Paper Citation Record · LEDGER

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search

As of 17 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2506.07062.

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

pith.paper-citation-record.v1
2506.07062 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:48:02.078916Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

18 of 18 outbound references displayed

verified exact0
verified fuzzy12
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a035ee80-fecc-4c68-a461-fc85a927300a · outbound

This paper cites (2022) Do as i can, not as i say: grounding language in robotic affordances.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search (2022) Do as i can, not as i say: grounding language in robotic affordances

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.332077Z

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 7e722757-fdd7-4964-bb79-cd0372df55ff · outbound

This paper cites (2021) Rhh-lgp: Receding Horizon and Heuristics-Based Logic-Geometric Programming for Task and Motion Planning.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search (2021) Rhh-lgp: Receding Horizon and Heuristics-Based Logic-Geometric Programming for Task and Motion Planning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.308981Z

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 1d8315ec-4cff-41d3-a93a-ac9acf6355f1 · outbound

This paper cites (2011) Continuous upper con ﬁdence trees.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search (2011) Continuous upper con ﬁdence trees

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.284697Z

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 453ff003-2cdd-4404-80e6-c13794c7c915 · outbound

This paper cites Therefore, if the grill is placed ﬁrst, it prevents the robot from placing another object (red can in the hand) in the region.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search Therefore, if the grill is placed ﬁrst, it prevents the robot from placing another object (red can in the hand) in the region

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.296283Z

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 ec03fac1-3693-4ae3-95cb-09c2bd58f373 · outbound

This paper cites Washington, DC: The Association for the Advancement of Arti ﬁcial Intelligence.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search Washington, DC: The Association for the Advancement of Arti ﬁcial Intelligence

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.259174Z

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 ed877441-c8e5-436a-9408-4770b1eaa7d4 · outbound

This paper cites Washington, DC: The Association for the Advancement of Arti ﬁcial Intelligence.

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.245761Z

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 b6113536-2ea6-4a4a-9812-9e2d0b5f246f · outbound

This paper cites (2023) Learning efﬁcient abstract planning models that choose what to predict.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search (2023) Learning efﬁcient abstract planning models that choose what to predict

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.232349Z

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 e1de5f07-141a-45e8-9adc-340d6e3952c9 · outbound

This paper cites In: The Conference on Lifelong Learning Agents, Pisa, Italy, 29-1 August.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search In: The Conference on Lifelong Learning Agents, Pisa, Italy, 29-1 August

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.219283Z

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 afe3aae5-1dd9-4a89-92b8-934aae73e42d · outbound

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

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:48:02.053445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f08e57d-b66d-4a04-97ba-6ba0ddac983b · outbound

This paper cites (2022) Con ﬂict- directed diverse planning for logic-geometric program- ming.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search (2022) Con ﬂict- directed diverse planning for logic-geometric program- ming

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.206340Z

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 b7210834-596d-4b5b-aa37-bf8a02d7d41b · outbound

This paper cites Extended Tree Search for Robot Task and Motion Planning.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search Extended Tree Search for Robot Task and Motion Planning

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:48:02.153874Z

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 06d36984-0f03-4332-8054-a929c4556733 · outbound

This paper cites Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T05:48:02.066703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff373c79-1789-4d9b-a49d-ba28ee60cae4 · outbound

This paper cites Translating Natural Language to Planning Goals with Large-Language Models.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search Translating Natural Language to Planning Goals with Large-Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T05:48:02.070869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9e2fb9d-ece4-4bb2-bb51-37ab89fd8766 · outbound

This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:48:02.074876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d66885d-4439-4e50-9efd-8ae60774f281 · outbound

This paper cites For WarmStartUCT of STaLM, We use UCT exploration constant c = 50, PW constants ( kα, cα) = (1.5, 0.15).

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search For WarmStartUCT of STaLM, We use UCT exploration constant c = 50, PW constants ( kα, cα) = (1.5, 0.15)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.192917Z

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 8bfe94c9-e568-4852-9468-9106710de4aa · outbound

This paper cites (2020b) Deep Visual Heuristics: Learning Feasibility of Mixed-Integer Programs for Ma- nipulation Planning.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search (2020b) Deep Visual Heuristics: Learning Feasibility of Mixed-Integer Programs for Ma- nipulation Planning

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.272467Z

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 ba8792ae-56ba-418b-951d-0ee3d2da5641 · outbound

This paper cites Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T05:48:02.032044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d2a723a-7a45-46a5-bcd4-079108159cbb · outbound

This paper cites (2023) Preference learning for guiding the tree search in continuous pomdps.

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search (2023) Preference learning for guiding the tree search in continuous pomdps

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:48:02.320564Z

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.

Pith citing papers

No inbound Pith citation observations are available.