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Paper Citation Record · LEDGER

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

As of 13 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 2026-08-13T06:32:02.005865+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

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source=pdf_text observed=2026-08-07T04:47:35.512929Z digest=sha256:274ecdca0424c746aa488c970ff84a5739ccacd9d96d174cbfe79c53dc6eaed6

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=sha256:6ae341c6e303d75a3f85fceaaa057735c138306ad4a50fd80b0d90e94dad6e5d

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=sha256:099678e75290374575e76ff16347003e9825e90e4e51b014ede288ea25e286eb

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=sha256:6ed681802464fd5a142c32030f4a771e691c822fe2afa07306f818f73ae43250

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=sha256:253397b6ebaaeb7ad019a2adf4f08da5cd22bb9fd5063d9647ca70661f7b264f

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:35.761632Z digest=sha256:2a34165926a8cc9a45baf0379ceca16269d7db3cf4dce04b61bb31ec9e89d6c4

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:35.794225Z digest=sha256:00a54e643a58938851c491356c8572fe80d18d2fff73474d8239d2b96cfb5766

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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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:35.818932Z digest=sha256:57c3a7731b6507962d4553939d0e53abc909db3ea37cc4fa1414ac918efc27ba

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=sha256:7222f28015c90489b047fee0a39bf83a92233c95f4287953eec77bcafe67c1e1

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=pdf_text observed=2026-08-07T04:47:35.961960Z digest=sha256:9e61082e83a8d44d3bde5b800d22666b8a070054b76d08baa08e6d5258ebe571

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:a01bf576c50441c3b5e9653079879d07878a032cc434ae84566e3b1afaec4d55

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=pdf_text observed=2026-08-07T04:47:36.115558Z digest=sha256:3ddfb3497be9651cf03f45430e607205cc202ec740c9f32c364dcfc6d48677bc

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=sha256:2b76c3d1ca7546cfebeecd1269b4672a97605ebd2ccf2cd4b590de65d7655995

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:e6bd7103f5cb61476ef1669844b86026080d7c280504ac5ed9bf7c79a016659d

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:36.324084Z digest=sha256:52e56a4322212fe5edd97a533c42a275f227d6293e63c6eb1c4a687f643fd6cd

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:36.420767Z digest=sha256:910836b2cbf1a0fe22a3655a9e3bd09c3b6107964c41cd4b8b6a665e2dcb89b8

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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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:36.470357Z digest=sha256:b24981d06f69f2cd8b4f36e860bffc434464758c7337220d808afcb349da6856

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:36.580762Z digest=sha256:1e350ce99510b6f376e4efa050779c2604964c5925ad756dfc51935e6c662d55

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=sha256:109cc8a03df04acc32b968802ec5a18f297b7fd44aa9de80713628daed26f4b2

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:36.687834Z digest=sha256:1cff130c5e3bf1f6ea9e35eecbb8efa521b5469310d7f3588a018921edde4e96

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:af03b6b34a142ebeda6d1a14215e71a77f5d7d245d3a7ee11fdec55b8fbd5b11

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=sha256:9a9c01d7eff0281d71135c4e2813cbf585e3873c0ef3f3dc2711ca6d9477c841

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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source=pdf_text observed=2026-08-07T04:47:36.908428Z digest=sha256:fee703eaf0c78e21ef3bb7307a5f4c773aa6f0d504e6f9901a1bf94b767af69b

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:36.964423Z digest=sha256:0a6441fe625ef3f49be808e5ead89b61267c82011bb7c2979a58ce5a79f26b16

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=sha256:8fdb5ce7892ea8ebfd356c260ff1e6ecf9b6feb999730ae3d23cc4f87c93ce71

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:37.092663Z digest=sha256:a912979f4dce0d2490337638375b638c97c5a9750b4bba9f2caad8d4cc7f8ebc

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=sha256:1f6387874224c48f5f259fe9713c2d07c3c1128717b92a6a49926603cb499585

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:37.247319Z digest=sha256:dfc511d95d61bfcb6acc2f4abe84caab0d193641bf78fff9ac3ec47a07efe3c6

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:37.302694Z digest=sha256:8211794341d5eb3c1bba1660de21ddcd31ddf2ff65fcb774871d995d8bba9b00

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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source=pdf_text observed=2026-08-07T04:47:37.354968Z digest=sha256:12d41479a692ff3428442217ceb91c3bac39db8a7e4e163f60f46ba9cc36cf57

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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source=pdf_text observed=2026-08-07T04:47:37.399355Z digest=sha256:2ea79c6af88079255342e3d62971eb90929e6b68f9de0272fbbf23ba5472cf1d

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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:37.444395Z digest=sha256:3adb129987d363ececcab2d0947d1380baf781819013f7289c1ee4b8acad3846

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:c6b2fc6d4f113a97e3b679bbfd2c9be29f07e8da2c09a3b097d6593ed9621e17

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:fa78eef1ea9865f957d493ab54b6c8a6c7c9119e70ee6bfffe259ce56f5acde6

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:37.627052Z digest=sha256:349e1789c572c2c7bd4005e6124155ad5bb7d217029989018883dd7956ca484f

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:37.682852Z digest=sha256:459adc9fd40394f6a7cc499453cb71c5c9a414d9d7047e6cc21d368f39f4a9b5

