Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-10T02:06:32.021051Z
Paper Citation Record · LEDGER
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning
As of 5 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 0 inbound Pith citation observations for arXiv:2604.19516.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
79 of 79 outbound references displayed
- verified exact24
- verified fuzzy37
- unresolved16
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 6ac9efe9-a9bf-4ade-a985-0cc724d1947a · outbound
This paper cites Aho and Jeffrey D.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Aho and Jeffrey D
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.962020Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0b8e9792-b82a-4ce3-8167-572bcd93d663 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T00:45:16.970890Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 42bf19b1-fd9d-43d5-b62f-0a48e2d16fd0 · outbound
This paper cites Chandra and Dexter C.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Chandra and Dexter C
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T02:06:36.456720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 6e2412ef-ce4d-4c19-ad24-1aceb63ef309 · outbound
This paper cites Scalable training of.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Scalable training of
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.942140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c5826416-23e5-44b4-84b0-d4a59778dffc · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T00:45:16.939581Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 59fe46be-a0d4-4ea9-8b13-4b4767b28d91 · outbound
This paper cites Tetreault , title =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Tetreault , title =
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.936924Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a4ce78f1-d502-4f76-86df-23f09aaed3ff · outbound
This paper cites A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data , Volume =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data , Volume =
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.927844Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 6f0a9d1e-f17e-4cac-b0fd-3914d12724ec · outbound
This paper cites Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages=
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.915262Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 76e970ed-2cc1-4fe3-9695-36304df204e8 · outbound
This paper cites 2025 , eprint=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning 2025 , eprint=
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.917822Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 24d8d8f1-d8be-4803-9ac0-d69f3bbd676d · outbound
This paper cites arXiv preprint arXiv:2510.11438 , year=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning arXiv preprint arXiv:2510.11438 , year=
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:16:05.664412Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation aad19c00-6e94-4bb7-be33-647046c56b17 · outbound
This paper cites A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:16:05.638106Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 40adcd3a-b303-4cf4-aa3f-b2a61692ad33 · outbound
This paper cites Future Internet , volume=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Future Internet , volume=
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.948210Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 5b15ea5c-7284-42aa-a72e-adcf1afcd676 · outbound
This paper cites Applied System Innovation , volume=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Applied System Innovation , volume=
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.906021Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4850a72d-8b6d-4391-9182-d56042e2f44f · outbound
This paper cites 2021 , eprint=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning 2021 , eprint=
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.909082Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 051cbe5d-3de0-4ca7-83e9-ea3c5808fab6 · outbound
This paper cites IEEE Transactions on Multimedia , year=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning IEEE Transactions on Multimedia , year=
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.899332Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b76d8609-9f71-4274-973c-5bd99a6ce5ec · outbound
This paper cites Journal of Sustainability, Policy, and Practice , volume=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Journal of Sustainability, Policy, and Practice , volume=
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.945018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ea36b907-37f6-4deb-9a31-74d3e37551de · outbound
This paper cites AI & SOCIETY , volume=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning AI & SOCIETY , volume=
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.896016Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 499dcf0c-e156-4b93-91f3-b468a15a7e56 · outbound
This paper cites Proceedings of the 30th International Conference on Intelligent User Interfaces , pages=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 30th International Conference on Intelligent User Interfaces , pages=
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.902900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9361233b-bb01-4f30-b349-e9e6e2a73800 · outbound
This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Reference 23
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-11T13:16:05.555351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 7b17e82e-275b-4ffc-8590-2ad1c1bb5e21 · outbound
This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.912242Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c9ee458a-a01b-4866-b33e-db4c15a4ccf0 · outbound
This paper cites Investment in Human Capital: A Theoretical Analysis.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Investment in Human Capital: A Theoretical Analysis
Reference 25
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T02:06:36.452176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ea344d62-ed4b-43c8-8795-a9640d2878ca · outbound
This paper cites Information Processing & Management , volume=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Information Processing & Management , volume=
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.920463Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e3bf2ee3-af87-46f5-82a3-007e26ea0ae8 · outbound
This paper cites 2025 , eprint=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning 2025 , eprint=
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.931031Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 80d4cd61-aab9-49b6-8ec2-e82aa1976933 · outbound
This paper cites Data Science and Engineering , pages=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Data Science and Engineering , pages=
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.956736Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 11a3d8c3-1ef0-48d0-aa0d-b8bb85ff1108 · outbound
This paper cites International Conference on Information and Communication Technologies in Education, Research, and Industrial Applications , year=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning International Conference on Information and Communication Technologies in Education, Research, and Industrial Applications , year=
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.877425Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cdddc4cc-bb2d-4264-9e04-e9acf0aa0480 · outbound
This paper cites 2010 , url=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning 2010 , url=
