language models

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.116803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:37.302694Z digest=sha256:3b5f8c35a6eed94532a2e4ae96f866209f6ec91488304d0cb828d6ecd0b0ad9a

Observation a750e4ad-3d8d-4d3e-987d-c8055f873e4a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Adam: A Method for Stochastic Optimization

Reference 30

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.354968Z digest=sha256:ab7028ebac10171e50f46c4d842aefe27d7675af5787fcf0ef15f7bdf840df6e

Observation 7baff500-c81c-4aa7-aafc-31c624088a1c · outbound

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

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Semi-Supervised Classification with Graph Convolutional Networks

Reference 31

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.399355Z digest=sha256:0f251f6ab5f44595f2ba694c5f9fd03e9d127272eb658a5996eaa0d1ff6a80ac

Observation 54872069-8d31-40c5-ba5c-665e1974d6df · outbound

This paper cites Ingram: Inductive knowledge graph embedding via relation graphs.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Ingram: Inductive knowledge graph embedding via relation graphs

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.105979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:37.444395Z digest=sha256:d06873c865028a728ed54d6dac27f393b4ac340f816ebefd1266699595fb5f0e

Observation 03af9d0a-7014-4ae6-b89d-9f36c2c30804 · outbound

This paper cites Retrieval-augmented generation for knowledge- intensive nlp tasks.Advances in neural information processing systems, 33:9459–9474, 2020.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Retrieval-augmented generation for knowledge- intensive nlp tasks.Advances in neural information processing systems, 33:9459–9474, 2020

Reference 33

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no resolver link, observed 2026-08-07T04:47:37.530892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.530892Z digest=sha256:ddb4c3e22e08954c1c43c6ebd7bbbb1f5a78f0b8d0bc9b2143c426772e1a8605

Observation 8542ce97-933d-42d5-8941-52302f466351 · outbound

This paper cites Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.567324Z digest=sha256:7d341ecb42c22645ab5680a7f9c2b20edb7fcb030358b791d334153d7a20316a

Observation 05fea252-2a91-4388-a488-079ccbeb8aa2 · outbound

This paper cites Distance encoding: Design provably more powerful neural networks for graph representation learning.Advances in Neural Information Processing Systems, 33:4465–4478, 2020.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Distance encoding: Design provably more powerful neural networks for graph representation learning.Advances in Neural Information Processing Systems, 33:4465–4478, 2020

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.089143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:37.627052Z digest=sha256:cd8f0290e408aac6539b7caf5c427c4c9a059c244bec9833e10a353f70ad994f

Observation b1524cd9-3362-45ec-9a64-cb34902f4257 · outbound

This paper cites Graph reasoning for question answering with triplet retrieval.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Graph reasoning for question answering with triplet retrieval

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.078918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:37.682852Z digest=sha256:3acbf968dcc126f5f2fc3c31e0629c85edcccfebad6d6d21c01e0e543d8d8262

Observation 78483f80-88b2-42a0-a649-9758f2f054c1 · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.719430Z digest=sha256:a701c8c50cb3fd8bc1d37f3626c487188fe51612cb852d9527f1271a51f5ab7a

Observation 0b8bfeaf-185f-41d6-869d-3fc239f650d2 · outbound

This paper cites Dual Reasoning: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Dual Reasoning: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.757564Z digest=sha256:65a7aa7f2ecaf4daa1ebdbfe20cf9c2cd3652eb17499ffe7decf643eed5dc8e9

Observation a8487c9b-58da-4910-a855-a6b710b74c4b · outbound

This paper cites Dual reasoning: A gnn-llm collaborative framework for knowledge graph question answering, 2025.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Dual reasoning: A gnn-llm collaborative framework for knowledge graph question answering, 2025

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.068430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:37.834534Z digest=sha256:b4d530d7b57e99e60e1acbe4550d58218080703d3aee0101b88fead1db97568a

Observation 5f546da4-17aa-4019-ae9e-017d78aec195 · outbound

This paper cites Reasoning on graphs: Faithful and interpretable large language model reasoning.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Reasoning on graphs: Faithful and interpretable large language model reasoning

Reference 40

Resolution
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no resolver link, observed 2026-08-07T04:47:37.902338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.902338Z digest=sha256:df0bb0d3a8fbd080f75455a5d83601a1fe660d2f03a0bd1dcd3591ca76e6bc4c

