Paper Citation Record · LEDGER

Plancraft: an evaluation dataset for planning with LLM agents

As of 11 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 9 inbound Pith citation observations for arXiv:2412.21033.

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

pith.paper-citation-record.v1
2412.21033 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:21:35.262071Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:11:54.275568Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T05:51:24.590137Z

Reference resolution

50 of 50 outbound references displayed

verified exact1
verified fuzzy11
unresolved38
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6899f4e-af3b-4b1c-9a30-0f0ebda2d7fd · outbound

This paper cites Qwen2.5-VL Technical Report.

Plancraft: an evaluation dataset for planning with LLM agents Qwen2.5-VL Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:34.962279Z

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Observation 83a6e7a3-bdb3-4633-8b20-6b3202ab33c4 · outbound

This paper cites Video pretraining (vpt): Learning to act by watching unlabeled online videos.

Plancraft: an evaluation dataset for planning with LLM agents Video pretraining (vpt): Learning to act by watching unlabeled online videos

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:36.127871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ffdfbd1e-9f5e-424c-ae64-f3751cd43797 · outbound

This paper cites Baby AI : First steps towards grounded language learning with a human in the loop.

Plancraft: an evaluation dataset for planning with LLM agents Baby AI : First steps towards grounded language learning with a human in the loop

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:36.110266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cb9af781-5bdc-42d0-b432-8c2ee8eca8ab · outbound

This paper cites Mind2web: Towards a generalist agent for the web, 2023.

Plancraft: an evaluation dataset for planning with LLM agents Mind2web: Towards a generalist agent for the web, 2023

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:34.980883Z

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Observation bcaafdb6-5669-4b4d-b95e-669cdd2d95a4 · outbound

This paper cites The Llama 3 Herd of Models.

Plancraft: an evaluation dataset for planning with LLM agents The Llama 3 Herd of Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:34.987102Z

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Observation 95ddbc39-c668-4e58-a37b-218ed7e79878 · outbound

This paper cites Minedojo: Building open-ended embodied agents with internet-scale knowledge.

Plancraft: an evaluation dataset for planning with LLM agents Minedojo: Building open-ended embodied agents with internet-scale knowledge

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:34.992805Z

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Observation 38d2ea49-d04b-4549-9ab2-085fda3ae948 · outbound

This paper cites MineRL: A Large-Scale Dataset of Minecraft Demonstrations.

Plancraft: an evaluation dataset for planning with LLM agents MineRL: A Large-Scale Dataset of Minecraft Demonstrations

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:34.998601Z

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Observation 9ef094eb-3095-4944-b64a-279ead6ec346 · outbound

This paper cites Exploring the capacity of pretrained language models for reasoning about actions and change.

Plancraft: an evaluation dataset for planning with LLM agents Exploring the capacity of pretrained language models for reasoning about actions and change

Reference 8

Resolution: verified exact; doi, observed 2026-08-10T23:21:35.379056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 69b3124f-1bbe-4667-b15a-6e8e7662b8c8 · outbound

This paper cites The fast downward planning system.

Plancraft: an evaluation dataset for planning with LLM agents The fast downward planning system

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.011784Z

Source-reported events for the cited work

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Observation 8db0f65c-f67f-42e7-b71b-22a5e3cfb518 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Plancraft: an evaluation dataset for planning with LLM agents LoRA: Low-Rank Adaptation of Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.020699Z

Source-reported events for the cited work

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Observation 339902b5-51f6-4cc1-b3e5-ead8166a9eaa · outbound

This paper cites Inner Monologue: Embodied Reasoning through Planning with Language Models.

Plancraft: an evaluation dataset for planning with LLM agents Inner Monologue: Embodied Reasoning through Planning with Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.026785Z

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Observation f78bec82-42db-4698-88be-c9715c2f0f62 · outbound

This paper cites The malmo platform for artificial intelligence experimentation.

Plancraft: an evaluation dataset for planning with LLM agents The malmo platform for artificial intelligence experimentation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.033683Z

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Observation 334b2164-3887-47e6-86c4-be78344f1904 · outbound

This paper cites Position: LLM s can’t plan, but can help planning in LLM -modulo frameworks.

