An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation | Paper Citation Record

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This paper cites In: Mining text data, pp.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Mining text data, pp

Reference 1

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This paper cites Advances in neural information processing systems 22 (2009).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Advances in neural information processing systems 22 (2009)

Reference 2

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This paper cites Ldow@ www 144 (2015).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Ldow@ www 144 (2015)

Reference 3

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This paper cites JobBERT: Understanding Job Titles through Skills.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation JobBERT: Understanding Job Titles through Skills

Reference 4

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This paper cites IEEE Access (2025).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation IEEE Access (2025)

Reference 5

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This paper cites arXiv preprint arXiv:2504.13834 (2025).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation arXiv preprint arXiv:2504.13834 (2025)

Reference 6

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This paper cites Knowledge acquisition 5(2), 199– 220 (1993).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Knowledge acquisition 5(2), 199– 220 (1993)

Reference 7

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This paper cites Creating a Fine Grained Entity Type Taxonomy Using LLMs.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Creating a Fine Grained Entity Type Taxonomy Using LLMs

Reference 8

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This paper cites Pattern recognition letters 31(8), 651–666 (2010).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Pattern recognition letters 31(8), 651–666 (2010)

Reference 9

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This paper cites In: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Reference 10

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This paper cites In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Reference 11

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This paper cites In: Proceedings of the ACM Web Conference 2022.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the ACM Web Conference 2022

Reference 12

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This paper cites In: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track

Reference 13

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This paper cites Advances in neural information processing systems 36, 46534–46594 (2023).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Advances in neural information processing systems 36, 46534–46594 (2023)

Reference 14

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This paper cites In: ISS@ IT&I.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: ISS@ IT&I

Reference 15

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This paper cites In: Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Reference 16

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This paper cites gradient descent.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation gradient descent

Reference 17

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This paper cites Automatic Bottom-Up Taxonomy Construction: A Software Application Domain Study.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Automatic Bottom-Up Taxonomy Construction: A Software Application Domain Study

Reference 18

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This paper cites In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Reference 19

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This paper cites Advances in neural information processing systems 36, 8634–8652 (2023).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Advances in neural information processing systems 36, 8634–8652 (2023)

Reference 20

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This paper cites Communications of the ACM 57(10), 78–85 (2014) 8 E.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Communications of the ACM 57(10), 78–85 (2014) 8 E

Reference 21

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This paper cites In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Reference 22

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This paper cites In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Reference 23

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This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 24

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This paper cites In: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management

Reference 25

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This paper cites In: Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining

Reference 26

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This paper cites In: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation In: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Reference 27

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This paper cites {expertise}.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation {expertise}

Reference 28

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An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Hard worker

Reference 29

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An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Unresolved cited work

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This paper cites Do not return 3 different QIDs that all mean the same thing.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Do not return 3 different QIDs that all mean the same thing

Reference 31

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This paper cites React.js & Node.js.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation React.js & Node.js

Reference 32

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This paper cites English to French translation.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation English to French translation

Reference 33

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This paper cites Réseaux sociaux.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Réseaux sociaux

Reference 34

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An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation False Friends

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An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation {expertise}

Reference 36

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An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Unresolved cited work

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This paper cites Use all provided context (co-occurring skills, job categories, Wikidata info).

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Use all provided context (co-occurring skills, job categories, Wikidata info)

Reference 38

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An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation {expertise}

Reference 39

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This paper cites - Fallback to the Wikidata label if the usage-based terms are ambiguous, informal, or inappropriate.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation - Fallback to the **Wikidata label** if the usage-based terms are ambiguous, informal, or inappropriate

Reference 40

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This paper cites malt"‘: based on an existing high-usage profile expertise. - ‘.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation malt"‘: based on an existing high-usage profile expertise. - ‘

Reference 41

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Observation bb5be30a-17c7-44ac-ad2f-13a24dc83608 · outbound

This paper cites English to French Translation.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation English to French Translation

Reference 42

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This paper cites - If you modify or add to this identifier, use ‘&‘ (AND) for integrated practices, and ‘|‘ (OR) for independent traits.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation - If you modify or add to this identifier, use ‘&‘ (AND) for integrated practices, and ‘|‘ (OR) for independent traits

Reference 43

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Observation 1e2f7a4e-ac39-4058-ad97-95430d5bb971 · outbound

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An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Unresolved cited work

Reference 44

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This paper cites Prioritize usage counts, fallback to Wikidata, or synthesize a professional HR term if needed.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Prioritize usage counts, fallback to Wikidata, or synthesize a professional HR term if needed

Reference 45

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Observation 1d594ce8-0cfb-4a6d-8fae-fcebbbd41e5c · outbound

This paper cites malt"‘: derived from an existing profile expertise. - ‘.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation malt"‘: derived from an existing profile expertise. - ‘

Reference 46

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This paper cites - DO NOT assume these skills fit into their previous Wikidata QIDs.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation - DO NOT assume these skills fit into their previous Wikidata QIDs

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:28:57.707947Z

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Observation c9e44aa5-0f27-4438-aa78-33edd897ab67 · outbound

This paper cites - If a skill genuinely matches one of the provided Wikidata QIDs, you may use it.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation - If a skill genuinely matches one of the provided Wikidata QIDs, you may use it

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:28:57.690021Z

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This paper cites gemini"‘ for synthesized labels. - Set ‘source‘ to ‘.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation gemini"‘ for synthesized labels. - Set ‘source‘ to ‘

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:28:57.674470Z

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An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation - Use ‘rejection_reason‘: ‘NOT_A_SKILL‘, ‘SEMANTIC_MISMATCH‘, or ‘AMBIGUOUS‘

Reference 50

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This paper cites Social media.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Social media

Reference 51

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Observation d4ee1fbd-008b-46e4-a6a7-43610e4cb9fe · outbound

This paper cites Web Project Management.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Web Project Management

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:28:57.621640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 21b72b30-6724-427b-8e27-a90249df4ceb · outbound

This paper cites an unresolved cited work.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:28:57.602712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 88fbe318-16ce-4b24-b9ca-36312edacd77 · outbound

This paper cites Preferred Labels.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Preferred Labels

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:28:57.585620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6e9f78ce-878d-4f26-9f07-691833a00948 · outbound

This paper cites an unresolved cited work.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:28:57.569697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 47b6bbca-78a0-419a-b4a8-a197a39849be · outbound

This paper cites an unresolved cited work.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:28:57.551848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fa0a4eee-bd8c-4415-8ef4-b0e44116c01f · outbound

This paper cites an unresolved cited work.

An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:28:57.535608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers