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Paper Citation Record · LEDGER

GenPlanX. Generation of Plans and Execution

As of 18 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2506.10897.

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

pith.paper-citation-record.v1
2506.10897 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:18:26.895953Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

  • verified exact2
  • verified fuzzy31
  • unresolved11
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b1f3f2a8-383b-4640-a92f-29790d84f0ed · outbound

This paper cites Ai-Chang, J.

GenPlanX. Generation of Plans and Execution Ai-Chang, J

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:37.014742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:21.513332Z digest=sha256:cb3f556f138e2ec4fa55e48b94528b86812f6cf898e6c98d890471ca3257c632

Observation 1f436ac4-6753-4198-bf69-d4be7c5973ce · outbound

This paper cites Learning action models with minimal ob- servability.Artificial Intelligence, 275:104–137, 2019.

GenPlanX. Generation of Plans and Execution Learning action models with minimal ob- servability.Artificial Intelligence, 275:104–137, 2019

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:36.766793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:21.572669Z digest=sha256:0f59240c5521465eada014573d2c65cfddbe5b4453e48b0334bae7606bd471dd

Observation f5e348dc-fef7-44b5-9dd4-57f4d7f6f790 · outbound

This paper cites an unresolved cited work.

GenPlanX. Generation of Plans and Execution Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:18:36.422485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:21.689239Z digest=sha256:c026bcd78e98a11dadf8760ab7106742edcaa82a5dda52a6834bc4db0991ea8c

Observation a1a329ff-c0a0-4562-b982-bac18ce8f9e9 · outbound

This paper cites Language models are few- shot learners.Advances in neural information processing systems, 33:1877–1901, 2020.

GenPlanX. Generation of Plans and Execution Language models are few- shot learners.Advances in neural information processing systems, 33:1877–1901, 2020

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:36.085212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:21.805671Z digest=sha256:4c6fcef0f3e7176808c95c78386edfa242bfd1e2b3f340ef5a7ea1edc03a17a7

Observation b26ef753-16ba-49aa-b39b-98b6827e75ab · outbound

This paper cites A multi-agent architecture for intelligent gathering systems.AI Communications, 18(1):15–32, 2005.

GenPlanX. Generation of Plans and Execution A multi-agent architecture for intelligent gathering systems.AI Communications, 18(1):15–32, 2005

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:35.784166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:22.004231Z digest=sha256:2de320f7222393f35124a5968bcd8a286ba40b493434606b4de4324cd2cbaa4f

Observation 464cb809-3f9d-4096-bd38-e16490efad72 · outbound

This paper cites Planning for tourism routes using social networks.Expert Systems with Applications, 69:1–9, 2017.

GenPlanX. Generation of Plans and Execution Planning for tourism routes using social networks.Expert Systems with Applications, 69:1–9, 2017

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:35.486127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:22.158822Z digest=sha256:1da8e62f63c60e5cd970a5ada2e6d1be7698875333bdf7b4d8e0240cc06617a1

Observation 0bcd3236-edbc-4572-a101-b3d9b675ba59 · outbound

This paper cites TRIP-PAL: Travel Planning with Guarantees by Combining Large Language Models and Automated Planners.

GenPlanX. Generation of Plans and Execution TRIP-PAL: Travel Planning with Guarantees by Combining Large Language Models and Automated Planners

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:22.268334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:22.268334Z digest=sha256:1f36aa9ef4c1e22335d79e0e14a5c0f9f7e528b1adb326319eb3a49bd1c3fde2

Observation 8239b767-14f1-4011-9cc8-d1494de7dc4b · outbound

This paper cites Etzioni, S.

GenPlanX. Generation of Plans and Execution Etzioni, S

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:35.217739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:22.393882Z digest=sha256:b43d00c773ff4ea6bf4278cd8ac7440925a3a42763561124f802d90eed93ab1f

Observation a0df749a-9d3b-43a5-9fe0-4313df39396a · outbound

This paper cites Assisting data mining through automated planning.

