Paper Citation Record · LEDGER

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations

As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2508.10841.

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

pith.paper-citation-record.v1
2508.10841 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:17:04.336383Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T13:48:11.732864Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T14:10:29.519146Z

Reference resolution

52 of 52 outbound references displayed

verified exact0
verified fuzzy36
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0cd60791-85dd-4b8b-a2ff-05290a97287a · outbound

This paper cites Reversing the cycle: self-supervised deep stereo through enhanced monocular distillation.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Reversing the cycle: self-supervised deep stereo through enhanced monocular distillation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:12.186779Z

Source-reported events for the cited work

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Observation 35099cbf-61a0-49a7-84c9-d07896a7d61c · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Emerg- ing properties in self-supervised vision transformers

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T20:16:59.321202Z

Source-reported events for the cited work

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Observation c335aee8-5f6f-4478-be03-749f5bc59b52 · outbound

This paper cites Pyramid stereo matching network.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Pyramid stereo matching network

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:11.984695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b2ab664b-1d9c-45bf-8d86-4e01e5beff75 · outbound

This paper cites Monster: Marry monodepth to stereo unleashes power.arXiv preprint arXiv:2501.08643,.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Monster: Marry monodepth to stereo unleashes power.arXiv preprint arXiv:2501.08643,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T20:16:59.556808Z

Source-reported events for the cited work

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Observation 1d48acd4-4ade-463a-99ca-846104b0f81b · outbound

This paper cites Carla: An open urban driv- ing simulator.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Carla: An open urban driv- ing simulator

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:11.771650Z

Source-reported events for the cited work

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Observation eefc9679-b6c5-41c6-bdd4-24b27ae61286 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:11.583264Z

Source-reported events for the cited work

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Observation 7756826f-c134-479e-ba96-c07553acb7ef · outbound

This paper cites Vision meets robotics: The kitti dataset.Interna- tional Journal of Robotics Research (IJRR), 2013.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Vision meets robotics: The kitti dataset.Interna- tional Journal of Robotics Research (IJRR), 2013

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:11.415465Z

Source-reported events for the cited work

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Observation f04b0d86-a468-430a-a215-5ae0272387a0 · outbound

This paper cites Digging into self-supervised monocular depth estimation.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Digging into self-supervised monocular depth estimation

Reference 8

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Source-reported events for the cited work

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Observation 0b996244-83ee-4385-8b74-4d4b16545996 · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284, 2020.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284, 2020

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:11.221691Z

Source-reported events for the cited work

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Observation 79b35938-8f30-46d4-bbce-a13b3bf92f6e · outbound

This paper cites Group-wise correlation stereo network.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Group-wise correlation stereo network

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:11.057923Z

Source-reported events for the cited work

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Observation c41aa348-6294-43d8-b8f1-b30f5ca9b262 · outbound

This paper cites DEFOM-Stereo: Depth Foundation Model Based Stereo Matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations DEFOM-Stereo: Depth Foundation Model Based Stereo Matching

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:00.399141Z

Source-reported events for the cited work

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Observation 49ed9d94-6bd5-4248-9df4-0169fb3e3e6b · outbound

This paper cites Emr-msf: Self- supervised recurrent monocular scene flow exploiting ego- motion rigidity.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Emr-msf: Self- supervised recurrent monocular scene flow exploiting ego- motion rigidity

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:10.834649Z

Source-reported events for the cited work

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Observation f68de9e8-fb14-4bec-976d-c7d614236a6f · outbound

This paper cites End-to-end learning of geometry and context for deep stereo regression.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations End-to-end learning of geometry and context for deep stereo regression

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:10.696392Z

Source-reported events for the cited work

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Observation 74647035-27e6-420f-9fc2-83a4d9c78a97 · outbound

This paper cites Kingma and Jimmy Ba.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Kingma and Jimmy Ba

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:00.606923Z

Source-reported events for the cited work

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Observation 9cc16761-da4d-4a56-aab4-c1d5d8d8f3f1 · outbound

This paper cites Occlusion aware stereo matching via cooperative unsupervised learning.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Occlusion aware stereo matching via cooperative unsupervised learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:10.503502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3e302ace-480e-41e6-aba1-e4368d318f93 · outbound

