Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T18:46:34.595228Z
Paper Citation Record · LEDGER
Towards Trustworthy Hypergraph Neural Networks under Label Noise
As of 9 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2608.04377.
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 2026-08-09T06:31:02.800959+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
57 of 57 outbound references displayed
- verified exact1
- verified fuzzy43
- unresolved13
- parse uncertain0
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 8ea98494-c574-4a47-b6dd-1c996bfa604f · outbound
This paper cites Learning with hyper- graphs: Clustering, classification, and embedding,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Learning with hyper- graphs: Clustering, classification, and embedding,
Reference 1
- Resolution
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Source-reported events for the cited work
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Observation 14c62951-2dbd-425d-bb34-d412ab52698a · outbound
This paper cites A survey on hypergraph representation learning,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise A survey on hypergraph representation learning,
Reference 2
- Resolution
- verified fuzzy
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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 f1dc20db-1364-4de7-bef0-1f1bcab3071a · outbound
This paper cites Berge, Hypergraphs: combinatorics of finite sets.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Berge, Hypergraphs: combinatorics of finite sets
Reference 3
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 4c101deb-f13b-4ffa-a539-dc7758c7c847 · outbound
This paper cites Hypergraph topolog- ical quantities for tagged social networks,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Hypergraph topolog- ical quantities for tagged social networks,
Reference 4
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 93ea76c6-cd51-4510-a667-64686e4dc761 · outbound
This paper cites Social influence maximization in hypergraph in social networks,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Social influence maximization in hypergraph in social networks,
Reference 5
- Resolution
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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 96475dbe-2e2f-4999-a320-7d85e8579c6a · outbound
This paper cites Self-supervised hypergraph transformer for recommender systems,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Self-supervised hypergraph transformer for recommender systems,
Reference 6
- Resolution
- verified fuzzy
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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 4c8f42e3-b420-4508-9b5a-7142aa7f77ee · outbound
This paper cites Next-item recommendation with sequential hypergraphs,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Next-item recommendation with sequential hypergraphs,
Reference 7
- Resolution
- verified fuzzy
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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 52c10ae6-c39e-49a7-bda7-825077a0b686 · outbound
This paper cites Hypergraph models of biological networks to identify genes critical to pathogenic viral response,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Hypergraph models of biological networks to identify genes critical to pathogenic viral response,
Reference 8
- Resolution
- verified fuzzy
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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 71efebc4-9355-4f77-92d9-87d821048c94 · outbound
This paper cites Hypergraphs and cellu- lar networks,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Hypergraphs and cellu- lar networks,
Reference 9
- Resolution
- verified fuzzy
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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 0c967766-b7fa-462c-a37d-de50ad100885 · outbound
This paper cites A survey on hypergraph neural networks: an in-depth and step-by-step guide,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise A survey on hypergraph neural networks: an in-depth and step-by-step guide,
Reference 10
- Resolution
- verified fuzzy
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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 01f121bd-8d28-41f1-9f77-35d0265a42e2 · outbound
This paper cites Hypergraph convolution on nodes- hyperedges network for semi-supervised node classification,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Hypergraph convolution on nodes- hyperedges network for semi-supervised node classification,
Reference 11
- Resolution
- verified fuzzy
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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 b8e8b4b0-425a-4d92-abbc-1afeb33dc873 · outbound
This paper cites Nhp: Neural hypergraph link prediction,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Nhp: Neural hypergraph link prediction,
Reference 12
- Resolution
- verified fuzzy
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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 0658be23-deb9-4d25-a7b2-bb54d0863a8e · outbound
This paper cites Link prediction in social networks based on hypergraph,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Link prediction in social networks based on hypergraph,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.269047Z
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 ff08485f-8799-450c-b4ef-5c7a9884cfb6 · outbound
This paper cites Hypersynergyx: Synergistic drug combination prediction via hypergraph modeling and knowledge graph-enhanced retrieval- augmented generation,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Hypersynergyx: Synergistic drug combination prediction via hypergraph modeling and knowledge graph-enhanced retrieval- augmented generation,
Reference 14
- Resolution
- verified fuzzy
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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 5f968c1d-00db-4d8d-ae01-8f873b5272b8 · outbound
This paper cites Graph topology adaptive judgment against node label noise,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Graph topology adaptive judgment against node label noise,
Reference 15
- Resolution
- verified fuzzy
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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 b1ae4bcb-2e42-4cf6-a194-1122f252429d · outbound
This paper cites Classification in the presence of label noise: a survey,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Classification in the presence of label noise: a survey,
Reference 16
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e07dbce0-6b8d-47fd-a8c8-b2ff1fb5f364 · outbound
This paper cites Noise-robust classification with hypergraph neural network.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Noise-robust classification with hypergraph neural network
Reference 17
- Resolution
- verified exact
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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 b0ad64f4-22ec-4657-9c85-1b4741a3c794 · outbound
