Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:51:14.924742Z
Paper Citation Record · LEDGER
As of 14 August 2026, this Paper Citation Record lists 100 of 100 outbound references and 2 inbound Pith citation observations for arXiv:2501.04062.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:51:14.924742Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-11T01:46:15.489550Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T21:51:24.176631Z
100 of 100 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 0b56b1b3-fdca-4d58-a45b-1e98945957ba · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: High Performance Computing in Science and Engineering: Second International Conference, HPCSE 2015, Sol´ aˇ n, Czech Republic, May 25-28, 2015, Revised Selected Papers 2, pp
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Observation c7dfffe4-14a0-4a2d-b2cc-f2eb393ed8b0 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: Advances in Nonlinear Dynamics, pp
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Observation 33e1dc7d-cdcf-41cf-a769-9d722873b82f · outbound
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Observation 8165dbc7-c4b3-4795-8cfa-6047fe471725 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Unresolved cited work
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Observation e99f0205-7c55-4ef6-853e-acad0b9b21e9 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono CEAS Space Journal 7(3), 335–346 (2015)
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Observation 16f7809b-e786-48ef-a335-b82ac96b23c6 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Multibody System Dynamics39(1-2), 3–20 (2017)
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Observation b124bd42-d727-4936-90b1-edd6417bcda9 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: AIAA Scitech 2020 Forum, p
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Observation 5942c674-f7bb-47d8-8af3-8c3045b3940a · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Computers & Graphics 116, 23 ' & $ % You ’ r e an e x p e r t i n t h e PyChrono s i m u l a t o r
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Observation 10460a19-a0cc-4559-8107-d0f3a169497b · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: 2017 International Joint Conference on Neural Networks (IJCNN), pp
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Observation 9f72832a-dab9-41dc-8bb7-878292c54395 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp
Reference 10
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Observation 312c09d3-d06a-4c87-a285-679df6f14593 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono SRDA: Generating Instance Segmentation Annotation Via Scanning, Reasoning And Domain Adaptation
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Observation bd66e7d5-efd1-4e92-9f6c-23fcea3eca00 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: Com- putational Science and Computational Intelligence (CSCI), 2016 International Conference On, pp
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Observation 6ce647c3-c461-4298-ba97-34467c3d759f · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: Military Technologies (ICMT), 2017 International Conference On, pp
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Observation a11c5f8f-dbf0-4608-a6dd-0ac6c7079858 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: Ground Vehicle Systems Engineering and Technology Symposium (2017)
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Observation c6137c5f-ecb9-4d30-bfe5-4e609b80a314 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono IEEE Transactions on Robotics (2023) 24
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Observation 1d2c3ad5-3258-446e-9aa8-ebe1b88b1d2d · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Agriculture 14(3), 499 (2024)
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Observation 3f58e298-367b-4858-9f8e-6a5503751958 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Journal of Marine Science and Engineering 12(5), 701 (2024)
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Observation a46f41d9-c74a-4ff9-8ad1-788b806e078a · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Vibroengineering PROCEDIA 18, 123–127 (2018)
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Observation 0b0f2cb5-3d62-4e0b-94de-be46717da9bd · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: 11th International SPHERIC Workshop – Munich Germany, June 14-16, 2016 (2016)
Reference 19
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Observation c327e00b-b597-4e39-adba-084ce2c4f9f6 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono KSCE Journal of Civil Engineering, 1–10 (2019)
Reference 20
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Observation 2e2a1c52-e4c3-4efd-9b33-06213e92aef3 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: Fluid Power Systems Technology, vol
Reference 21
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Observation abd94c6e-cc50-419b-a296-542c96119a6f · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition, pp
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Observation 96feadfd-9c5d-45c8-b4fe-5de2dca44af5 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Journal of Engineering for Gas Turbines and Power 141(4), 041014 (2019)
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: Proceedings of the European Wave and Tidal Energy Conference, vol
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Observation 231eb5eb-59a0-47bc-85a9-ddda5f37ee85 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: SPE Latin American and Caribbean Petroleum Engineering Conference (2020)
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono https://groups.google.com/forum/#! forum/projectchrono
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Observation 54a81346-b687-4d3d-b92b-64d3873d8d34 · outbound
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Observation 578ee016-fc47-4683-9ab8-53db1add5cb9 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono https://hub.docker.com/ r/uwsbel/projectchrono
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Observation 49b61c08-fd92-4013-a3f7-761a70703851 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono https://github.com/projectchrono/ chrono
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Observation 9e28797a-50b8-481a-8cac-c18306d47493 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Scaling Laws for Neural Language Models
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Observation fe5f9caa-1325-4a3b-a17d-5ed396aa82b9 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Training Compute-Optimal Large Language Models
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Observation 35815adc-6ef1-4a80-b6a1-26915d786ed9 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Emergent Abilities of Large Language Models
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Observation c75ddbb2-933e-4ca9-9c1d-61cf63755da4 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Unresolved cited work
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Observation d9958f12-4e3f-471c-8278-d0935a81280d · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Language Models are Few-Shot Learners
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Observation e1ef2698-35b8-440f-8aa0-f4bd4fc83cf2 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Gemini: A Family of Highly Capable Multimodal Models
Reference 36
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Observation a30d8e1a-5b1b-455b-b41e-58e56a3cae29 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono https: //www-cdn.anthropic.com/bd2a28d2535bfb0494cc8e2a3bf135d2e7523226/ Model-Card-Claude-2.pdf
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Observation e6ea2325-ae03-4383-83cf-c045cf0aee1b · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono ACM computing surveys (csur) 53(3), 1–34 (2020)
Reference 38
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Observation 7e9139a2-8ccd-480f-8ef4-8fcf8bc2d78c · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Advances in neural information processing systems 35, 24824–24837 (2022)
Reference 39
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Observation d634c8e0-35eb-4b2f-87d6-14e154003494 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Show Your Work: Scratchpads for Intermediate Computation with Language Models
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Observation 34e33a1f-fbde-47be-8efa-2324bd0c6434 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono PPT: Pre-trained Prompt Tuning for Few-shot Learning
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Observation 069e3b93-c481-46ef-9e89-64ee2033c155 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
Reference 42
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Observation 2ab9b42e-8f20-4333-a63a-0e58ecfdfdf8 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Prefix-Tuning: Optimizing Continuous Prompts for Generation
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Observation 16cc91be-4bd0-4857-ae56-9c4564bb95c0 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: The 2023 Conference on Empirical Methods in Natural Language Processing (2023)
Reference 44
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Observation 08c410ff-e619-461a-97dd-bd0b3c0a7964 · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono In: International Conference on Learning Representations (2022)
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
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Observation 18f82041-0a4e-4a14-b812-a6b2f057587f · outbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono OMPGPT: A Generative Pre-trained Transformer Model for OpenMP
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono https://github.com/meta-llama/ llama3/blob/main/MODEL CARD.md
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Multibody System Dynamics, 1–23 (2024) 28
Reference 50
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Journal of Machine Learning for Modeling and Computing 4(4) (2023)
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Journal of Computational Physics 378, 686–707 (2019) https://doi.org/10.1016/j.jcp.2018.10.045
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono IEEE Transactions on Neural Networks and Learning Systems (2023)
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Reference 64
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Reference 68
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono Advances in Neural Information Processing Systems 35, 1950–1965 (2022)
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Reference 72
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Reference 73
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