Paper Citation Record · LEDGER

Generating Symbolic World Models via Test-time Scaling of Large Language Models

As of 9 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 3 inbound Pith citation observations for arXiv:2502.04728.

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

pith.paper-citation-record.v1
2502.04728 v2

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:45:45.538720Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:14:21.027074Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T23:42:49.549067Z

Reference resolution

63 of 63 outbound references displayed

verified exact0
verified fuzzy21
unresolved42
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 03cd33d5-726d-41df-939a-57dd9a284dfe · outbound

This paper cites GPT-4 Technical Report.

Generating Symbolic World Models via Test-time Scaling of Large Language Models GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

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Observation 0333c392-25f1-4a9e-baa1-91417723d13c · outbound

This paper cites Learning discrete world models for heuristic search.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Learning discrete world models for heuristic search

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.845605Z

Source-reported events for the cited work

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Observation 36c5cbae-ff49-461e-acf8-180ea3d9df5d · outbound

This paper cites Program Synthesis with Large Language Models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Program Synthesis with Large Language Models

Reference 3

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Observation 6d31b2ee-9447-45c1-8cab-ecccf8d49965 · outbound

This paper cites Learning warm-start points for ac optimal power flow.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Learning warm-start points for ac optimal power flow

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.831395Z

Source-reported events for the cited work

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Observation 9e4b8858-2e3f-44c4-bf71-3ca19a79f864 · outbound

This paper cites Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?

Reference 5

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Observation 39f13cc1-2b1d-46b8-a381-21be6515f46a · outbound

This paper cites OpenAI Gym.

Generating Symbolic World Models via Test-time Scaling of Large Language Models OpenAI Gym

Reference 6

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Source-reported events for the cited work

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Observation 85844672-b9dc-4afe-982a-cc1b173a2e71 · outbound

This paper cites Language models are few-shot learners.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Language models are few-shot learners

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.816778Z

Source-reported events for the cited work

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Observation bcbf0079-ae87-45ce-989a-c8b37f8c7cad · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Evaluating Large Language Models Trained on Code

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.275330Z

Source-reported events for the cited work

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Observation ede1b7a6-2aa2-4a1f-8c27-e9012feacaf2 · outbound

This paper cites Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks

Reference 9

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Source-reported events for the cited work

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Observation f07b44fe-b95c-485b-ad97-09d742351135 · outbound

This paper cites Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.285649Z

Source-reported events for the cited work

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Observation 0ea578a5-37f1-4a1d-a3e8-dc8c91c33b24 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Training Verifiers to Solve Math Word Problems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.290407Z

Source-reported events for the cited work

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Observation e46c3c3c-c61a-4dc6-93bf-14d15caae9ad · outbound

This paper cites Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.295334Z

Source-reported events for the cited work

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Observation 9cae3b3f-2bc0-4940-a254-af6b3f0c1477 · outbound

This paper cites Parameter-efficient fine-tuning of large-scale pre-trained language models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Parameter-efficient fine-tuning of large-scale pre-trained language models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.802075Z

Source-reported events for the cited work

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Observation bba694be-40d2-4597-b281-d6988b038b87 · outbound

This paper cites A Survey on In-context Learning.

Generating Symbolic World Models via Test-time Scaling of Large Language Models A Survey on In-context Learning

Reference 14

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Source-reported events for the cited work

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Observation eefa8b78-3ad8-45ac-92c2-2fa09093e5a1 · outbound

This paper cites The Llama 3 Herd of Models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models The Llama 3 Herd of Models

Reference 15

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Source-reported events for the cited work

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Observation 05e9d0c6-f8f0-4c7b-b83d-8b830a7848a5 · outbound

This paper cites Fikes and Nils J.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Fikes and Nils J

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.787696Z

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Observation a8196531-c14f-4dd2-9fa5-80c78856f6b5 · outbound

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

Generating Symbolic World Models via Test-time Scaling of Large Language Models Leveraging pre- trained large language models to construct and utilize world models for model-based task planning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.773058Z

Source-reported events for the cited work

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Observation b7d8ce2b-c5dc-43e9-bd3b-a8549d7d7275 · outbound

This paper cites Reasoning with Language Model is Planning with World Model.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Reasoning with Language Model is Planning with World Model

Reference 18

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Source-reported events for the cited work

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Observation 7f0a7224-bc1f-4018-8a5d-da4c5e801049 · outbound

This paper cites The fast downward planning system.

