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Paper Citation Record · LEDGER

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning

As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2607.15674.

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

pith.paper-citation-record.v1
2607.15674 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:39:17.308965Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

29 of 29 outbound references displayed

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External citation measurements

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Outbound references

Observation 406d4a85-8c7e-4c16-879e-51e29aa98d11 · outbound

This paper cites Crowd-Robot Interaction: Crowd-Aware Robot Navigation With Attention-Based Deep Rein- forcement Learning,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Crowd-Robot Interaction: Crowd-Aware Robot Navigation With Attention-Based Deep Rein- forcement Learning,

Reference 1

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Observation 346a9da8-0646-42a7-9db0-ad17ed7b8902 · outbound

This paper cites Decentralized structural-rnn for robot crowd navigation with deep reinforcement learning,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Decentralized structural-rnn for robot crowd navigation with deep reinforcement learning,

Reference 2

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source=pdf_text observed=2026-08-01T22:39:13.805482Z digest=sha256:445f92c39153312b08419c4207fbd5ddf4511d8a11e8981018a54093f6e99f7e

Observation 7b5f3a23-008c-4d6a-8e36-bbe9696bb12e · outbound

This paper cites RT-1: Robotics Transformer for Real-World Control at Scale.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning RT-1: Robotics Transformer for Real-World Control at Scale

Reference 3

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source=pdf_text observed=2026-08-01T22:39:13.959598Z digest=sha256:cfccb9d676ded355f79b84fd08f4afab8b7cd8006f58a85797207286b1102fe8

Observation fe713ed1-ffef-429d-b459-8fd48a6a4dc2 · outbound

This paper cites Rt- 2: Vision-language-action models transfer web knowledge to robotic control,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Rt- 2: Vision-language-action models transfer web knowledge to robotic control,

Reference 4

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source=pdf_text observed=2026-08-01T22:39:14.022116Z digest=sha256:ea3b768589bc14ff37f055cd7e2544d30f83589882d89f1ce2520cbea0d2f5d3

Observation 899dc4f4-9fbb-497f-a463-ef24762f5313 · outbound

This paper cites Safevla: Towards safety alignment of vision-language-action model via constrained learning,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Safevla: Towards safety alignment of vision-language-action model via constrained learning,

Reference 5

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source=pdf_text observed=2026-08-01T22:39:14.146100Z digest=sha256:2f90024004e17fbb2e4446c8ff59f9f075e7ec26c7088617149119cefce27d71

Observation 2daad173-b354-4aa5-b7be-8781e82352ea · outbound

This paper cites Improving pre-trained vision-language-action policies with model- based search,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Improving pre-trained vision-language-action policies with model- based search,

Reference 6

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source=pdf_text observed=2026-08-01T22:39:14.257329Z digest=sha256:650a996efee4586df747f0852578936c6b11397e4996b64f57391ec024d357f9

Observation 83051fd7-47b2-4ffa-9ebd-5ccc57df31cf · outbound

This paper cites A survey of behavior trees in robotics and ai,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning A survey of behavior trees in robotics and ai,

Reference 7

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source=pdf_text observed=2026-08-01T22:39:14.425180Z digest=sha256:28af33c3fe870610f5ab23c5981eab6b1b99072acccf3c909c37a7d2255a094c

Observation 7593f2ed-d144-4c5d-9ef0-849e536c4a7c · outbound

This paper cites Learning behavior trees with genetic programming in unpredictable environments,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Learning behavior trees with genetic programming in unpredictable environments,

Reference 8

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source=pdf_text observed=2026-08-01T22:39:14.608075Z digest=sha256:91f235e2a6542278ed7e457bd24fd990a8ed6e4ee6423d8ab0ff8fa2ec0d2e9c

Observation a523da99-2501-47b8-ada9-a595602d7815 · outbound

This paper cites Do as i can, not as i say: Grounding language in robotic affordances,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Do as i can, not as i say: Grounding language in robotic affordances,

Reference 9

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source=pdf_text observed=2026-08-01T22:39:14.768443Z digest=sha256:ddeb1b4cfcdbc25b8536fc7bd8f3889b9c70d43e80c75a9e07cd4cfb7259582f

