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Paper Citation Record · LEDGER

Hybrid Preferences: Learning to Route Instances for Human vs. AI Feedback

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.19133.

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

pith.paper-citation-record.v1
2410.19133 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:05:24.348981Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T18:55:58.590568Z

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 ef52ddb6-517b-4feb-a90b-cbed374f81de · inbound

Standardizing Intelligence: Aligning Generative AI for Regulatory and Operational Compliance cites this paper.

Standardizing Intelligence: Aligning Generative AI for Regulatory and Operational Compliance Hybrid Preferences: Learning to Route Instances for Human vs. AI Feedback

Reference 67

Resolution
malformed identifier
no resolver link, observed 2026-08-09T15:05:24.348981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:05:24.348981Z digest=sha256:fda244827a1f1a93233cc82aaf5ba2e4d1e7d18f7f8b55baea89c70e093d3ad7

Observation 2a7ff6ea-0c4b-45ae-8ef1-bcd6b10d81e1 · inbound

PEBS: Per-rater Empirical-Bayes Shrinkage for RLHF Reward-Model Calibration cites this paper.

PEBS: Per-rater Empirical-Bayes Shrinkage for RLHF Reward-Model Calibration Hybrid Preferences: Learning to Route Instances for Human vs. AI Feedback

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-01T18:55:58.591972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T01:26:00.228782Z digest=sha256:86de1d9b8d8392682ea22cc3db1ca290b89d987d4f6c5998c7a9eb61220f2a7d