Generating Symbolic World Models via Test-time Scaling of Large Language Models The fast downward planning system

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.758668Z

Source-reported events for the cited work

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Observation ae4c5c4b-61de-4c3b-8da5-288a88e88961 · outbound

This paper cites The Competition: Impact, Organization, Evaluation, Benchmarks.

Generating Symbolic World Models via Test-time Scaling of Large Language Models The Competition: Impact, Organization, Evaluation, Benchmarks

Reference 20

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Observation 8f457a45-904f-4767-b2c9-6c79ece777c4 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Lora: Low-rank adaptation of large language models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.729161Z

Source-reported events for the cited work

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Observation 6a196f09-0952-4697-b545-3cb315e96399 · outbound

This paper cites OpenAI o1 System Card.

Generating Symbolic World Models via Test-time Scaling of Large Language Models OpenAI o1 System Card

Reference 22

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Observation 646869af-157b-450d-b043-6057ffe4fe10 · outbound

This paper cites Mistral 7B.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Mistral 7B

Reference 23

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Source-reported events for the cited work

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Observation 1a73d1ce-9422-42c9-910b-472c4d627b15 · outbound

This paper cites Can large language models reason and plan?Annals of the New York Academy of Sciences, 1534(1):15–18, 2024.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Can large language models reason and plan?Annals of the New York Academy of Sciences, 1534(1):15–18, 2024

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.714844Z

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Observation f93ed7bc-4342-4b77-8817-7936a8abda61 · outbound

This paper cites Parameter-efficient orthogonal finetuning via butterfly factorization.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Parameter-efficient orthogonal finetuning via butterfly factorization

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.699971Z

Source-reported events for the cited work

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Observation 946a65a8-9d97-4a61-a89a-5c4701501fea · outbound

This paper cites Leveraging Environment Interaction for Automated PDDL Translation and Planning with Large Language Models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Leveraging Environment Interaction for Automated PDDL Translation and Planning with Large Language Models

Reference 26

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Source-reported events for the cited work

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Observation 54cfd0fa-f274-448c-b515-e2a85c50e5a1 · outbound

This paper cites Howe, Craig A.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Howe, Craig A

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.685254Z

Source-reported events for the cited work

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Observation 45ab39e7-1ebf-4626-884c-998a24d671d0 · outbound

This paper cites GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

Reference 28

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Observation b772d60b-b75b-43d3-831e-f8a9906aac37 · outbound

This paper cites Fully autonomous ai agents should not be developed.arXiv preprint arXiv:2502.02649, 2025.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Fully autonomous ai agents should not be developed.arXiv preprint arXiv:2502.02649, 2025

Reference 29

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Source-reported events for the cited work

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Observation 68346e29-ac90-4df6-99d3-75a7b5ab64fc · outbound

This paper cites Large language models as planning domain generators.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Large language models as planning domain generators

Reference 30

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Source-reported events for the cited work

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Observation ed5725ed-d274-40e8-89c1-761ee62b7939 · outbound

This paper cites Automatic Prompt Optimization with "Gradient Descent" and Beam Search.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Automatic Prompt Optimization with "Gradient Descent" and Beam Search

Reference 31

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Observation 654adc1e-7ed5-4d85-901d-6daa106d887e · outbound

This paper cites O1 Replication Journey: A Strategic Progress Report -- Part 1.