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.880669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 65b3758c-9946-4355-aa33-593ba92233dc · outbound
This paper cites Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) , pages =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) , pages =
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.887183Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a4fc942f-fca2-4c57-93b9-679c325d9ee8 · outbound
This paper cites The Twelfth International Conference on Learning Representations , year =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning The Twelfth International Conference on Learning Representations , year =
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.867340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cf6b2587-ef8f-4a09-bf11-46e987d31d84 · outbound
This paper cites Advances in Neural Information Processing Systems , volume =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Advances in Neural Information Processing Systems , volume =
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.870950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 365a82ca-a7d0-4b5a-b9ce-d3378bac6df1 · outbound
This paper cites Advances in Neural Information Processing Systems , volume =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Advances in Neural Information Processing Systems , volume =
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.874114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3f09fb2f-2442-4762-95cb-91af2c87cd21 · outbound
This paper cites Advances in Neural Information Processing Systems , volume =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Advances in Neural Information Processing Systems , volume =
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.853681Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3b2845e1-41cb-4337-8b13-59c14422a0ec · outbound
This paper cites Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages =
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.951456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0390bfbe-60d8-4175-a4d7-cb189d7c986e · outbound
This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages =
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.850169Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 56d2b18e-6afa-45d5-be19-26d3a4b79f97 · outbound
This paper cites Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages =
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.862205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 11b3d225-a6c0-455f-a29d-61f3bd9cf453 · outbound
This paper cites Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages =
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.889792Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 005344f5-79be-418c-b9b8-3117de426bbd · outbound
This paper cites Advances in Neural Information Processing Systems , volume =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Advances in Neural Information Processing Systems , volume =
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.841709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f829d08a-cffe-4962-8738-f7c7f04bd1e1 · outbound
This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume =
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.844592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cf7e4fe3-3bfd-42b6-8028-e9beda94dea5 · outbound
This paper cites Findings of the Association for Computational Linguistics: ACL 2025 , pages =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Findings of the Association for Computational Linguistics: ACL 2025 , pages =
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.884148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c6fdb45d-c0ae-4f90-985b-a0889a32b8f2 · outbound
This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages =
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.923173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ceae9b3f-853d-43dc-beb7-a34f52fe4c26 · outbound
This paper cites The Thirteenth International Conference on Learning Representations , year =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning The Thirteenth International Conference on Learning Representations , year =
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.847385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d902c500-c547-45bc-9a4a-57c9dec1ab31 · outbound
This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume=
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.892698Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation dbd81271-499b-4abf-9b6d-06e6c660a956 · outbound
This paper cites The Thirty-ninth Annual Conference on Neural Information Processing Systems , year=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning The Thirty-ninth Annual Conference on Neural Information Processing Systems , year=
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.934085Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 42cf2921-f901-4d04-b074-085e5b9047f8 · outbound
This paper cites AAAI 2026 , year=.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning AAAI 2026 , year=
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.954190Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1431dc23-9c5d-4864-8e31-7fdd674047f3 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 56
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T00:45:17.003424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e47a7b20-17e0-485b-b7b9-1788477a6450 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 57
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T00:45:16.988328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e3985b1a-ceaf-40ed-aef1-28c0795610cf · outbound
This paper cites Qwen Technical Report.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Qwen Technical Report
Reference 58
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:16:05.610686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4b5f6698-8e7a-4358-a2a2-3ddefa0e3ae4 · outbound
This paper cites Realmem: Bench- marking llms in real-world memory-driven interaction.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Realmem: Bench- marking llms in real-world memory-driven interaction
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:16:05.571384Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3aa94af1-899b-4311-8467-a6f1df4d08c1 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 60
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T00:45:16.991129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4dda8bd3-10e6-4e67-a413-162c8728b46b · outbound
This paper cites InThe Twelfth International Conference on Learning Representa- tions.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning InThe Twelfth International Conference on Learning Representa- tions
Reference 61
- Resolution
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- arxiv_id, observed 2026-05-11T13:16:05.582777Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0048e79b-c99f-4579-a5b2-b06fa219a371 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 62
- Resolution
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- arxiv_id, observed 2026-05-11T13:16:05.675347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2c5c11e2-4db4-44b8-8adc-5e26a5cb0268 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 63
- Resolution
- verified exact
- doi, observed 2026-05-10T02:06:36.461069Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c893cb71-4e62-4ef2-8e38-0b234d024303 · outbound
This paper cites Godlevsky, Sergey V.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Godlevsky, Sergey V
