Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2106.09291.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-27T10:33:02.954683Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T09:07:47.651991Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation d6af75c1-e20b-4cff-96c8-1839bc26ab68 · inbound
Can LLMs Learn to Reason Robustly under Noisy Supervision? cites this paper.
Can LLMs Learn to Reason Robustly under Noisy Supervision? Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T17:08:01.300816Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation fb560bc0-9118-4a72-b130-89ab559bc0f5 · inbound
See Through the Noise: Improving Domain Generalization in Gaze Estimation cites this paper.
See Through the Noise: Improving Domain Generalization in Gaze Estimation Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:37:53.965599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation fac4d633-4e21-49ce-b97a-b930b5cc3a3b · inbound
Holistic Reliability Propagation: Decoupling Annotation and Prediction for Robust Noisy-Label cites this paper.
Holistic Reliability Propagation: Decoupling Annotation and Prediction for Robust Noisy-Label Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T05:23:58.318324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a75fd643-7666-4c8f-805a-ecae5d58f73d · inbound
GAMR: Geometric-Aware Manifold Regularization with Virtual Outlier Synthesis for Learning with Noisy Labels cites this paper.
GAMR: Geometric-Aware Manifold Regularization with Virtual Outlier Synthesis for Learning with Noisy Labels Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T05:19:39.231810Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c44cc749-690e-4823-acb8-5a94b8a38183 · inbound
Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching cites this paper.
Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T09:07:47.653973Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.