Paper Citation Record · LEDGER

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance

As of 11 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2507.16382.

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

pith.paper-citation-record.v1
2507.16382 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:15:26.334084Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

25 of 25 outbound references displayed

verified exact0
verified fuzzy17
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e195e1b9-113b-4fca-91b4-2eb09ea49754 · outbound

This paper cites Reciprocal col- lision avoidance with acceleration-velocity obstacles,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Reciprocal col- lision avoidance with acceleration-velocity obstacles,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.558637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation eac33085-bde4-4183-99bc-857d5e599711 · outbound

This paper cites An improved artificial potential field method for path planning and formation control of the multi-uav systems,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance An improved artificial potential field method for path planning and formation control of the multi-uav systems,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.550967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 01ac2bd7-99aa-45c9-a3c8-e43bd7c0fd52 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Proximal Policy Optimization Algorithms

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T15:15:26.274545Z

Source-reported events for the cited work

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Observation 040d2581-4b1c-481d-a71f-bd479012a1d2 · outbound

This paper cites Impala: Scalable distributed deep-rl with importance weighted actor-learner architec- tures,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Impala: Scalable distributed deep-rl with importance weighted actor-learner architec- tures,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.543274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4973b4bb-ad7a-4e4d-a47a-e69496da2a79 · outbound

This paper cites Monotonic value function factorisation for deep multi- agent reinforcement learning,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Monotonic value function factorisation for deep multi- agent reinforcement learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.535269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5d936f68-df05-426a-8253-1694e47db49a · outbound

This paper cites Grandmaster level in starcraft ii using multi-agent reinforcement learning,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Grandmaster level in starcraft ii using multi-agent reinforcement learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.526744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b16eff6f-b9ae-46ba-b876-f07722f1998b · outbound

This paper cites Dota 2 with Large Scale Deep Reinforcement Learning.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Dota 2 with Large Scale Deep Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T15:15:26.285767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8134c526-2ee1-462e-891d-c25a67816111 · outbound

This paper cites The surprising effectiveness of ppo in cooperative multi- agent games,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance The surprising effectiveness of ppo in cooperative multi- agent games,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.519109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bc39f2c1-3a29-4337-9038-e53a97d4e4ee · outbound

This paper cites Formation control with collision avoidance through deep reinforcement learning using model-guided demonstration,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Formation control with collision avoidance through deep reinforcement learning using model-guided demonstration,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.510870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5fbe4ceb-82d6-4c64-8453-c37a0fee59c2 · outbound

This paper cites Relative distributed formation and obstacle avoidance with multi- agent reinforcement learning,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Relative distributed formation and obstacle avoidance with multi- agent reinforcement learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.502992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation eab2090f-48d2-499d-85f6-56a35751e303 · outbound

This paper cites Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T15:15:26.296759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cb9f391-230a-41ac-83be-47446074ee81 · outbound

This paper cites Executable code actions elicit better LLM agents,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Executable code actions elicit better LLM agents,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.494976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a8ad1ec2-20e2-4550-be8c-87121bcdc8cf · outbound

This paper cites Boosting efficient reinforcement learning for vision-and-language navigation with open- sourced llm,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Boosting efficient reinforcement learning for vision-and-language navigation with open- sourced llm,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T15:15:26.303082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c7e1473-ebcf-4eea-9b60-3d86c85bb14d · outbound

This paper cites Text2Reward: Reward Shaping with Language Models for Reinforcement Learning,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Text2Reward: Reward Shaping with Language Models for Reinforcement Learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.481824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9cd4743c-7e2f-42a1-a305-96c145e0a1db · outbound

This paper cites Eureka: Human-Level Reward Design via Coding Large Language Models.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Eureka: Human-Level Reward Design via Coding Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T15:15:26.308611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38724d0b-7726-4a2d-93ea-21d30620900d · outbound

This paper cites Adaptive finite-time tracking control of nonholonomic multirobot formation systems with limited field-of- view sensors,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Adaptive finite-time tracking control of nonholonomic multirobot formation systems with limited field-of- view sensors,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.474042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f4af54e6-f34f-4c46-b4c3-e84ce22bfdcc · outbound

This paper cites Racer: Rapid collaborative explo- ration with a decentralized multi-uav system,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Racer: Rapid collaborative explo- ration with a decentralized multi-uav system,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.465655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f69ba60d-d882-4553-ba42-a64c19535799 · outbound

This paper cites An overview of recent advances in coordinated control of multiple autonomous surface vehicles,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance An overview of recent advances in coordinated control of multiple autonomous surface vehicles,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.456447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7a4c6c52-a0eb-4c66-b473-712116e2cf7b · outbound

This paper cites an unresolved cited work.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:15:26.447284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4a5e88e6-0b93-4744-aec7-b4eb4cfddfb2 · outbound

This paper cites Distributed swarm trajectory optimization for formation flight in dense environments,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Distributed swarm trajectory optimization for formation flight in dense environments,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.438654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bc38e57e-663e-43b7-b7a8-b6ea90ba8722 · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T15:15:26.323832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 512bfd60-7e1f-49f0-81dd-4ba8d691cecf · outbound

This paper cites Asynchronous Methods for Deep Reinforcement Learning,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Asynchronous Methods for Deep Reinforcement Learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.430760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c19c8140-8183-4258-b2ea-62779837963c · outbound

This paper cites Qwen2.5 Technical Report,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Qwen2.5 Technical Report,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.422025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c9ea01f0-55d7-4287-acc1-29068e5ad278 · outbound

This paper cites Decentralized non- communicating multiagent collision avoidance with deep reinforce- ment learning,.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance Decentralized non- communicating multiagent collision avoidance with deep reinforce- ment learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:15:26.412821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 02c0bf11-842e-407d-a166-d4d3129d883d · outbound

This paper cites DrEureka: Language Model Guided Sim-To-Real Transfer.

Application of LLM Guided Reinforcement Learning in Formation Control with Collision Avoidance DrEureka: Language Model Guided Sim-To-Real Transfer

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T15:15:26.334084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.