Observation 25f2da1c-dd46-47e6-a95e-72ac7d6d1e6e · outbound

This paper cites Sayplan: Grounding large language models using 3d scene graphs for scalable robot task planning,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Sayplan: Grounding large language models using 3d scene graphs for scalable robot task planning,

Reference 10

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source=pdf_text observed=2026-08-01T22:39:14.928559Z digest=sha256:37ad2bb49d1819b9f6c9cd7187409942773b642827ef1012584e786486c343a1

Observation 35dceca6-70a9-41a9-9b97-f5597edebcbf · outbound

This paper cites Llm-brain: Ai-driven fast generation of robot behaviour tree based on large language model,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Llm-brain: Ai-driven fast generation of robot behaviour tree based on large language model,

Reference 11

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source=pdf_text observed=2026-08-01T22:39:15.079137Z digest=sha256:7b1d9a1c3ac125ff6f4678f8f335a05a32c9f2a1fbd13b1a82b50d04e95e9c2d

Observation 7240a427-f1c3-4a8a-86db-56a9acf07a58 · outbound

This paper cites BTGenBot: Behavior Tree Generation for Robotic Tasks with Lightweight LLMs,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning BTGenBot: Behavior Tree Generation for Robotic Tasks with Lightweight LLMs,

Reference 12

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source=pdf_text observed=2026-08-01T22:39:15.211144Z digest=sha256:1d50b6f1758b89967321044529aaa1d4616f7b7ae8e6049c11cec45a43c16ee2

Observation bac413ad-1166-4ebd-bd37-78bc07eac5cb · outbound

This paper cites LLM-BT: Performing Robotic Adaptive Tasks based on Large Language Models and Behav- ior Trees,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning LLM-BT: Performing Robotic Adaptive Tasks based on Large Language Models and Behav- ior Trees,

Reference 13

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source=pdf_text observed=2026-08-01T22:39:15.268766Z digest=sha256:f32fdc074083011183bcc8e3913689d4b014ad0da9e112f836d25d98a06f0141

Observation e17849e8-f75b-496b-9e4c-cbe31d5dc284 · outbound

This paper cites On the implementation of behaviour trees in robotics,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning On the implementation of behaviour trees in robotics,

Reference 14

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source=pdf_text observed=2026-08-01T22:39:15.389467Z digest=sha256:d21ed8209ff49966137bd8aa3c685aa61e71a34d111ff57d4b0c745471bc598f

Observation 6a3b868a-b164-418d-909f-a6316b41927c · outbound

This paper cites ROS Topics: Capabilities [ROS Topics],.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning ROS Topics: Capabilities [ROS Topics],

Reference 15

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source=pdf_text observed=2026-08-01T22:39:15.464105Z digest=sha256:6db7e1228d1d3d4c0c9bc52e863941ce33dbfd5744bc8193a7bb27153cd81663

Observation 208082df-4746-4c7e-ae6b-20aacb92e7da · outbound

This paper cites Capabilities2 for ROS2: Advanced Skill-Based Control for Human- Robot Interaction,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Capabilities2 for ROS2: Advanced Skill-Based Control for Human- Robot Interaction,

Reference 16

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Observation 54ecca0d-fba2-43a5-b9df-35cf3a5c5e32 · outbound

This paper cites Comparison between behavior trees and finite state ma- chines,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Comparison between behavior trees and finite state ma- chines,

Reference 17

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source=pdf_text observed=2026-08-01T22:39:15.626621Z digest=sha256:0186bdebd86d926d83aa0c7478e22fa90433fe76d8f46c0444bfc7802d3cf665

Observation 7db79b82-2103-450b-852e-4c8582683175 · outbound

This paper cites ROS 2-Based Flexible Behavior Engine for Flexible Navigation,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning ROS 2-Based Flexible Behavior Engine for Flexible Navigation,

Reference 18

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Observation bbaa7e01-8e65-4329-ae66-c9808a32f1ca · outbound

This paper cites Yasmin: Yet another state machine library for ros 2,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Yasmin: Yet another state machine library for ros 2,

Reference 19

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source=pdf_text observed=2026-08-01T22:39:15.790056Z digest=sha256:7ed3268b93904f343f196bc75b735d91a4e05738a185e10c470b1b9854f93004