This paper cites Practical stereo matching via cascaded recurrent net- work with adaptive correlation.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Practical stereo matching via cascaded recurrent net- work with adaptive correlation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:10.345994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ceda91f8-4f8b-4286-9ef2-27a95feaaa61 · outbound

This paper cites Raft-stereo: Multilevel recurrent field transforms for stereo matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Raft-stereo: Multilevel recurrent field transforms for stereo matching

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:10.121459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 48cbd7bb-0e73-4c73-8e2c-36094675d1e4 · outbound

This paper cites Flow2stereo: Effective self-supervised learning of optical flow and stereo matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Flow2stereo: Effective self-supervised learning of optical flow and stereo matching

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:09.971046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 13245431-28a2-47bb-9378-87b05cc93348 · outbound

This paper cites A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:01.186830Z

Source-reported events for the cited work

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Observation 714f86a6-698e-482a-aa5c-610525c7d3c2 · outbound

This paper cites Object scene flow for au- tonomous vehicles.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Object scene flow for au- tonomous vehicles

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:09.710736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4170943b-12c9-4663-8600-ec16802f2c85 · outbound

This paper cites Zoom and learn: Generalizing deep stereo matching to novel domains.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Zoom and learn: Generalizing deep stereo matching to novel domains

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:09.571054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cd68f687-0526-4100-8960-ecf8c18f76bd · outbound

This paper cites A taxonomy and evaluation of dense two-frame stereo correspondence algo- rithms.International journal of computer vision, 47(1):7– 42, 2002.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations A taxonomy and evaluation of dense two-frame stereo correspondence algo- rithms.International journal of computer vision, 47(1):7– 42, 2002

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:09.409126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a7c3e986-0730-4f4a-be08-9737c222feb4 · outbound

This paper cites High-resolution stereo datasets with subpixel-accurate ground truth.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations High-resolution stereo datasets with subpixel-accurate ground truth

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:09.293800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0d4f92ef-3c6d-436a-8e23-64a0aea3883f · outbound

This paper cites A multi-view stereo benchmark with high- resolution images and multi-camera videos.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations A multi-view stereo benchmark with high- resolution images and multi-camera videos

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:08.964150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ed6a0bd2-969f-4e15-b5be-8e49cdfceeaa · outbound

This paper cites Sgm-nets: Semi-global matching with neural networks.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Sgm-nets: Semi-global matching with neural networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:08.634913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cfc6610e-9dda-4432-9963-4422021c441d · outbound

This paper cites Cfnet: Cascade and fused cost volume for robust stereo matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Cfnet: Cascade and fused cost volume for robust stereo matching

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:08.360132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5263bfb1-ad2e-4064-bc53-62b6364b3e8a · outbound

This paper cites an unresolved cited work.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-05T20:17:08.087580Z

Source-reported events for the cited work

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Observation ee79fb6c-e866-48bf-9eb9-f8ae4a6e63cd · outbound

This paper cites an unresolved cited work.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-05T20:17:07.838765Z

Source-reported events for the cited work

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Observation cbf27f31-73f8-4154-bf99-5c9e29f4e075 · outbound

This paper cites Adastereo: a simple and efficient ap- proach for adaptive stereo matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Adastereo: a simple and efficient ap- proach for adaptive stereo matching

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:07.560143Z

Source-reported events for the cited work

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Observation 2c367d83-c1ec-4fd3-ab92-c84f1cf78abc · outbound

This paper cites Real-time self-adaptive deep stereo.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Real-time self-adaptive deep stereo

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:07.281817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68464e3b-5d8e-4c60-b06b-bd9cae2f1f0e · outbound

This paper cites Nerf-supervised deep stereo.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Nerf-supervised deep stereo

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:07.102524Z

Source-reported events for the cited work

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Observation c8e3752a-2fef-4347-8f96-152f34a0cd50 · outbound

This paper cites Weakly supervised learning of deep metrics for stereo recon- struction.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Weakly supervised learning of deep metrics for stereo recon- struction

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:06.878353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 64e89f7a-c8ae-4eda-8c65-ef8cb3c8f1e0 · outbound

This paper cites Faster self-adaptive deep stereo.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Faster self-adaptive deep stereo

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:06.671391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7ac80098-22c4-4e44-918a-065ee42a0c84 · outbound

This paper cites Parallax attention for unsupervised stereo correspondence learning.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Parallax attention for unsupervised stereo correspondence learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:06.548340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 47f031d1-4de8-48b7-8115-05623f674383 · outbound