Plancraft: an evaluation dataset for planning with LLM agents Position: LLM s can’t plan, but can help planning in LLM -modulo frameworks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:36.043705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6d9561c3-a4ab-45b1-a64c-9e52a305d5e1 · outbound

This paper cites ACPB ench hard: Unrestrained reasoning about action, change, and planning.

Plancraft: an evaluation dataset for planning with LLM agents ACPB ench hard: Unrestrained reasoning about action, change, and planning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:36.022450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 078b8185-56bd-4951-89f5-cc1b9010685b · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.

Plancraft: an evaluation dataset for planning with LLM agents Retrieval-augmented generation for knowledge-intensive nlp tasks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:36.004799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c072f7f4-658f-4ecb-99b7-25cf3fda2706 · outbound

This paper cites Benchmarking Detection Transfer Learning with Vision Transformers.

Plancraft: an evaluation dataset for planning with LLM agents Benchmarking Detection Transfer Learning with Vision Transformers

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.055671Z

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Observation 555f29c1-caf5-44a2-a03e-2c87edf7aac0 · outbound

This paper cites Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration.

Plancraft: an evaluation dataset for planning with LLM agents Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.061524Z

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Observation a246f7b0-38bf-4ab1-b99a-10f34eb346cf · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

Plancraft: an evaluation dataset for planning with LLM agents AgentBench: Evaluating LLMs as Agents

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.068214Z

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Observation 962a9973-7623-474f-9fe5-6d44f7cd8606 · outbound

This paper cites Howe, Craig A.

Plancraft: an evaluation dataset for planning with LLM agents Howe, Craig A

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.073575Z

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Observation baf260aa-6547-40dc-8624-10217e91f32f · outbound

This paper cites GAIA: a benchmark for General AI Assistants.

Plancraft: an evaluation dataset for planning with LLM agents GAIA: a benchmark for General AI Assistants

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.079301Z

Source-reported events for the cited work

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Observation 50d5c23b-1742-4ff0-a903-716ee56be25e · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

Plancraft: an evaluation dataset for planning with LLM agents WebGPT: Browser-assisted question-answering with human feedback

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.085746Z

Source-reported events for the cited work

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Observation bdb18fd8-7ebc-4a8c-a102-06938619207b · outbound

This paper cites GPT-4 Technical Report.

Plancraft: an evaluation dataset for planning with LLM agents GPT-4 Technical Report

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.096695Z

Source-reported events for the cited work

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Observation c2ca0f0e-10e2-4c33-9437-895551410b4e · outbound

This paper cites TALM: Tool Augmented Language Models.

Plancraft: an evaluation dataset for planning with LLM agents TALM: Tool Augmented Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.103520Z

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Observation 2865db62-cda1-4847-8197-ae4521bf585c · outbound

This paper cites Gorilla: Large Language Model Connected with Massive APIs.

Plancraft: an evaluation dataset for planning with LLM agents Gorilla: Large Language Model Connected with Massive APIs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.109381Z

Source-reported events for the cited work

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Observation c53212ee-6663-47e8-883b-bfc414e84533 · outbound

This paper cites The Multi-Agent Reinforcement Learning in Malm\"O (MARL\"O) Competition.

Plancraft: an evaluation dataset for planning with LLM agents The Multi-Agent Reinforcement Learning in Malm\"O (MARL\"O) Competition

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.114523Z

Source-reported events for the cited work

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Observation 82ceb89d-cca3-41c6-a076-5178223b2734 · outbound

This paper cites ADaPT: As-Needed Decomposition and Planning with Language Models.

Plancraft: an evaluation dataset for planning with LLM agents ADaPT: As-Needed Decomposition and Planning with Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.120847Z

Source-reported events for the cited work

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Observation f1152107-ef53-4331-a093-fcc67dabf01a · outbound

This paper cites Virtualhome: Simulating household activities via programs.

Plancraft: an evaluation dataset for planning with LLM agents Virtualhome: Simulating household activities via programs

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.126921Z

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Observation 2aff9efb-81e9-47f5-8a39-58823c8b1925 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

Plancraft: an evaluation dataset for planning with LLM agents Toolformer: Language models can teach themselves to use tools

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:35.964322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 116c7831-baaf-4084-a3dd-af5a46b4c68a · outbound

This paper cites Narasimhan, and Shunyu Yao.