GenPlanX. Generation of Plans and Execution Assisting data mining through automated planning

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:34.984991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:22.528332Z digest=sha256:dc593985a4e89263d800909c77ba1f08395d14dcaaf15a12a95729f8419a7b87

Observation 4755e800-2ae3-4591-b3bc-bf5a6cd64b08 · outbound

This paper cites Anticipation of goals in automated planning.

GenPlanX. Generation of Plans and Execution Anticipation of goals in automated planning

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:34.662947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:22.662723Z digest=sha256:8342553890ea4a2027b5664b74ccce34e8b99ad8d82c2fbbe3627cd871fd4b70

Observation fdd0e89d-8588-4215-80ed-774f44f80b06 · outbound

This paper cites Florez,´Alvaro Torralba, Daniel Borrajo, Carlos Linares-L´ opez, ´Angel Garc ´ ıa- Olaya, and Juan S´ aenz.

GenPlanX. Generation of Plans and Execution Florez,´Alvaro Torralba, Daniel Borrajo, Carlos Linares-L´ opez, ´Angel Garc ´ ıa- Olaya, and Juan S´ aenz

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:34.324595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:22.779642Z digest=sha256:2112f7519030035243116f5583340b3adfad53d03cf5687e6098e8a3cb932ca8

Observation 82d001c1-741f-4d59-a35e-944b00b326dd · outbound

This paper cites Ghallab, A.

GenPlanX. Generation of Plans and Execution Ghallab, A

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:34.032692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:22.935838Z digest=sha256:f48ef86f666c72495d6dee08ac621bc7a57f34a8557ddbee9235892758240f03

Observation 25142c9d-a794-43bb-a89d-6ca35d8d5cb7 · outbound

This paper cites Access Online via Elsevier, 2004.

GenPlanX. Generation of Plans and Execution Access Online via Elsevier, 2004

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:33.689086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:23.084202Z digest=sha256:4cc9ddbbe745de05ab19ea3cb7451a0b2abdb171f12056e90b15507af05a4d28

Observation 7e41d61b-967d-4066-b292-0d798e002583 · outbound

This paper cites A planning approach to repair domains with incomplete action effects.

GenPlanX. Generation of Plans and Execution A planning approach to repair domains with incomplete action effects

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:33.402349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:23.197979Z digest=sha256:4c72750bd7d3370237eb3637dd7e255aeaf7b88ab969186625a6fa698c10a5f5

Observation 5121e8cf-f9e3-45c9-8e25-e784205114ae · outbound

This paper cites Leveraging pre- trained large language models to construct and utilize world models for model-based task planning.

GenPlanX. Generation of Plans and Execution Leveraging pre- trained large language models to construct and utilize world models for model-based task planning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:23.336995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:23.336995Z digest=sha256:4b526e83536e50d87f24d8f954c2d24521820e78da1ed680b999e6230b9b5612

Observation 7c65219a-a279-424b-aaf2-af2f90659941 · outbound

This paper cites Transformers for natural language to structured planning: Integrating domain knowledge.

GenPlanX. Generation of Plans and Execution Transformers for natural language to structured planning: Integrating domain knowledge

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:33.110826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:23.434485Z digest=sha256:4c383f1b3c8b6e0046b61c8c2454ac201204153ebcc4aa236a4aaf657989a94f

Observation 25116e41-2296-4851-84ef-b3134caf24fa · outbound

This paper cites Building a domain-independent architecture for planning, learning and execution.pelea.

GenPlanX. Generation of Plans and Execution Building a domain-independent architecture for planning, learning and execution.pelea

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:32.854386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:23.563013Z digest=sha256:1bcd157fa37ac256d7f50d5e6aa1f0919db9e029547c6c7217950f2c03399048

Observation 30266ffc-e13e-4c91-8732-1f34623e0f1d · outbound

This paper cites The fast downward planning system.Journal of Artificial Intelligence Research, 26:191– 246, 2006.

