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Paper Citation Record · LEDGER

Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2108.12627.

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

pith.paper-citation-record.v1
2108.12627 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:14:57.798603Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:47:37.817638Z

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 a0540dae-24e9-4cbf-b0ab-b544057c177d · inbound

Pretraining Large Brain Language Model for Active BCI: Silent Speech cites this paper.

Pretraining Large Brain Language Model for Active BCI: Silent Speech Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-16T05:14:57.798603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:14:57.798603Z digest=sha256:eec5192dd0dbd291551755e760c3dd0797f15e53171907709bbb9b2451fbd5c6

Observation c7a498c0-c91f-4212-9aa2-7b26b2c942b6 · inbound

FinCast: A Foundation Model for Financial Time-Series Forecasting cites this paper.

FinCast: A Foundation Model for Financial Time-Series Forecasting Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T15:45:36.283113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:45:36.283113Z digest=sha256:85ce234d08e2cb6d3e97355cd840928ce9838c1a9735cbfa171a97777e627861

Observation 3e349b90-ec71-4b34-afa5-b126ad1d8e9f · inbound

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting cites this paper.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-03T11:45:28.698038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:45:28.698038Z digest=sha256:7273f8831dc1b87e854aba670f75deca09372c0ddcc7a64043d1bfbc045c3127

Observation 68819242-a2f8-45df-b229-a134505cba0f · inbound

ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps cites this paper.

ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics

Reference 99

Resolution
verified exact
arxiv_id, observed 2026-05-22T02:20:56.229143Z

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.

source=arxiv_source observed=2026-05-22T02:16:37.897274Z digest=sha256:af2847ca8627eb3fa9b4e425d629c98eadffb5b03a3a8f40d4a9db062532ff99

Observation e0eed349-c167-4a4b-a8bd-3baad6192022 · inbound

One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data cites this paper.

One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-03T04:47:37.818930Z

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.

source=pdf_text observed=2026-06-27T13:41:52.295889Z digest=sha256:8aa0d61a0abb6fe0dd1c911b997bf184860dd16d8511d3a89d6e9bbc3967a328