Paper Citation Record · LEDGER

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning

As of 15 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 2 inbound Pith citation observations for arXiv:2506.19592.

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

pith.paper-citation-record.v1
2506.19592 v2

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:09:56.280646Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T12:59:51.091008Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:40:06.803339Z

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy23
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fad65613-87ec-4f0e-9370-04ad52b36553 · outbound

This paper cites Chain-of-thought prompting elicits rea- soning in large language models,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Chain-of-thought prompting elicits rea- soning in large language models,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:01.402875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fa340bfc-109b-4f8e-837d-915effdebcae · outbound

This paper cites Large language models are zero-shot reasoners,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Large language models are zero-shot reasoners,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:01.235607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0a7675d0-674d-4c46-a892-f255fd7fc694 · outbound

This paper cites Tree of thoughts: Deliberate prob- lem solving with large language models,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Tree of thoughts: Deliberate prob- lem solving with large language models,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:00.979158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d54885c1-e084-4971-93a4-8459b30a10e0 · outbound

This paper cites Graph of thoughts: Solving elaborate problems with large language models,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Graph of thoughts: Solving elaborate problems with large language models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:00.733795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a9e5f571-4622-4855-808d-b877992daefe · outbound

This paper cites Lan- guage models as zero-shot planners: Extracting actionable knowledge for embodied agents,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Lan- guage models as zero-shot planners: Extracting actionable knowledge for embodied agents,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:00.557344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 912ea74c-a040-4b37-8ee9-39ec40feac72 · outbound

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

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Do as i can, not as i say: Grounding language in robotic affordances,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:00.374850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 499fe722-a58e-4f9e-a646-f488a99396d6 · outbound

This paper cites Inner monologue: Embodied reasoning through planning with language models,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Inner monologue: Embodied reasoning through planning with language models,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:00.191326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f7c80c85-edf5-4e97-9d69-dc84b4721c9d · outbound

This paper cites Reflexion: language agents with verbal rein- forcement learning,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Reflexion: language agents with verbal rein- forcement learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:59.996275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9edf86c2-70ee-4a89-884f-3e024787dfe8 · outbound

This paper cites CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T23:09:53.788945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87e7efcf-5f2f-489c-8171-c31a700d27a9 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning ReAct: Synergizing Reasoning and Acting in Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T23:09:53.862291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a80e6d6-a2e5-4a5f-aff0-eece16558057 · outbound

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

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Sayplan: Grounding large language models using 3d scene graphs for scalable robot task planning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:59.858441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e060d15a-c574-4afd-9623-5a2d60c56e97 · outbound

This paper cites Reasoning with language model is planning with world model,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Reasoning with language model is planning with world model,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:59.679702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b2ed3f50-0b98-45db-87ca-e0af099c89de · outbound

This paper cites Generalized planning in pddl do- mains with pretrained large language models,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Generalized planning in pddl do- mains with pretrained large language models,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:59.448267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 32ee2dea-0ba7-4c82-8de6-07b477b54d6f · outbound

This paper cites Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:59.261416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 59f33418-c9be-41a7-8375-ce978da771be · outbound

This paper cites Llms can’t plan, but can help planning in llm-modulo frameworks,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Llms can’t plan, but can help planning in llm-modulo frameworks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:59.065405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 63873f5f-9d09-4d48-b648-6a4417ece7a5 · outbound

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

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T23:09:54.394747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8693223-67f7-4ed2-a9f8-20c5bd0c4807 · outbound

This paper cites Dynamic Planning with a LLM.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Dynamic Planning with a LLM

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T23:09:54.480410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1dc9e8c-6f07-4f30-8e65-fe1ac353c379 · outbound

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

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Leveraging pre-trained large language models to construct and utilize world models for model-based task planning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:58.783300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ac2c0ea4-aa89-4751-961d-cc46b4dc823c · outbound

This paper cites Nl2plan: Robust llm-driven planning from minimal text descriptions,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Nl2plan: Robust llm-driven planning from minimal text descriptions,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:58.578266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e1dba212-46d5-4a3e-8723-0f4c6c85e156 · outbound

This paper cites LaMMA-P: Generalizable Multi-Agent Long-Horizon Task Allocation and Planning with LM-Driven PDDL Planner.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning LaMMA-P: Generalizable Multi-Agent Long-Horizon Task Allocation and Planning with LM-Driven PDDL Planner

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T23:09:54.747482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47918340-568f-448a-b2c7-2107b6932b49 · outbound

This paper cites CLMASP: Coupling Large Language Models with Answer Set Programming for Robotic Task Planning.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning CLMASP: Coupling Large Language Models with Answer Set Programming for Robotic Task Planning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T23:09:54.880216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb549c1f-c58b-4ee1-8cb3-90da6ff6c782 · outbound

This paper cites Coupling large language models with logic programming for robust and general reasoning from text,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Coupling large language models with logic programming for robust and general reasoning from text,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:58.268885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f962287f-1b53-4787-aa5e-02845c04706e · outbound

This paper cites Autotamp: Autoregressive task and motion planning with llms as translators and checkers,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Autotamp: Autoregressive task and motion planning with llms as translators and checkers,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:58.003211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9bd51d2d-52d3-4e00-8b55-43af531c22c7 · outbound

This paper cites AutoGPT+P: Affordance-based Task Planning using Large Language Models,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning AutoGPT+P: Affordance-based Task Planning using Large Language Models,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:57.800830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 553003d2-2e53-4986-b46e-255e20913891 · outbound

This paper cites DELTA: Decomposed Efficient Long-Term Robot Task Planning using Large Language Models.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning DELTA: Decomposed Efficient Long-Term Robot Task Planning using Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T23:09:55.479290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 210a57b0-6963-4dc9-9f53-d2ff6f0169dc · outbound

This paper cites Makeable: Memory-centered and affordance-based task execution framework for transferable mobile manipulation skills,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Makeable: Memory-centered and affordance-based task execution framework for transferable mobile manipulation skills,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:57.531508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ac3fcd58-0112-4683-8de5-c4aaafcb75a2 · outbound

This paper cites Robots can multitask too: Integrating a memory architecture and llms for enhanced cross-task robot action generation,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Robots can multitask too: Integrating a memory architecture and llms for enhanced cross-task robot action generation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:57.290912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ace2a777-e67f-4a7c-b611-f88cad0ebf96 · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning OpenVLA: An Open-Source Vision-Language-Action Model

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T23:09:55.935565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b729b5d7-de6c-46e4-82ae-dda884490959 · outbound

This paper cites Open x-embodiment: Robotic learning datasets and rt-x models,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Open x-embodiment: Robotic learning datasets and rt-x models,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:57.052209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c68b677a-2716-4d3f-bf11-9850926c53c0 · outbound

This paper cites Virtualhome: Simulating household activities via programs,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning Virtualhome: Simulating household activities via programs,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:56.800515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3f5fb0fa-5b9e-437a-aae8-3a7c858d3471 · outbound

This paper cites The effect of sampling temperature on prob- lem solving in large language models,.

Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning The effect of sampling temperature on prob- lem solving in large language models,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:09:56.612221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation aadafa22-d927-44b0-bddd-af6661848780 · inbound

The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes cites this paper.

The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-08-10T01:13:53.066579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f795578a-13ed-4563-b7a3-68a8b1491c8f · inbound

HEART: Coordination of Heterogeneous Expert Agents for Physically Grounded Robotic Task Planning cites this paper.

HEART: Coordination of Heterogeneous Expert Agents for Physically Grounded Robotic Task Planning Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planning

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-08-10T01:13:53.066579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.