Paper Citation Record · LEDGER

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study

As of 19 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2507.23589.

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

pith.paper-citation-record.v1
2507.23589 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:45:59.609092Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T04:40:52.854907Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

38 of 38 outbound references displayed

verified exact3
verified fuzzy14
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 49bc82a5-2191-4a10-96b6-60a483259a01 · outbound

This paper cites The fast downward planning system.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study The fast downward planning system

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.456686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6250c9d6-e2cf-44e2-bfec-06ef27bb4fde · outbound

This paper cites PDDL —the planning domain definition language.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study PDDL —the planning domain definition language

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.495048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 18b393af-a807-4e95-bc45-bdf63897c314 · outbound

This paper cites Chi, Quoc V.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Chi, Quoc V

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.484107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0a588ba2-55db-406c-a35a-05889c642f88 · outbound

This paper cites ReAct : Synergizing reasoning and acting in language models.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study ReAct : Synergizing reasoning and acting in language models

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.472237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5cce2666-b6d6-45a4-92a8-9526e956dbba · outbound

This paper cites Sadler, Wei-Lun Chao, and Yu Su.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Sadler, Wei-Lun Chao, and Yu Su

Reference 5

Resolution: verified exact; raw_fallback, observed 2026-08-06T10:46:00.287389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d60c3fc9-d942-4033-9d13-bf5268cf55da · outbound

This paper cites Generating Executable Action Plans with Environmentally-Aware Language Models.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Generating Executable Action Plans with Environmentally-Aware Language Models

Reference 6

Resolution: verified exact; raw_fallback, observed 2026-08-06T10:46:00.199508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 042a9429-61c7-4afc-b456-95c0e358e9d6 · outbound

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

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.485930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b94b3c2c-3e92-4ff1-931a-a6c8ed2905c0 · outbound

This paper cites an unresolved cited work.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-06T10:46:00.460490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 496886cf-8f00-474e-b00a-537900bc8640 · outbound

This paper cites Can Large Language Models Reason and Plan? Annals of the New York Academy of Sciences, 2024.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Can Large Language Models Reason and Plan? Annals of the New York Academy of Sciences, 2024

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.493963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b602f388-51a7-4dc8-812b-22546b0d9c52 · outbound

This paper cites Leveraging environment interaction for automated pddl translation and planning with large language models.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Leveraging environment interaction for automated pddl translation and planning with large language models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.448753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1fce17a5-63fd-4e91-8cbe-5a1404e32ec2 · outbound

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

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.501390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13e42e2b-9e24-4c0d-9ffb-ea659bf1feff · outbound

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

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.436105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0b91cd9b-ab87-4a95-b070-b8200e55736f · outbound

This paper cites Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.509242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e48dc1af-e625-4013-8d95-615a6cbd5cf3 · outbound

This paper cites an unresolved cited work.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-06T10:46:00.424534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 36501121-d7b5-4b19-89eb-f6865d6eeabe · outbound

This paper cites AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.516565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bab11192-388a-4bf8-a8e3-c71eea454a49 · outbound

This paper cites On the planning abilities of large language models: A critical investigation.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study On the planning abilities of large language models: A critical investigation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.412846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8274e362-d01f-461d-a016-4a92c8a5a5a0 · outbound

This paper cites A Framework for Neurosymbolic Robot Action Planning using Large Language Models.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study A Framework for Neurosymbolic Robot Action Planning using Large Language Models

Reference 17

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T10:46:00.049165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation db6a0d60-8e6a-4c98-87dd-f1dd64a146f9 · outbound

This paper cites Automating the Generation of Prompts for LLM-based Action Choice in PDDL Planning.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Automating the Generation of Prompts for LLM-based Action Choice in PDDL Planning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.527985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8388aa4-0d24-4a7e-9735-fc68e4aefe0f · outbound

This paper cites Tenenbaum, Leslie Pack Kaelbling, and Michael Katz.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Tenenbaum, Leslie Pack Kaelbling, and Michael Katz

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.531672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b6846e1-d56b-4d9f-9728-f48209d0a078 · outbound