Plancraft: an evaluation dataset for planning with LLM agents Narasimhan, and Shunyu Yao

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:35.946960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c12d3bed-6c15-4c79-a0ec-4a930b70fe5d · outbound

This paper cites ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks.

Plancraft: an evaluation dataset for planning with LLM agents ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.147072Z

Source-reported events for the cited work

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Observation 9cbccd52-50dc-427f-916f-7ec7d2b8b666 · outbound

This paper cites ALFWorld: Aligning Text and Embodied Environments for Interactive Learning.

Plancraft: an evaluation dataset for planning with LLM agents ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.152677Z

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Observation 055f60ee-d2ce-4e03-9aa1-de7187c82301 · outbound

This paper cites Gemma 3 Technical Report.

Plancraft: an evaluation dataset for planning with LLM agents Gemma 3 Technical Report

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.158607Z

Source-reported events for the cited work

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Observation 081fc9bc-764e-4035-9d14-32dde4d12d35 · outbound

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

Plancraft: an evaluation dataset for planning with LLM agents Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:35.926300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 91aa0402-1940-4531-8be3-14587ccb4094 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Plancraft: an evaluation dataset for planning with LLM agents Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.170924Z

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Observation a4f0be2a-6056-470e-9f2c-4e36370ee0a7 · outbound

This paper cites ScienceWorld: Is your Agent Smarter than a 5th Grader?.

Plancraft: an evaluation dataset for planning with LLM agents ScienceWorld: Is your Agent Smarter than a 5th Grader?

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.176667Z

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Observation da4e836e-958f-492f-ac7b-beeb7ee13d4f · outbound

This paper cites Le, Ed H.

Plancraft: an evaluation dataset for planning with LLM agents Le, Ed H

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:35.908331Z

Source-reported events for the cited work

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Observation f02204f5-6697-41a8-9983-636805a31499 · outbound

This paper cites JARVIS-1: Open-World Multi-task Agents with Memory-Augmented Multimodal Language Models.

Plancraft: an evaluation dataset for planning with LLM agents JARVIS-1: Open-World Multi-task Agents with Memory-Augmented Multimodal Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.187048Z

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Observation a9b14b8f-aa06-4a74-8cd8-af1181c01011 · outbound

This paper cites Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents.

Plancraft: an evaluation dataset for planning with LLM agents Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.192867Z

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Observation 46b5cc90-0735-4706-a9e7-014ee022779f · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Plancraft: an evaluation dataset for planning with LLM agents The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 39

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Observation ad43041a-4c60-44c8-a1c1-03b4c1f24634 · outbound

This paper cites Agentgym: Evolving large language model-based agents across diverse environments, 2024.

Plancraft: an evaluation dataset for planning with LLM agents Agentgym: Evolving large language model-based agents across diverse environments, 2024

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.203606Z

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Observation 622c2cef-fc5a-47e2-8f75-c69add1c58cb · outbound

This paper cites T ravel P lanner: A benchmark for real-world planning with language agents.

Plancraft: an evaluation dataset for planning with LLM agents T ravel P lanner: A benchmark for real-world planning with language agents

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:35.876732Z

Source-reported events for the cited work

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Observation ab05e995-3cba-4319-ad51-5ce72c237bac · outbound

This paper cites Qwen3 Technical Report.

Plancraft: an evaluation dataset for planning with LLM agents Qwen3 Technical Report

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.214636Z

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Plancraft: an evaluation dataset for planning with LLM agents GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.221340Z

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Observation 743ffc22-c821-4684-8ded-a37454626c15 · outbound

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Plancraft: an evaluation dataset for planning with LLM agents Webshop: Towards scalable real-world web interaction with grounded language agents

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.227225Z

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Observation cd52a878-8b99-4885-82ed-2115bc8ae527 · outbound

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Plancraft: an evaluation dataset for planning with LLM agents Tree of thoughts: Deliberate problem solving with large language models

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:21:35.838013Z

Source-reported events for the cited work

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Observation 9fd08eaf-e80b-4421-b36c-ec56d382f42e · outbound