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T00:45:16.995052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ee91f16a-2095-45b0-a1f4-5b0d3b0ed533 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 65
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0ad3b89a-86fa-47f4-9bdf-242c69fc59ca · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 66
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2934aa20-4a49-477b-8c29-8d10693d0b08 · outbound
This paper cites Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , month = nov, year =.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , month = nov, year =
Reference 67
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 19d68ba1-7404-40b2-9cb3-cf37b8daa6d4 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 68
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 201b40e4-9d63-4dd7-95ab-3fe8f4ad405a · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 69
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c72342a1-751f-4922-bd0f-a559c65e95b2 · outbound
This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Reference 70
- Resolution
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- local_arxiv, observed 2026-05-11T13:16:05.621928Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 478dd819-792d-4e9a-ac61-a4dfec0c0905 · outbound
This paper cites Search-o1: Agentic search-enhanced large reasoning models.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Search-o1: Agentic search-enhanced large reasoning models
Reference 71
- Resolution
- verified exact
- doi, observed 2026-05-10T02:06:36.444471Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1c98693f-0453-443e-a337-0144efa286a8 · outbound
This paper cites DeepThink: Aligning Language Models with Domain-Specific User Intents.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning DeepThink: Aligning Language Models with Domain-Specific User Intents
Reference 72
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:16:05.523668Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c8da1c7a-57af-4f54-8f05-d236746bb7a3 · outbound
This paper cites In: Al-Onaizan, Y., Bansal, M., Chen, Y.-N.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning In: Al-Onaizan, Y., Bansal, M., Chen, Y.-N
Reference 73
- Resolution
- verified exact
- doi, observed 2026-05-10T02:06:36.442196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1fba506e-8248-4f15-96c8-f162c8092112 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 74
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ade73cf3-9444-44a4-8ead-5eb6195b17f6 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 75
- Resolution
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- arxiv_id, observed 2026-05-11T13:16:05.689801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d54e6c8c-2e20-461f-8b6a-ba6f1830257d · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 76
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ab93c1f9-8a29-43b6-b89b-d5b0bbe6ade7 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 77
- Resolution
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- arxiv_id, observed 2026-05-11T13:16:05.629106Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1f6ffa65-d74a-489b-baf7-6d561c20a102 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 78
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 606c1ccb-13c2-4e9c-bc01-f122ba53265d · outbound
This paper cites In: Duh, K., Gomez, H., Bethard, S.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning In: Duh, K., Gomez, H., Bethard, S
Reference 79
- Resolution
- verified exact
- doi, observed 2026-05-10T02:06:36.447928Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation dc01f2c2-f0e2-498d-b603-c5826287f1da · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 80
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b4a8ca2d-682e-4ca1-9c0a-959b74543d15 · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 81
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 06315069-3d89-4618-b71e-2862dee0b450 · outbound
This paper cites Gemini: A Family of Highly Capable Multimodal Models.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Gemini: A Family of Highly Capable Multimodal Models
Reference 82
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:16:05.645132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 6319c846-093f-4d0c-9216-4e8f73378453 · outbound
This paper cites R3Mem: Bridging memory retention and retrieval via reversible compression.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning R3Mem: Bridging memory retention and retrieval via reversible compression
Reference 83
- Resolution
- verified exact
- doi, observed 2026-05-10T02:06:36.438182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3b8b9a5f-5ff0-4519-a0d2-d661feef394b · outbound
This paper cites Concise Reasoning, Big Gains: Pruning Long Reasoning Trace with Difficulty-Aware Prompting.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Concise Reasoning, Big Gains: Pruning Long Reasoning Trace with Difficulty-Aware Prompting
Reference 84
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:16:05.593124Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 130242f2-8a80-48b1-9612-da4b39d85c9c · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 85
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T00:45:16.964647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f49b6de8-223e-4b49-8730-5087dd4257ad · outbound
This paper cites From what to why: A multi-agent system for evidence-based chemical reaction condition reasoning.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning From what to why: A multi-agent system for evidence-based chemical reaction condition reasoning
Reference 86
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:16:05.543133Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c90c3c4b-ef34-483a-a860-236123f7a617 · outbound
This paper cites ACE-Router: Generalizing History-Aware Routing from MCP Tools to the Agent Web.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning ACE-Router: Generalizing History-Aware Routing from MCP Tools to the Agent Web
Reference 87
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:16:05.604765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 35e05bbf-fe79-4432-b1f8-d71d272fad99 · outbound
This paper cites Dual Latent Memory for Visual Multi-agent System.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Dual Latent Memory for Visual Multi-agent System
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-06-08T02:03:51.273031Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 85cbb3c0-ba0d-4696-b2a5-54ade10fce3f · outbound
This paper cites InAdvances in Neural Information Processing Systems, volume 36, pages 11809–11822.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning InAdvances in Neural Information Processing Systems, volume 36, pages 11809–11822
Reference 89
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:16:05.534042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1ffe4c6e-a83b-4e94-b18e-493f2740d00c · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 90
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T00:45:16.967102Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ff2999eb-088d-4464-88ac-1ced522aa9ea · outbound
This paper cites an unresolved cited work.
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning Unresolved cited work
Reference 91
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T00:45:16.959327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Pith citing papers
No inbound Pith citation observations are available.