This paper cites Fast and Accurate Task Planning using Neuro-Symbolic Language Models and Multi-level Goal Decomposition.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Fast and Accurate Task Planning using Neuro-Symbolic Language Models and Multi-level Goal Decomposition

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.539657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5670468d-2670-4b04-942b-61f796e6e533 · outbound

This paper cites CoPAL: Corrective Planning of Robot Actions with Large Language Models.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study CoPAL: Corrective Planning of Robot Actions with Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.543728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 363bcc86-bc10-4b74-9ece-199e8ab32e95 · outbound

This paper cites Saycanpay: Heuristic planning with large language models using learnable domain knowledge.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Saycanpay: Heuristic planning with large language models using learnable domain knowledge

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.547535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05e5e0b6-9f30-40f4-a66f-67e5ab375afd · outbound

This paper cites PaLM-E: An Embodied Multimodal Language Model.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study PaLM-E: An Embodied Multimodal Language Model

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.551279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba4a841c-c3ee-43a7-8feb-4f039cf70fa1 · outbound

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

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.399627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fcc2a004-06f6-47e3-a5c9-d9af1404e752 · outbound

This paper cites LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBench.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBench

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.558754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5572bc3b-ed74-41cd-b8c6-7997792d9df3 · outbound

This paper cites Littman, and Stephen H.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Littman, and Stephen H

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.562768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 249cde25-c9bc-4384-9b69-aecd0d6ffe01 · outbound

This paper cites NL2Plan: Robust LLM-Driven Planning from Minimal Text Descriptions.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study NL2Plan: Robust LLM-Driven Planning from Minimal Text Descriptions

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.566806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c995e071-1e8c-4969-9b34-55c5c68ada16 · outbound

This paper cites NATURAL PLAN: Benchmarking LLMs on Natural Language Planning.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study NATURAL PLAN: Benchmarking LLMs on Natural Language Planning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.570552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f58b833-7ab4-493a-b090-abb03732f5e3 · outbound

This paper cites Open Grounded Planning: Challenges and Benchmark Construction.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Open Grounded Planning: Challenges and Benchmark Construction

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-06T10:45:59.692535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 49ed1861-dc8d-48b4-b69d-011a47b16ba5 · outbound

This paper cites CaT-Bench: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Plans.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study CaT-Bench: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Plans

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.578372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f79db19d-e568-42e8-8d85-f03158156c23 · outbound

This paper cites The production ai platform built for developers, 2024.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study The production ai platform built for developers, 2024

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.385229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3dbe9cab-60d4-4cea-9734-ffafcf100a96 · outbound

This paper cites an unresolved cited work.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.585767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f70cca8e-7b30-4500-a07a-208a8e730f15 · outbound

This paper cites Deepseek vs.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Deepseek vs

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.365312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b8e668ac-58cc-4251-ae55-91003419891c · outbound

This paper cites Meta releases new llama 3.1 models, including highly anticipated 405b parameter variant.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Meta releases new llama 3.1 models, including highly anticipated 405b parameter variant

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.354585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5b54945e-3975-4b79-a3d1-174f57b3eda5 · outbound

This paper cites Gemini 2.0 flash thinking experimental: A guide with examples.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Gemini 2.0 flash thinking experimental: A guide with examples

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.339061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c3c1fb54-4c33-48dc-909b-1ba87abc77d6 · outbound

This paper cites Comparing claude 3.7 sonnet, claude 3.5 sonnet, openai o3-mini, deepseek r1, and grok 3 beta.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Comparing claude 3.7 sonnet, claude 3.5 sonnet, openai o3-mini, deepseek r1, and grok 3 beta

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.326857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a5ef1c3a-d9fa-467d-ae83-64385cf1b4a7 · outbound

This paper cites Grok 3 beta—the age of reasoning agents.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Grok 3 beta—the age of reasoning agents

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.313588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 74ab2bf0-21c3-4379-856f-31c298bd3518 · outbound

This paper cites Claude 3.7 sonnet and claude code.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Claude 3.7 sonnet and claude code

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:46:00.300041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation e657ef9d-ead4-462d-8171-d0d281ced4b2 · inbound

Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards cites this paper.

Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-10T04:45:21.129130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.