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Plancraft: an evaluation dataset for planning with LLM agents ReAct : Synergizing reasoning and acting in language models

Reference 46

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Observation 284316ec-9da3-40f3-bcb9-955f90fb8d78 · outbound

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Plancraft: an evaluation dataset for planning with LLM agents WebArena: A Realistic Web Environment for Building Autonomous Agents

Reference 47

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Observation 591c7327-c25b-4752-87d7-325f51abd00a · outbound

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Plancraft: an evaluation dataset for planning with LLM agents @esa (Ref

Reference 48

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Observation b796486c-0b2f-4657-948b-394d834a896a · outbound

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Plancraft: an evaluation dataset for planning with LLM agents Unresolved cited work

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.255755Z

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Observation 96bc7824-9550-4c8d-b846-9b683a9cd7a0 · outbound

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Plancraft: an evaluation dataset for planning with LLM agents Unresolved cited work

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:35.262071Z

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Pith citing papers

Observation abff24fd-b60f-419c-a4d9-d0d3e9d60792 · inbound

Large Language Models for Planning: A Comprehensive and Systematic Survey cites this paper.

Large Language Models for Planning: A Comprehensive and Systematic Survey Plancraft: an evaluation dataset for planning with LLM agents

Reference 46

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Observation ff96bea1-04fc-4465-bc89-20013780566c · inbound

Memory in the Age of AI Agents cites this paper.

Memory in the Age of AI Agents Plancraft: an evaluation dataset for planning with LLM agents

Reference 294

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Observation c672ca42-ac22-4414-974b-925c85ff5c05 · inbound

LLM-WikiRace Benchmark: How Far Can LLMs Plan over Real-World Knowledge Graphs? cites this paper.

LLM-WikiRace Benchmark: How Far Can LLMs Plan over Real-World Knowledge Graphs? Plancraft: an evaluation dataset for planning with LLM agents

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Observation bf88a171-f6f1-45dc-8b52-bb38ba31f581 · inbound

Mastering PokeGym: Graph-Guided Multimodal Evolution at Test Time cites this paper.

Mastering PokeGym: Graph-Guided Multimodal Evolution at Test Time Plancraft: an evaluation dataset for planning with LLM agents

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:41:00.539463Z

Source-reported events for the cited work

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Observation cdc6800e-bb63-4bf2-a048-6976b23682f7 · inbound

Mastering PokeGym: Graph-Guided Multimodal Evolution at Test Time cites this paper.

Mastering PokeGym: Graph-Guided Multimodal Evolution at Test Time Plancraft: an evaluation dataset for planning with LLM agents

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T05:32:20.258624Z

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Observation 9acd0518-47c9-4290-bf37-7442fdd9cd96 · inbound

TacoMAS: Test-Time Co-Evolution of Topology and Capability in LLM-based Multi-Agent Systems cites this paper.

TacoMAS: Test-Time Co-Evolution of Topology and Capability in LLM-based Multi-Agent Systems Plancraft: an evaluation dataset for planning with LLM agents

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:51:24.593178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 89f93662-bec2-4466-8eec-8de955794d7a · inbound

Object-Centric Environment Modeling for Agentic Tasks cites this paper.

Object-Centric Environment Modeling for Agentic Tasks Plancraft: an evaluation dataset for planning with LLM agents

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-12T06:39:21.435864Z

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Observation f7a7032f-82e0-41ce-8f6d-08bafddaeae7 · inbound

Spinning Straw into Gold: Relabeling LLM Agent Trajectories in Hindsight for Successful Demonstrations cites this paper.

Spinning Straw into Gold: Relabeling LLM Agent Trajectories in Hindsight for Successful Demonstrations Plancraft: an evaluation dataset for planning with LLM agents

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-11T20:45:51.403759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19a1ebac-1b72-4a5f-b1d8-97e85909ecdc · inbound

AgentRadio: Passive Awareness for Long-Horizon Multi-Agent Collaboration cites this paper.

AgentRadio: Passive Awareness for Long-Horizon Multi-Agent Collaboration Plancraft: an evaluation dataset for planning with LLM agents

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-31T07:38:10.235062Z

Source-reported events for the cited work

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