GenPlanX. Generation of Plans and Execution The fast downward planning system.Journal of Artificial Intelligence Research, 26:191– 246, 2006

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:32.594831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:23.738364Z digest=sha256:f7d2d7dfbee80b2ced1a2d98bb593bcc6c98cb7c150fdae2db79aedf0facb42f

Observation 7a7ad816-a8a1-4b66-bb6a-03383c61bc35 · outbound

This paper cites Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents.

GenPlanX. Generation of Plans and Execution Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:23.897927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:23.897927Z digest=sha256:918e04be85b583029f6d16510fb381923106a74f4d4c0ab219f14b1fe2d202b6

Observation 99c2cda3-4e2e-49cc-8ba0-2d0081f64d95 · outbound

This paper cites LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks.

GenPlanX. Generation of Plans and Execution LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:24.013731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:24.013731Z digest=sha256:0ed4c3a6c4bd6ce86cf26f7d58bd93f983ae034c9f82282a0bcc6bfa11456509

Observation 154208a7-9451-4bc9-98e4-8ae751c5e52e · outbound

This paper cites Advanced messaging platform (amp): Pipeline for automated enterprise email processing.

GenPlanX. Generation of Plans and Execution Advanced messaging platform (amp): Pipeline for automated enterprise email processing

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:32.358728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:24.176109Z digest=sha256:9e5312d3725b75d67556f4f02198ecd71ae9a264d31e96bb158efd71c58a7383

Observation d4a4926e-037a-4771-9f1d-52b62b9d7cc2 · outbound

This paper cites Elevator control as a planning problem.

GenPlanX. Generation of Plans and Execution Elevator control as a planning problem

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:32.085393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:24.332281Z digest=sha256:0541aa9bc7bd33fd9a2adca63c842feccd07e9454220628ba66466dcd852441b

Observation e40a24eb-3f2b-4619-ab15-6d9d345167d2 · outbound

This paper cites LLM+P: Empowering Large Language Models with Optimal Planning Proficiency.

GenPlanX. Generation of Plans and Execution LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 23

Resolution
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no resolver link, observed 2026-08-07T04:18:24.467715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:24.467715Z digest=sha256:6088893e399f46188e641249f43e017470b6f25c7f44fee3c2ca53e01268416b

Observation 5dcf9f16-7249-48ab-bc57-9ad829d95321 · outbound

This paper cites Unified planning: Modeling, manipulating and solving ai planning problems in python.SoftwareX, 29:102012, 2025.

GenPlanX. Generation of Plans and Execution Unified planning: Modeling, manipulating and solving ai planning problems in python.SoftwareX, 29:102012, 2025

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:31.797143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:24.581760Z digest=sha256:c5a2754b5c2d05faa3eac0a34d130eb36b91bd3089aacaa42e411e5fb10feb71

Observation 30425c6d-da13-48fc-9427-3199309372f4 · outbound

This paper cites On Learning Action Costs from Input Plans.

GenPlanX. Generation of Plans and Execution On Learning Action Costs from Input Plans

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:24.645694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:24.645694Z digest=sha256:42965fbc13bab937827f76a8bca06932ab87fb5cc528340803fe25f04e60e306

Observation c01143d0-751c-47f0-a1e0-fe5669815ff9 · outbound

This paper cites Nocturne: A scalable driving benchmark for bringing multi-agent learning one step closer to the real world.

GenPlanX. Generation of Plans and Execution Nocturne: A scalable driving benchmark for bringing multi-agent learning one step closer to the real world

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:31.555003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:24.714267Z digest=sha256:e126149ce2d843d91a66e1929e218f3fcc92e425f5db511bdcfeeee895760127

Observation cd7d30cd-70d0-4dcc-9051-674dd4cb19b8 · outbound

This paper cites Aha, and Elizabeth Carter.