This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Co-teaching: Robust training of deep neural networks with extremely noisy labels,
Reference 18
- Resolution
- verified fuzzy
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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 d1f4eaf3-1578-4abe-91e5-70dbb99e1b82 · outbound
This paper cites How does disagreement help generalization against label corruption,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise How does disagreement help generalization against label corruption,
Reference 19
- Resolution
- verified fuzzy
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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 5488bb63-fa5e-48a9-a67d-bc7ee96f97e0 · outbound
This paper cites Decoupling “when to up- date.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Decoupling “when to up- date
Reference 20
- Resolution
- verified fuzzy
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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 cad091fc-25c1-4562-802a-a3c7f5aee9b5 · outbound
This paper cites Dividemix: Learning with noisy labels as semi-supervised learning,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Dividemix: Learning with noisy labels as semi-supervised learning,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.196492Z
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 504574d1-5aac-428b-9866-52807d4683bf · outbound
This paper cites Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels,
Reference 22
- Resolution
- verified fuzzy
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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 f74f083a-bf38-441f-b81d-bb6bcbaa6ab4 · outbound
This paper cites Training deep neural- networks using a noise adaptation layer,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Training deep neural- networks using a noise adaptation layer,
Reference 23
- Resolution
- verified fuzzy
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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 c6508657-28d9-4428-bdc0-5b64051b7959 · outbound
This paper cites Dimensionality-driven learn- ing with noisy labels,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Dimensionality-driven learn- ing with noisy labels,
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.165395Z
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 faac2e63-3e7b-4c6e-809f-b76959e82802 · outbound
This paper cites Making deep neural networks robust to label noise: a loss correction approach,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Making deep neural networks robust to label noise: a loss correction approach,
Reference 25
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00cc8a69-5784-467b-84ce-f5477ba9e1ec · outbound
This paper cites Training deep neural networks on noisy labels with bootstrapping,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Training deep neural networks on noisy labels with bootstrapping,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.154795Z
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 a242e119-3d2d-4842-babb-32acb0703205 · outbound
This paper cites Nrgnn: Learning a label noise resistant graph neural network on sparsely and noisily labeled graphs,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Nrgnn: Learning a label noise resistant graph neural network on sparsely and noisily labeled graphs,
Reference 27
- Resolution
- verified fuzzy
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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 a7da06fa-e0f6-4475-b931-81a732285406 · outbound
This paper cites Robust training of graph neural networks via noise governance,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Robust training of graph neural networks via noise governance,
Reference 28
- Resolution
- verified fuzzy
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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 a7f4f690-4fa4-4368-bc8e-5be06c1608d2 · outbound
This paper cites Unified robust training for graph neural networks against label noise,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Unified robust training for graph neural networks against label noise,
Reference 29
- Resolution
- verified fuzzy
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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 63c5e77c-1685-4f89-81c8-9b7fc038d05f · outbound
This paper cites Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions
Reference 30
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d3f866cf-d07c-4399-9901-70430d8e161e · outbound
This paper cites Adversarial label- flipping attack and defense for graph neural networks,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Adversarial label- flipping attack and defense for graph neural networks,
Reference 31
- Resolution
- verified fuzzy
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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 3cca8e0a-3551-4019-9b79-d2f96ff92e2e · outbound
This paper cites Learning on graphs under label noise,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Learning on graphs under label noise,
Reference 32
- Resolution
- verified fuzzy
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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 63d728c1-0771-4e58-bb2a-79e246092ebd · outbound
This paper cites Robust loss functions under label noise for deep neural networks,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Robust loss functions under label noise for deep neural networks,
Reference 33
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fec465b3-c34b-4167-acc1-ee74c59b063c · outbound
This paper cites NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise.
Towards Trustworthy Hypergraph Neural Networks under Label Noise NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
Reference 34
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0573b436-6d37-46b2-8405-cec3092abc4a · outbound
This paper cites Hypergraph neural networks,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Hypergraph neural networks,
Reference 35
- Resolution
- verified fuzzy
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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 e530b141-98f2-4684-860f-c34fd0bb13cf · outbound
This paper cites HNHN: Hypergraph Networks with Hyperedge Neurons.
Towards Trustworthy Hypergraph Neural Networks under Label Noise HNHN: Hypergraph Networks with Hyperedge Neurons
Reference 36
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d081d4e-d1f2-43aa-8252-d91b192d50e1 · outbound
This paper cites Hypergcn: A new method for training graph convolutional networks on hypergraphs,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Hypergcn: A new method for training graph convolutional networks on hypergraphs,
Reference 37
- Resolution
- verified fuzzy
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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 60deabe1-a39f-4cb9-986e-4b4f117eb3a8 · outbound
This paper cites HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphs.