Observation 148105e4-4310-4d4b-9fa8-3ab8f9ff4b78 · outbound

This paper cites Code as Policies: Language Model Programs for Embodied Control.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Code as Policies: Language Model Programs for Embodied Control

Reference 20

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source=pdf_text observed=2026-08-01T22:39:15.922685Z digest=sha256:3b83ef36a81adc17c9c11826897340f68dfd6cb8ef9befddbae0254d963e6317

Observation d6aa5a34-b1d8-477d-909a-26d81715e6d9 · outbound

This paper cites Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance,

Reference 21

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source=pdf_text observed=2026-08-01T22:39:16.102662Z digest=sha256:c23de0552e7cebaf73b7fd4a5bf160328c421116973ec2b271597bd08d7e55e6

Observation 60f13c5d-485d-423d-b13c-e4370dbf9692 · outbound

This paper cites Au- tomatic behavior tree expansion with llms for robotic manipulation,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Au- tomatic behavior tree expansion with llms for robotic manipulation,

Reference 22

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source=pdf_text observed=2026-08-01T22:39:16.217884Z digest=sha256:221c1607f915dc1ebf75665640f824a0dde435e7939e9457d1e41b2fe3d5806f

Observation ed83f3b1-a262-4452-99c8-f65360690455 · outbound

This paper cites Llm-as-bt-planner: Leveraging llms for behavior tree generation in robot task planning,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Llm-as-bt-planner: Leveraging llms for behavior tree generation in robot task planning,

Reference 23

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source=pdf_text observed=2026-08-01T22:39:16.367550Z digest=sha256:e72ec3c834b144c8f03f5b00dafaf55350202823cc910166b3750937dce0e809

Observation acccddce-00f5-4576-b302-0a1d9e088f43 · outbound

This paper cites VLM-driven Behavior Tree for Context-aware Task Planning,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning VLM-driven Behavior Tree for Context-aware Task Planning,

Reference 24

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source=pdf_text observed=2026-08-01T22:39:16.533513Z digest=sha256:4666a16dfb6cb445204f051fcd4897ca7b19b5796c4ff2b5f33063e9c511b278

Observation db6a34df-2756-49ea-be9a-aee57f16ae95 · outbound

This paper cites Look before you leap: Using seri- alized state machine for language conditioned robotic manipulation,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Look before you leap: Using seri- alized state machine for language conditioned robotic manipulation,

Reference 25

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source=pdf_text observed=2026-08-01T22:39:16.849427Z digest=sha256:a752029e35391cf4ae4eaeb530b77c2c610e61566cf8687b6ed418132e3bc8cc

Observation a1b6dc99-32c9-414d-aa7c-1eb33bcbbd46 · outbound

This paper cites Unleashing the power of llm to infer state machine from the protocol implementation,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Unleashing the power of llm to infer state machine from the protocol implementation,

Reference 26

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source=pdf_text observed=2026-08-01T22:39:17.015793Z digest=sha256:d527b50b4cea76857b1efeec838c0d8d7ef7d2b2e20448fce02d103c41b49864

Observation 42874eb6-adbe-47e9-87b3-1ccb70313977 · outbound

This paper cites Can Large Language Models Help Developers with Robotic Finite State Machine Modification?.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Can Large Language Models Help Developers with Robotic Finite State Machine Modification?

Reference 27

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source=pdf_text observed=2026-08-01T22:39:17.160688Z digest=sha256:e699d4b5632b216f77377744471581e229aec2486e4ac819895f6c98972862d2

Observation ec69861a-5ad1-4ad7-af21-abb8d49e1c06 · outbound

This paper cites Behavior trees and state machines in robotics applications,.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Behavior trees and state machines in robotics applications,

Reference 28

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source=pdf_text observed=2026-08-01T22:39:17.308965Z digest=sha256:336350d05bc23406f7e990af9aa4c47b25679c22d986ac572d252af8317a8560

Observation 9bcc3adf-975d-4480-90db-ba83724652bf · outbound

This paper cites VLM-driven Behavior Tree for Context-aware Task Planning.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning VLM-driven Behavior Tree for Context-aware Task Planning

Reference 2025

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source=pdf_text observed=2026-08-01T22:39:16.676984Z digest=sha256:233b7a92cefea8ff83f284211ca9946c7dd820b3097f62429d398978f6e1496d

Pith citing papers

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