This paper cites Selective-stereo: Adaptive frequency information selection for stereo matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Selective-stereo: Adaptive frequency information selection for stereo matching

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:06.425634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6e2fba4b-9a71-4340-9059-5eb47d82229e · outbound

This paper cites ZeroStereo: Zero-shot Stereo Matching from Single Images.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations ZeroStereo: Zero-shot Stereo Matching from Single Images

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:03.035389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b34380d5-c28e-4724-8524-c7a873241305 · outbound

This paper cites Dualnet: Ro- bust self-supervised stereo matching with pseudo-label su- pervision.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Dualnet: Ro- bust self-supervised stereo matching with pseudo-label su- pervision

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:06.192526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 266cc803-6d6f-4d9e-9ed0-66c292f9ffa3 · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:03.194370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abb2ea97-a41d-499d-843d-66b3779af9b6 · outbound

This paper cites FoundationStereo: Zero-Shot Stereo Matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations FoundationStereo: Zero-Shot Stereo Matching

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:03.244887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12d12ad8-f28c-4004-8d06-be9e02fdc881 · outbound

This paper cites Iterative geometry encoding volume for stereo matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Iterative geometry encoding volume for stereo matching

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:06.068102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2b40580e-3f1c-4a43-b447-e85f267f0845 · outbound

This paper cites Aanet: Adaptive aggrega- tion network for efficient stereo matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Aanet: Adaptive aggrega- tion network for efficient stereo matching

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:05.978311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a9963f6e-130a-40f3-900e-c12234c37d2b · outbound

This paper cites Drivingstereo: A large-scale dataset for stereo matching in autonomous driving scenarios.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Drivingstereo: A large-scale dataset for stereo matching in autonomous driving scenarios

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:05.826233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ce389087-64c0-4b7a-913f-ab7e5aaa452c · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Depth anything: Unleashing the power of large-scale unlabeled data

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:03.547485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d8bd1a2-e015-4ff8-a1d5-432b50f26218 · outbound

This paper cites Depth any- thing v2.Advances in Neural Information Processing Sys- tems, 37:21875–21911, 2024.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Depth any- thing v2.Advances in Neural Information Processing Sys- tems, 37:21875–21911, 2024

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:03.640374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caadbb47-5e50-422c-9fa7-0f9efaf10d70 · outbound

This paper cites Unsupervised hierarchical iterative tile refinement network with 3d planar segmentation loss.IEEE Robotics and Au- tomation Letters, 9(3):2678–2685, 2024.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Unsupervised hierarchical iterative tile refinement network with 3d planar segmentation loss.IEEE Robotics and Au- tomation Letters, 9(3):2678–2685, 2024

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:05.613672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cbbc85d4-615b-4fe2-9c31-8fda40d815f0 · outbound

This paper cites Semi- stereo: A universal stereo matching framework for imper- fect data via semi-supervised learning.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Semi- stereo: A universal stereo matching framework for imper- fect data via semi-supervised learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:05.446925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6ca05b82-a9f4-46fb-9fcc-47bd61b73a5d · outbound

This paper cites Eai-stereo: Error aware iterative network for stereo matching.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Eai-stereo: Error aware iterative network for stereo matching

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:05.302087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 24157ec6-c011-4512-9fb0-4b2f7725bad8 · outbound

This paper cites High-frequency stereo match- ing network.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations High-frequency stereo match- ing network

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:05.176540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 625f186b-396b-45d1-a254-ca17f5e6fd2c · outbound

This paper cites Self-Supervised Learning for Stereo Matching with Self-Improving Ability.

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Self-Supervised Learning for Stereo Matching with Self-Improving Ability

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:04.083714Z

Source-reported events for the cited work

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Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Consistency-aware self-training for iterative-based stereo matching

Reference 50

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Observation 387d69cc-7c84-4219-98e4-34714cfa7c26 · outbound

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Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations Unresolved cited work

Reference 51

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Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations #"$"%&"'()*+

Reference 52

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Pith citing papers

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Fidelity of Machine Learned Potentials: Quantitative Assessment for Protonated Oxalate cites this paper.

Fidelity of Machine Learned Potentials: Quantitative Assessment for Protonated Oxalate Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations

Reference 9

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