GenPlanX. Generation of Plans and Execution Aha, and Elizabeth Carter

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:31.324086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:24.808879Z digest=sha256:9b81aa3fb9c0f14b1c260dc9b54973c140d243f8e66e8b637b0f24faf22dbf19

Observation abc4f660-149c-42d1-9cf3-50c3d21fd758 · outbound

This paper cites Pandurang Nayak, Barney Pell, and Brian C.

GenPlanX. Generation of Plans and Execution Pandurang Nayak, Barney Pell, and Brian C

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:31.023145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:24.937136Z digest=sha256:0285ab52f90a1f0d0eaf005b13b78721534f27f6590b564becc5c66df8aa7114

Observation bdaaa968-7bcb-4fb0-b5e3-191cbf910f85 · outbound

This paper cites Using copilot in microsoft 365.

GenPlanX. Generation of Plans and Execution Using copilot in microsoft 365

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:30.793407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.089714Z digest=sha256:8c3c7c7d2da2df0da9b21a8a922684f7e681f0d1756a102cf5648ad8b2735943

Observation c87ac690-492a-49ec-a9f3-bd61ea1b7d25 · outbound

This paper cites Large language models as planning domain generators.

GenPlanX. Generation of Plans and Execution Large language models as planning domain generators

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:30.498537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.197773Z digest=sha256:914f372ef96f4fb435d5ea6b7ba00386eca9abc3b7db24a1a0593ae539b6d1ab

Observation 8f49f538-b6b6-4e8f-97dd-24d4f7b1c32b · outbound

This paper cites On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS).

GenPlanX. Generation of Plans and Execution On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:18:27.325493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.300132Z digest=sha256:f86a9cf3c93002efcdfcfaf0c700ebf398a82c779eb46010116f8c1e55db58c2

Observation 360ac301-d071-4715-9c6f-ded6fa0440b5 · outbound

This paper cites Using online planning and acting to recover from cyberattacks on software-defined networks.

GenPlanX. Generation of Plans and Execution Using online planning and acting to recover from cyberattacks on software-defined networks

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:30.137189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.371431Z digest=sha256:cbe7f75c63c4f5999b523d1a7a5c24283567d8b9662e6793594213faac427f5a

Observation f2f2c014-709f-4bfe-8dce-40a4bb8b0101 · outbound

This paper cites Generating replanning goals through multi- objective optimization in response to execution observation.

GenPlanX. Generation of Plans and Execution Generating replanning goals through multi- objective optimization in response to execution observation

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:29.858032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.438312Z digest=sha256:b126329b238409c17a98892f7dc537776c515a6978209d7937b0cd826f94a5ef

Observation b3f3a8c3-0d6b-46fb-b898-ff82013120ae · outbound

This paper cites Learning-driven goal generation.AI Commu- nications, 31(2):137–150, 2018.

GenPlanX. Generation of Plans and Execution Learning-driven goal generation.AI Commu- nications, 31(2):137–150, 2018

Reference 34

Resolution
verified exact
doi, observed 2026-08-07T04:18:27.124385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.562549Z digest=sha256:e9291060eb23b95225510d623507729d72134ede4e1734cb4472797206e54165

Observation 26d03777-3987-48e0-8f9f-c87d7552f04f · outbound

This paper cites Computing planning centroids and minimum covering states using symbolic bidirectional search.

GenPlanX. Generation of Plans and Execution Computing planning centroids and minimum covering states using symbolic bidirectional search

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:29.629088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.657882Z digest=sha256:b966d6c6752ca91b2cca95fea6f477ce7ea18854a014998d45cc90c31c9d6b90

Observation 49347653-2757-4056-9298-6af497f04e00 · outbound

This paper cites Adapt: As-needed decomposition and planning with language models, 2024.