Towards Trustworthy Hypergraph Neural Networks under Label Noise HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphs
Reference 38
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b8851817-1560-4af0-b754-f5af255ed2f7 · outbound
This paper cites UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks.
Towards Trustworthy Hypergraph Neural Networks under Label Noise UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks
Reference 39
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e10f9d15-e481-4787-b62f-b901605b5a20 · outbound
This paper cites You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.
Towards Trustworthy Hypergraph Neural Networks under Label Noise You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks
Reference 40
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ce841f0-ca1f-45d7-a590-ce070c510ed9 · outbound
This paper cites Hypergraph dynamic system,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Hypergraph dynamic system,
Reference 41
- Resolution
- verified fuzzy
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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 d27611f7-5086-4471-a5fb-6659e5be6e06 · outbound
This paper cites Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing
Reference 42
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 05dcdc63-f715-4e56-b790-7ee59edabfaf · outbound
This paper cites K-hop hypergraph neural network: A comprehensive aggregation approach,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise K-hop hypergraph neural network: A comprehensive aggregation approach,
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.059518Z
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 0bbad9bb-ccd8-466d-a337-f679530b204b · outbound
This paper cites Un- derstanding deep learning requires rethinking generalization,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Un- derstanding deep learning requires rethinking generalization,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.049409Z
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 a04b0022-6c60-4112-bae5-de9fb0c66fae · outbound
This paper cites Contrastive learning of graphs under label noise,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Contrastive learning of graphs under label noise,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.038681Z
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 deaba07e-47e9-4d71-9658-d1b9cf257014 · outbound
This paper cites Tackling over-smoothing on hypergraphs: A ricci flow-guided neural diffusion approach,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Tackling over-smoothing on hypergraphs: A ricci flow-guided neural diffusion approach,
Reference 46
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d4f8efa9-de8d-4aeb-b69e-765f399ad7bc · outbound
This paper cites Combating noisy labels by agreement: A joint training method with co-regularization,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Combating noisy labels by agreement: A joint training method with co-regularization,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.027647Z
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 a9143d88-aa10-409b-844c-15c4e2f7aea6 · outbound
This paper cites Normalized loss functions for deep learning with noisy labels,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Normalized loss functions for deep learning with noisy labels,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.016454Z
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 9ddae215-2f1a-4905-b8e8-3171dd2b1d97 · outbound
This paper cites Symmetric cross entropy for robust learning with noisy labels,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Symmetric cross entropy for robust learning with noisy labels,
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:35.005169Z
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 3ca7f42c-7dba-441e-bf6b-89ff62247ec9 · outbound
This paper cites Clnode: Curriculum learning for node classification,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Clnode: Curriculum learning for node classification,
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:34.993307Z
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 bfa27209-775e-4e4a-a015-d3d54ebea5d7 · outbound
This paper cites Learning Graph Neural Networks with Noisy Labels.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Learning Graph Neural Networks with Noisy Labels
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:46:34.574912Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0db2af1a-762d-4c5e-b3b3-2cbd1c2a3f24 · outbound
This paper cites Node similarity preserving graph convolutional networks,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Node similarity preserving graph convolutional networks,
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:34.981803Z
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 fa5027c1-48b9-4f32-91fe-2a4b9dcb2323 · outbound
This paper cites Inferring anchor links across multiple heterogeneous social networks,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Inferring anchor links across multiple heterogeneous social networks,
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:34.970042Z
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 bdb6ad5f-ff4d-4d39-9b0a-5fece0dbf49a · outbound
This paper cites node2vec: Scalable feature learning for networks,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise node2vec: Scalable feature learning for networks,
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:34.958943Z
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 108e6820-6df3-4c02-a85f-c7aa3a8db1c7 · outbound
This paper cites Current and future directions in network biology,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise Current and future directions in network biology,
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:34.947546Z
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 495d6b1f-a9b9-4ee9-a87a-412e8f8b1541 · outbound
This paper cites 3d shapenets: A deep representation for volumetric shapes,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise 3d shapenets: A deep representation for volumetric shapes,
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:46:34.591701Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e9090645-8e4e-46f0-9034-dc1b848dc693 · outbound
This paper cites On vi- sual similarity based 3d model retrieval,.
Towards Trustworthy Hypergraph Neural Networks under Label Noise On vi- sual similarity based 3d model retrieval,
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:46:34.929045Z
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
No inbound Pith citation observations are available.