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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no resolver link, observed 2026-08-07T04:47:37.719430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.719430Z digest=sha256:206b605f356aae7ba75e7b01f4fd562b487c5977facc552493b1241d0b3e9614

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

Resolution
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no resolver link, observed 2026-08-07T04:47:37.757564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.757564Z digest=sha256:f422ee779599f63b17aa9719b2ff03c6ef989f724d821680d37e80bac4f723f2

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:37.834534Z digest=sha256:1e4a71b082d2d3d5953c3f80857b029584675fc83d5ec0e205a3c2e7af9ef78d

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
unresolved
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=sha256:1b11c1c4129e104761c88d441d76f700ee4b513844f21a5823410b0659b7cc96

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:37.974407Z digest=sha256:b8270b0433a279da279ce897d748b155c1250fde81610ad0278fbcba66ac295a

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=sha256:5e99a2437fd050799bbf267568986f6485ba530a90f6e58db4b568b605b7ae89

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:38.106561Z digest=sha256:44eb6dcbd1d21e17fb14a424f801a5f9ebc53077016a020d007e1c76a102d8c1

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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no resolver link, observed 2026-08-07T04:47:38.174391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:38.174391Z digest=sha256:6ea9c5d30cb33ae2637b1ad8c52e69d474d66b8fe8d15386cc4cc635cdc15360

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:38.226132Z digest=sha256:561ccc900f79b373bc7c5b44de1b1acbfc0f3e551d6e822079a5a68f7b364d28

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=sha256:56b5f14afb36cb432c2686b8adf9d82ffd470cb1d304f9eeec6042d28ea2f013

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:38.354887Z digest=sha256:fbac9b28dd55589270a327bed33d9d0bba79cb88b8485bf464f911b590ed79f2

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:c4387ec8d2bf869a3ec1cc13c452b2aa1b9f3255c7c4c9e7796ef1e3bdfd8b76

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:fd6809e48e6961cd0da9ccf2be2ad081e1e9b4ac5e484b0eafb622c882b18955

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:38.513260Z digest=sha256:7416429f5627e46f377fad6f1c72bb314da6d3d24fb1ebd1ee9bb2afa6c0ce4e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:38.562263Z digest=sha256:addca07f6eec97ff39644e08ae0593021771ec241c248b4d4c23c95a0fc9f2a9

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

Resolution
unresolved
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=sha256:7d7f92617dab07528ada05bd608af2028ec548a5101fb95d308ab97562145e6f

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:38.689683Z digest=sha256:b418de834c26e58fae1d3b487ab70bf156cd93cf1d9b29efc9d1fcc884da1338

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:38.759559Z digest=sha256:65301b684e5916f626fb48ad8b6d0fc1313811ac2f356e333114323b8026245d

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

Resolution
unresolved
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=sha256:5468d19394335d0091bcffadf4d3c5028adc6de6ea7080b34045d9af9eb378d1

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:b13d05fb1ea74c5328d0513b1eab4a1e7fc9ea59dfab7e3c41a5608ea947a127

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=sha256:2c55fc7faee6f78c8a183f44302ea8de7d45410ed33648c64dfc1c3f7b8e325a

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
unresolved
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=sha256:4e334175704a75dc709515d3f3cf51375180f86da322130ded58708ef74ad890

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:39.118607Z digest=sha256:80c71837551f6fc364d17a5e28a6cdf77cf4b505e4e1b8f3128c707e55a140d9

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:39.250700Z digest=sha256:50d6e5348326e8dc4d9e8349c093a2161e5aa060264ba7977abf31247e3f4579

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

Resolution
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=sha256:40c23784e5dbea580e479602fbd8ed7ad3fe9f453c109b3e3bd3e82327578939

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:39.435851Z digest=sha256:a7492dd201e1da7d13246060715de097f94ab2c6e26746d321f3a4c1ea50bd04

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:39.614841Z digest=sha256:20c041e919e868f74d0f3307c835867ed9ee9fcb1c27171fbd7e8b921cb59d3e

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

Resolution
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=sha256:5e1c62815155c33c781495ffaba408465871c0a5868d684cd16da4ea18a26a82

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

Resolution
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=sha256:0225396bd33dfc0f10462b91d6fbfce4412cd95a750d14bdfe92a3fba93f1390

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:39.987320Z digest=sha256:54a114e5e9eb4e2ced7390743f84a992332f721b24ee86de81e7363210cb3ae4

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:40.097440Z digest=sha256:a233b8fb3936d5e2687bb9091bcd103c4b478cededa545027898738fbbab8c41

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T04:47:40.225987Z digest=sha256:60bafd671faeffb929aa5febc021af93954621266d6e09579a916fab27d89491

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

Resolution
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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=sha256:0882c9cfd71884e30eaef39c2ee6a6c4b403c5b0f621d9156af11c3195584842

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

Resolution
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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:d95e5057061702f082d0cf681d10e41f3dda3365a50d3c4927461d96b71f2191

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T15:17:59.538800Z digest=sha256:be37b55aaee94cd412e02b0ac68657e00493f948a3d2956c8e3640ffc15b41b5

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
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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-12T04:35:49.207472Z digest=sha256:bd4cea596fa4b4e5c06064d95ffcc5c3b3ba3b721510461ca0aa46e473ce1844