Generating Symbolic World Models via Test-time Scaling of Large Language Models O1 Replication Journey: A Strategic Progress Report -- Part 1

Reference 32

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Observation d184fcdf-b6bd-47af-9930-beae695c542e · outbound

This paper cites Controlling text-to-image diffusion by orthogonal finetuning.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Controlling text-to-image diffusion by orthogonal finetuning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.656622Z

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Observation 0713ec78-5d08-4f1c-bdff-b5e5fc75dd4e · outbound

This paper cites Pearson, 2016.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Pearson, 2016

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.637822Z

Source-reported events for the cited work

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Observation 9fadc9f0-a05a-4a15-8305-74c25f31662e · outbound

This paper cites Learning Multiple Initial Solutions to Optimization Problems.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Learning Multiple Initial Solutions to Optimization Problems

Reference 35

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Observation 57bc6fa8-88cf-4830-a177-cab53de0f5b8 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Sys- tems, 36:8634–8652, 2023.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Sys- tems, 36:8634–8652, 2023

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.622404Z

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Observation 7a02912c-cd62-4dad-b69b-5270c4090adf · outbound

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

Generating Symbolic World Models via Test-time Scaling of Large Language Models ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

Reference 37

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Observation aa6afb8f-1814-45f2-a363-8dae05abc82a · outbound

This paper cites Generating consistent PDDL domains with Large Language Models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Generating consistent PDDL domains with Large Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.414679Z

Source-reported events for the cited work

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Observation 8b811352-2a25-4087-9114-a9c5b07014ac · outbound

This paper cites Inference scaling flaws: The limits of llm resampling with imperfect verifiers.arXiv preprint arXiv:2411.17501, 2024.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Inference scaling flaws: The limits of llm resampling with imperfect verifiers.arXiv preprint arXiv:2411.17501, 2024

Reference 39

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Source-reported events for the cited work

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Observation 138c330b-e603-41c1-9383-3aebb683c63d · outbound

This paper cites WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment.

Generating Symbolic World Models via Test-time Scaling of Large Language Models WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.423844Z

Source-reported events for the cited work

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Observation 02887bf2-501d-4228-854e-948372ef04ff · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Gemma: Open Models Based on Gemini Research and Technology

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.428515Z

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Observation 320494a9-972c-4a9b-aaf3-4c3a54ad206c · outbound

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

Generating Symbolic World Models via Test-time Scaling of Large Language Models Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.607314Z

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Observation d1ec938e-c08e-4c54-8447-311a147ecf4c · outbound

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

Generating Symbolic World Models via Test-time Scaling of Large Language Models LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBench

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.438262Z

Source-reported events for the cited work

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Observation 03ae988b-5ada-4c24-970e-d209af5d3491 · outbound

This paper cites On The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability.

Generating Symbolic World Models via Test-time Scaling of Large Language Models On The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.447954Z

Source-reported events for the cited work

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Observation 2b2e7a1c-ce55-4a01-8229-9cd14def1877 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.452286Z

Source-reported events for the cited work

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Observation 26aedf24-c089-4a68-a1c2-24a2e02fbdb8 · outbound

This paper cites Emergent Abilities of Large Language Models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Emergent Abilities of Large Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.457229Z

Source-reported events for the cited work

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Observation 7e4dc49f-163a-48a8-ad00-e8ea8df8ae46 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Chain-of-thought prompting elicits reasoning in large language models

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.592486Z

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Observation b7151f06-4a35-470d-95bf-a263b660de2d · outbound

This paper cites System 2 Attention (is something you might need too).