Observation 9e8d211e-c3e1-441d-b8af-6102d0a87968 · outbound

This paper cites Think-on-graph 2.0: Deep and interpretable large language model reasoning with knowledge graph-guided retrieval.arXiv e-prints, pages arXiv–2407, 2024.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Think-on-graph 2.0: Deep and interpretable large language model reasoning with knowledge graph-guided retrieval.arXiv e-prints, pages arXiv–2407, 2024

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.052356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:37.974407Z digest=sha256:1e2d0862018592a33e932aade8ed4f9d2aa399649530895203337df242004d9c

Observation 90775d33-dd47-4f9d-9b23-b7b07ee0f784 · outbound

This paper cites Automated social science: Language models as scientist and subjects.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Automated social science: Language models as scientist and subjects

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T04:47:38.023777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.023777Z digest=sha256:8a023dc4445c6a4bbeb2402d687aa04632a7688aed43ef1159f4f9e25c25890c

Observation b6c9d1b5-aeb5-42a6-8fa2-4c14e20aa59d · outbound

This paper cites Rearev: Adaptive reasoning for question answering over knowledge graphs.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Rearev: Adaptive reasoning for question answering over knowledge graphs

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.034355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:38.106561Z digest=sha256:5a981ed7a7f7b15d92bc506e24f91a594a713bd99205cfd885a60383b890f49b

Observation 6a6b8ed1-b82d-45e4-82a5-f078aa5553cc · outbound

This paper cites GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning

Reference 44

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.174391Z digest=sha256:023954b0c74fd3ef62acd8cf1bfb38846bf5c39cc9383492bb00d855e5c6083e

Observation cd52d773-5628-4b3a-b793-4ed06891fdfe · outbound

This paper cites Build the future of ai with meta llama 3, 2024.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Build the future of ai with meta llama 3, 2024

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.023784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:38.226132Z digest=sha256:1c7a470ea90f6da9369392f5499ee8f4aa088a25d9aacb7c8b67fb2b9e6eb4b8

Observation 59b96e11-5e18-4a1f-b930-dd18df9e4b98 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Efficient Estimation of Word Representations in Vector Space

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T04:47:38.294523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.294523Z digest=sha256:86219621fe90b8613a7a998a929d8c192cb2e0cbd24b1d6f6d343217222232dc

Observation 48866ae5-4633-4ddb-9d3f-2048c29ee9c9 · outbound

This paper cites Introducing chatgpt, 2022.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Introducing chatgpt, 2022

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:41.013626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:38.354887Z digest=sha256:8769267e98c65eb2117edc92cfb0d06084d4ddc931a1ebd27b976f25b1ad3956

Observation c7e3a015-d613-4303-a41b-dd05586bd6e7 · outbound

This paper cites Hello gpt-4o, 2024.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Hello gpt-4o, 2024

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T04:47:38.407792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.407792Z digest=sha256:eb3ca23c5b8781036c3d0f58df921c03d3ac8616e66c4c432da14b5acdf95c2b

Observation 9be7f244-d084-41c8-890b-df29cc419106 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library, 2019.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Pytorch: An imperative style, high-performance deep learning library, 2019

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T04:47:38.476718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.476718Z digest=sha256:05598611f1ace6e07021caec450b5f15668b2e77c2285235daa43aebe301145f

Observation bd18f6f3-c8b2-4edc-9c49-1e1a477ecef5 · outbound

This paper cites O’Reilly Media, Inc.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering O’Reilly Media, Inc

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.991049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:38.513260Z digest=sha256:9c18112fc623fd28f6cb64b94e22f3a4440808e223c57b1b956a2873c2dd4f88

Observation ac51d714-839d-4423-9012-14a5813f6419 · outbound

This paper cites Retrieval augmentation reduces hallucination in conversation.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Retrieval augmentation reduces hallucination in conversation

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.979838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:38.562263Z digest=sha256:755953081fd79694da4578b4c800b8c4a53583028215baa48789e890f37116f4

Observation 8dc5cdf7-85c9-41a2-8f26-f3ee101d2dee · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfitting.The journal of machine learning research, 15(1):1929–1958, 2014.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Dropout: a simple way to prevent neural networks from overfitting.The journal of machine learning research, 15(1):1929–1958, 2014