GenPlanX. Generation of Plans and Execution Adapt: As-needed decomposition and planning with language models, 2024

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:29.401982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.754775Z digest=sha256:a60471caaa7c0a7b7ffca08a258bf46da6f6cec3ec30b951c332a0843985279b

Observation 77450e8d-0d26-4c4c-b476-0216158077d5 · outbound

This paper cites Integrating plan- ning and scheduling in workflow domains.Expert Systems with Applications, 33(2):389–406, October 2007.

GenPlanX. Generation of Plans and Execution Integrating plan- ning and scheduling in workflow domains.Expert Systems with Applications, 33(2):389–406, October 2007

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:29.106632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.889919Z digest=sha256:95579bc8571b6e9c3ae835b27de6bc06e29907165f3e7382f2ae73ea3de6f868

Observation 339c74ad-faa3-4b7e-9513-ae3f92e2b09c · outbound

This paper cites An AI planning- based tool for scheduling satellite nominal operations.AI Magazine, 25(4):9–27, Winter 2004.

GenPlanX. Generation of Plans and Execution An AI planning- based tool for scheduling satellite nominal operations.AI Magazine, 25(4):9–27, Winter 2004

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:28.787284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:25.998561Z digest=sha256:c149c672309611ca8f729e492b2198921e437c409ba97e834e0a5c354f9c82da

Observation a53c1901-4a47-40f5-b894-a4750b7407a1 · outbound

This paper cites Twostep: Multi-agent task planning using classical planners and large language models, 2024.

GenPlanX. Generation of Plans and Execution Twostep: Multi-agent task planning using classical planners and large language models, 2024

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:28.438246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:26.106314Z digest=sha256:5885d5ddf5958557e06268e46cca8f336060301f55a1ae22408fba50f9f9874f

Observation f0f66fe8-7800-49fc-9c59-0662d853c68a · outbound

This paper cites Automated composition of semantic web services into executable processes.

GenPlanX. Generation of Plans and Execution Automated composition of semantic web services into executable processes

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:18:28.053444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:26.224364Z digest=sha256:dd2b642503f3c7b0a2d2defffb439737aa0396ae8b6df9694cc766840085fadc

Observation 3f61024a-0ca6-4b6f-a3fe-7ec72afc538f · outbound

This paper cites PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change.

GenPlanX. Generation of Plans and Execution PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:26.474007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:26.474007Z digest=sha256:beecb7bba2e8a6356783e59883424cf30e174187b41cc0a2da06ac30f6c92552

Observation 2297629f-418e-49a7-89dc-5797796f9295 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models, 2023.

GenPlanX. Generation of Plans and Execution Chain-of-thought prompting elicits reasoning in large language models, 2023

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:26.542943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:26.542943Z digest=sha256:5471e17485a8a7b9c3999dcf7ac832dac2ff651c90bcba22de15f1089513b480

Observation 8f36e09f-21fe-4850-ae24-eb602db117bb · outbound

This paper cites Griffiths, Yuan Cao, and Karthik Narasimhan.

GenPlanX. Generation of Plans and Execution Griffiths, Yuan Cao, and Karthik Narasimhan

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:26.633772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:26.633772Z digest=sha256:adb4f77c7b90669421c044ac35d0155e789fd9ddddaa1558d9c765670d9bc783

Observation 9cb82c97-2327-4e21-b066-980d8d1c6c6d · outbound

This paper cites React: Synergizing reasoning and acting in language models, 2023.

GenPlanX. Generation of Plans and Execution React: Synergizing reasoning and acting in language models, 2023

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:26.768815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:18:26.768815Z digest=sha256:be5e531d323dc0d6c1f771c76c6bacba6e73019a363c5c5e146b0b1c87313bd4

Observation 3c149eb8-1892-4d04-8896-a55a59a63081 · outbound

This paper cites type": "text.

GenPlanX. Generation of Plans and Execution type": "text

Reference 46

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T04:18:27.693739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:18:26.895953Z digest=sha256:30271e585dafd741f0f8c13920b1e36466523540201ae2d48070a4de3bd832b8

Pith citing papers

No inbound Pith citation observations are available.