Generating Symbolic World Models via Test-time Scaling of Large Language Models System 2 Attention (is something you might need too)

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.466137Z

Source-reported events for the cited work

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Observation 1045e54b-a72d-44d0-a6ec-35c66fa8dbae · outbound

This paper cites Verbalized Machine Learning: Revisiting Machine Learning with Language Models.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Verbalized Machine Learning: Revisiting Machine Learning with Language Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.470962Z

Source-reported events for the cited work

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Observation 670baf85-dec8-40a9-8b0a-1045fe5539a2 · outbound

This paper cites Qwen2 Technical Report.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Qwen2 Technical Report

Reference 51

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Source-reported events for the cited work

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Observation 0db9d5d2-2838-4684-adc7-5b4f1e931cde · outbound

This paper cites Le, Denny Zhou, and Xinyun Chen.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Le, Denny Zhou, and Xinyun Chen

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.576067Z

Source-reported events for the cited work

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Observation 5d3b7035-f87b-412a-b727-b261da42ae26 · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Yi: Open Foundation Models by 01.AI

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.484908Z

Source-reported events for the cited work

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Observation 41055a6c-f42a-4147-ae5f-31763f762d3b · outbound

This paper cites Distilling System 2 into System 1.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Distilling System 2 into System 1

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.489671Z

Source-reported events for the cited work

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Observation cb0d4312-531b-41b3-a5bd-24554ff9ce11 · outbound

This paper cites TextGrad: Automatic "Differentiation" via Text.

Generating Symbolic World Models via Test-time Scaling of Large Language Models TextGrad: Automatic "Differentiation" via Text

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.494452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e390a31d-ece3-4680-8602-4e9b7f4b24a3 · outbound

This paper cites Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.499263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0135e484-0cab-4eed-8cc7-889552487b0a · outbound

This paper cites Generative Verifiers: Reward Modeling as Next-Token Prediction.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Generative Verifiers: Reward Modeling as Next-Token Prediction

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.504109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9755324-e6a7-4746-9e07-35f758271294 · outbound

This paper cites MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics.

Generating Symbolic World Models via Test-time Scaling of Large Language Models MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.509398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f78d30ca-a71c-44cf-bfd8-29d54df6cd81 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.561071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ac2a8a49-3c8e-4897-92cb-edec6482a32d · outbound

This paper cites Large Language Models Are Human-Level Prompt Engineers.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Large Language Models Are Human-Level Prompt Engineers

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.519535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0017a679-4b3c-4983-9544-091018a6b5b0 · outbound

This paper cites Plane- tarium: A rigorous benchmark for translating text to structured planning languages.arXiv preprint arXiv:2407.03321, 2024.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Plane- tarium: A rigorous benchmark for translating text to structured planning languages.arXiv preprint arXiv:2407.03321, 2024

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-08T21:45:45.524359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87adb92d-79da-48f4-b24a-c65f2c4e2186 · outbound

This paper cites object1 is washed and heated.

Generating Symbolic World Models via Test-time Scaling of Large Language Models object1 is washed and heated

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:45:46.545188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f993925a-28f3-40d8-bf4f-44d289741275 · outbound

This paper cites an unresolved cited work.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-08T21:45:46.528926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6022571f-e1b0-4246-8129-db0ae523b999 · outbound

This paper cites an unresolved cited work.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-08T21:45:46.513526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation d1d36373-ba35-402f-b684-c848f9aea5ad · inbound

CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization cites this paper.

CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization Generating Symbolic World Models via Test-time Scaling of Large Language Models

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-06T19:14:21.027074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdba0c82-df4a-4742-a488-ce638e579571 · inbound

Any House Any Task: Scalable Long-Horizon Planning for Abstract Human Tasks cites this paper.

Any House Any Task: Scalable Long-Horizon Planning for Abstract Human Tasks Generating Symbolic World Models via Test-time Scaling of Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T06:05:30.314068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b55257f8-e899-462e-a68e-8fb55168961d · inbound

Sample-Efficient Post-Training for LEGO Spatial-Physics Reasoning cites this paper.

Sample-Efficient Post-Training for LEGO Spatial-Physics Reasoning Generating Symbolic World Models via Test-time Scaling of Large Language Models

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:42:49.550411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.