Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T13:16:09.094224Z
Paper Citation Record · LEDGER
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity
As of 9 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2502.07293.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
52 of 52 outbound references displayed
- verified exact1
- verified fuzzy20
- unresolved31
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 0bd04254-060d-4fa9-b454-4acb9e0cc042 · outbound
This paper cites Four Generations of High -Dimensional Neural Network Potentials.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Four Generations of High -Dimensional Neural Network Potentials
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.960798Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation cfd9eef6-3da1-41b4-91cc-195e09c294df · outbound
This paper cites Perspective: Machine learning potentials for atomistic simulations.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Perspective: Machine learning potentials for atomistic simulations
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.945583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 46e72e7a-79cb-434a-917a-580e1e4e2524 · outbound
This paper cites Machine-learning interatomic potentials for materials science.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Machine-learning interatomic potentials for materials science
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.930264Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d8cfee27-10bb-45cb-822e-bc6c7bcd8066 · outbound
This paper cites L., Caro, M.
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.914186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d4eeb523-04b4-4562-be57-635bbaa25e5d · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.898042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 251dda44-4761-4295-9684-581276edabfb · outbound
This paper cites P., Batatia, I., Arany, E.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity P., Batatia, I., Arany, E
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.883022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 209d8699-41cd-4510-8435-41ed3f9cc53f · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.867894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 660fa2a9-f54f-46dc-abeb-1cf32132d31b · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.852568Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 154d825b-9276-443a-87dc-aa01aead05d1 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 9
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.835437Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e875f48a-a4b8-46ac-8298-7e51cfafa685 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.820170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f7568adb-8883-4223-b639-8ddfd5a6cf1a · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.803153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8a28e432-7c82-4dc7-abaa-499264ff0672 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.787659Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b48280a3-d5d8-486c-aba9-2039bbbc2f1f · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 13
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.772495Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 98cc9df5-b351-4549-8952-416dee6685aa · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.756432Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d78310b1-d0aa-4d9a-9ec9-3542dee96ba6 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 15
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.740281Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7880cefb-5081-4a69-845e-8511ef34eb74 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.725070Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 195b10ed-9907-4296-b8ec-75807c0c0eba · outbound
This paper cites Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:08.800935Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46fba186-fe84-443e-ab75-2ff4592e11cc · outbound
This paper cites D., Gardner, J.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity D., Gardner, J
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.707320Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 61e921ba-e9bb-4fbf-819e-1208c2c9c94a · outbound
This paper cites Statistical Modeling: The Two Cultures.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Statistical Modeling: The Two Cultures
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.691123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 95f38a79-bb89-468f-a991-f319a2509f98 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.672497Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 20afa78b-7c48-4ea3-b7e2-8bcdd91e19d9 · outbound
This paper cites H., Smith, J.
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.654481Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f250fdc2-96b7-4715-87fd-7ad7335eb6d1 · outbound
This paper cites Atomic cluster expansion for accurate and transferable interatomic potentials.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Atomic cluster expansion for accurate and transferable interatomic potentials
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.638396Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 94c04bcc-6a9b-4853-b480-e9418bc8e925 · outbound
This paper cites Atomic cluster expansion of scalar, vectorial, and tensorial properties including magnetism and charge transfer.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Atomic cluster expansion of scalar, vectorial, and tensorial properties including magnetism and charge transfer
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.621899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d981f3f7-a959-4d28-89e8-df0eff5a5793 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 24
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.604682Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 179dab5a-a885-4e23-b21d-7f60f5f76a17 · outbound
This paper cites & Ong, S.
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:08.839336Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7543d028-9671-415a-ba10-14914626ca42 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 26
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.576538Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e090a24a-446f-43c2-ba70-9db177d4656d · outbound
This paper cites W., Wood, B.
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:08.849680Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d161958-aaa1-4801-a11c-3eb0e233fa0e · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 28
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.548921Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 3d2736b1-770e-420d-9a10-d2d22bff7d26 · outbound
This paper cites Freitas, L.
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:08.975823Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1ba78239-d637-4b79-badc-747ccf5b3db7 · outbound
This paper cites A foundation model for atomistic materials chemistry.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity A foundation model for atomistic materials chemistry
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:08.980923Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 332d7489-a393-4b5c-9be5-549a49b84390 · outbound
This paper cites & Smith, J.
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.530284Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 425ec337-1c4a-4043-82e6-fad255fd3800 · outbound
This paper cites S., Gubaev, K., Podryabinkin, E.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity S., Gubaev, K., Podryabinkin, E
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.513218Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d9b715f2-3603-407e-ba5f-19b397528aaa · outbound
This paper cites A new frontier for Hopfield networks.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity A new frontier for Hopfield networks
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.495464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 64087484-274d-4c5d-a740-f62384b4d795 · outbound
This paper cites J., Gutfreund, H.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity J., Gutfreund, H
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.477863Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d8acdc4e-bb5b-4c24-b3e5-a531cb2592ea · outbound
This paper cites KAN: Kolmogorov-Arnold Networks.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity KAN: Kolmogorov-Arnold Networks
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:09.006522Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 071a6f00-0be5-4789-8ead-9fc86494bf2e · outbound
This paper cites & Vermet, F.
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.461339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 4bb683c5-5946-46fe-80d5-3e948b552855 · outbound
This paper cites GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:09.016809Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e1b07e5-b651-46b1-9011-1be8e7dd748a · outbound
This paper cites EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:09.022230Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b8e64a12-a155-4bae-99a0-858fa8da2b6a · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:09.027386Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b064259-51df-449c-8544-b675c4a752fc · outbound
This paper cites DPA-2: a large atomic model as a multi-task learner.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity DPA-2: a large atomic model as a multi-task learner
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:09.032607Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2d98d559-f45b-4860-a655-8496dd533b08 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 41
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.433213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation dcbc639e-ba4e-4d3d-b657-f4d12c6e5265 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 42
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.416289Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 93303447-184e-417c-ab86-cb7651edaf07 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 43
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.398474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 60087a0f-1bae-47f2-8761-23f7eacbf4c5 · outbound
This paper cites Copper ion liquid-like thermoelectrics.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Copper ion liquid-like thermoelectrics
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.380772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 59a2120a-ad0f-4352-b92b-cf529d99db44 · outbound
This paper cites & Chou, M.-Y.
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.363298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 6409e522-5664-4e53-a949-9f6b63029045 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.345774Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7617e56c-c55a-4782-97dc-33ee571e2e97 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 47
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T13:16:09.329091Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c22d0406-5ead-4608-bd9b-91ff617f0803 · outbound
This paper cites A Pre-trained Deep Potential Model for Sulfide Solid Electrolytes with Broad Coverage and High Accuracy.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity A Pre-trained Deep Potential Model for Sulfide Solid Electrolytes with Broad Coverage and High Accuracy
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T13:16:09.170064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 9bb12b61-52d1-459f-a533-b0357d2d4bd9 · outbound
This paper cites S., Gubaev, K., Podryabinkin, E.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity S., Gubaev, K., Podryabinkin, E
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.312038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2d147d6b-39f2-4c58-aa33-c17565e14ad2 · outbound
This paper cites First-principles Phonon Calculations with Phonopy and Phono3py.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity First-principles Phonon Calculations with Phonopy and Phono3py
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.295305Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 049d4a13-bb06-4732-a67e-4c5750363032 · outbound
This paper cites & Tanaka, I.
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T13:16:09.279565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 87238966-9aaa-4a0d-9d6b-330792c2f596 · outbound
This paper cites an unresolved cited work.
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity Unresolved cited work
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:16:09.094224Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.