Reference 52

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no resolver link, observed 2026-08-07T04:47:38.630413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.630413Z digest=sha256:eb88e92d1830d7d227acc8ed00d02813ef97cac3477d11d55a121b9e1e97c289

Observation 02901886-9147-4606-b60d-f0c075a6dfa8 · outbound

This paper cites Think-on-graph: Deep and responsible reasoning of large language model on knowledge graph.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Think-on-graph: Deep and responsible reasoning of large language model on knowledge graph

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.962486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:38.689683Z digest=sha256:5fa452b8527bc74991fb1c4cc021ca2c28d68979202cadfb8bca7e5bf854b3aa

Observation e004cb1e-5fb5-44e6-96ac-056696b01d77 · outbound

This paper cites The web as a knowledge-base for answering complex questions.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering The web as a knowledge-base for answering complex questions

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.951943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:38.759559Z digest=sha256:42c9c33d80297e847811af4be9b3ca60ebd3b0eaf67604da07fbebcf80af04d3

Observation 0c8449b2-26e0-4756-aa9f-2c279be8634e · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 55

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no resolver link, observed 2026-08-07T04:47:38.793227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.793227Z digest=sha256:c09c4ce4e056715328339872cc82544d9141ae1a32abcc6a589e6e84eaafe0df

Observation 11c09014-839f-430b-98c1-eac2bc1f3b84 · outbound

This paper cites Graph Attention Networks.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Graph Attention Networks

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T04:47:38.850519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.850519Z digest=sha256:cb99c9f93f59baa3555f9ab7b259c7864b876fe5406979805d3d5e6c396dbd67

Observation cc124f8c-8d79-4762-8468-2b9b1d29e030 · outbound

This paper cites Graph attention networks.stat, 1050(20):10–48550, 2017.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Graph attention networks.stat, 1050(20):10–48550, 2017

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T04:47:38.924630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.924630Z digest=sha256:2780ee55c1adac27a6fc1fd206d00bda2ed4e6c4ade02d10f6746910c79058b0

Observation aecae7b9-be3a-47a6-8bbe-57cd60633558 · outbound

This paper cites Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering

Reference 58

Resolution
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no resolver link, observed 2026-08-07T04:47:39.004807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:39.004807Z digest=sha256:ea46bf0075b7b82b672d8faadd454f2631a8756cc0c4ec7a2c10fdb173e88759

Observation 87abafd6-a0d9-42c2-b44d-1a542c426d42 · outbound

This paper cites Knowledge graph prompting for multi-document question answering.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Knowledge graph prompting for multi-document question answering

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.935333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:39.118607Z digest=sha256:6c4c8f71f899e93b7aa2c67fed7d1f02a276d4609f8afa5f8baaccf5060c188e

Observation 94b044d8-65e3-4c2c-93a8-2fe146060367 · outbound

This paper cites Chi, Quoc V Le, and Denny Zhou.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Chi, Quoc V Le, and Denny Zhou

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.925781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:39.250700Z digest=sha256:b4ce993a52155f0207a82dc2789f070096bcc4d32ec4120251d739999c36f131

Observation 35d93351-ee93-438e-b484-dea0c61bee54 · outbound

This paper cites MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models

Reference 61

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unresolved
no resolver link, observed 2026-08-07T04:47:39.345994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:39.345994Z digest=sha256:c372b7ec6a1a905421adb08f10d50e85a8786f379c02557cb1a0cda91ea7e613

Observation 41a7c75b-4527-43a9-b6ad-25a2121ae32b · outbound

This paper cites A survey on large language models for recommendation.World Wide Web, 27(5):60, 2024.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering A survey on large language models for recommendation.World Wide Web, 27(5):60, 2024

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.915854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:39.435851Z digest=sha256:f28ae8d490f4322cac0a21d0768b819b5b95cf6130e1ff60f77dabea4c8b79c5

Observation ba57b682-8da1-4d02-b952-19fcd31e2a16 · outbound

This paper cites Retrieve-rewrite-answer: A kg-to-text enhanced llms framework for knowledge graph question answering, 2023.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Retrieve-rewrite-answer: A kg-to-text enhanced llms framework for knowledge graph question answering, 2023

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.906714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:39.614841Z digest=sha256:cbaf4326e5b667fe794d0542f1262c77501a9c533a08e1707c375702b2adb52f

Observation 37aafdf4-ff76-4d13-8d0c-3f52feb8b494 · outbound

This paper cites How powerful are graph neural networks? InInternational Conference on Learning Representations, 2019.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering How powerful are graph neural networks? InInternational Conference on Learning Representations, 2019

Reference 64

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unresolved
no resolver link, observed 2026-08-07T04:47:39.715576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:39.715576Z digest=sha256:e781b63316f5f92e35b27af62b3a8d6365e9e7408810b86914eaa515b12f8ffd

Observation b4614909-b869-4f82-82e3-514f981458f4 · outbound

This paper cites Qwen2 Technical Report.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Qwen2 Technical Report

Reference 65

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unresolved
no resolver link, observed 2026-08-07T04:47:39.818522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:39.818522Z digest=sha256:1f6d0eec2a752433bbd1318fe5301b04642982515051e4199105024da0d034a3

Observation 835a9359-650b-4fc6-bcee-ca18a88750f0 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.Advances in Neural Information Processing Systems, 36, 2024.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Tree of thoughts: Deliberate problem solving with large language models.Advances in Neural Information Processing Systems, 36, 2024

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.891139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:39.987320Z digest=sha256:a07be2dffae1b10c6a6b933958324347d1c30a23ccc3d8692cc1ebe1e6f03305

Observation 3a85d529-0906-4a42-840f-67c48160cf37 · outbound

This paper cites The value of semantic parse labeling for knowledge base question answering.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering The value of semantic parse labeling for knowledge base question answering

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.881183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:40.097440Z digest=sha256:092ce08b51d6d3a2475c61f90a87f08b18f474fa0307992c873e6d9125129860

Observation 7c8e05b6-ba32-49e1-a427-edc98711ca4a · outbound

This paper cites Subgraph retrieval enhanced model for multi-hop knowledge base question answering.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Subgraph retrieval enhanced model for multi-hop knowledge base question answering

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:47:40.823166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:47:40.225987Z digest=sha256:89c427a04a353f57e0734563627f08e1d3c2b2b37145b76d2ba206b5494c9736

Observation c0e7ccde-1205-4b1f-a6a9-cc049a1f1bd6 · outbound

This paper cites Labeling trick: A theory of using graph neural networks for multi-node representation learning.Advances in Neural Information Processing Systems, 34:9061–9073, 2021.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Labeling trick: A theory of using graph neural networks for multi-node representation learning.Advances in Neural Information Processing Systems, 34:9061–9073, 2021

Reference 69

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no resolver link, observed 2026-08-07T04:47:40.327799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:40.327799Z digest=sha256:f1efd823c18768bac61e8368f9ed956eed1085e3f369682ff6db9d9568c24b9e

Observation d646f850-f168-4085-9803-f0ed851c6c27 · outbound

This paper cites A Multi-Task Perspective for Link Prediction with New Relation Types and Nodes.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering A Multi-Task Perspective for Link Prediction with New Relation Types and Nodes

Reference 70

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unresolved
no resolver link, observed 2026-08-07T04:47:40.429016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:40.429016Z digest=sha256:75474f0fe41cc33add085070dc53029713520f694ea3fa0177acb4a126607f0b

Pith citing papers

Observation 5987d127-5c6d-424c-a47f-834f4bdf4e1d · inbound

TRACE: An Experiential Framework for Coherent Multi-hop Knowledge Graph Question Answering cites this paper.

TRACE: An Experiential Framework for Coherent Multi-hop Knowledge Graph Question Answering Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:51:03.038886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:17:59.538800Z digest=sha256:82f9ede2109f77a5a57f123e527770da3c6be61c4577af5a901b062581dac683

Observation 7ec901b1-96bf-48c5-bdc0-dc02a9199505 · inbound

PathISE: Learning Informative Path Supervision for Knowledge Graph Question Answering cites this paper.

PathISE: Learning Informative Path Supervision for Knowledge Graph Question Answering Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:06:26.161434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T04:35:49.207472Z digest=sha256:26d59bdd26507a46d9b0f34c7b01204e33d0724f27c69f898a0c75b554c640e6