Paper Citation Record · LEDGER

Active Preference-Based Gaussian Process Regression for Reward Learning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2005.02575.

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

pith.paper-citation-record.v1
2005.02575 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:52:23.819700Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:17:43.402574Z

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 7986c8ac-db51-4892-bf14-1509a6a4b928 · inbound

Learning Implicit Social Navigation Behavior using Deep Inverse Reinforcement Learning cites this paper.

Learning Implicit Social Navigation Behavior using Deep Inverse Reinforcement Learning Active Preference-Based Gaussian Process Regression for Reward Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T20:55:50.075137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3369010c-f1da-4ca0-a102-b717adf3fbd0 · inbound

TREND: Tri-teaching for Robust Preference-based Reinforcement Learning with Demonstrations cites this paper.

TREND: Tri-teaching for Robust Preference-based Reinforcement Learning with Demonstrations Active Preference-Based Gaussian Process Regression for Reward Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T22:52:23.819700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34b88cb9-7994-4e46-8ce1-dfc1bd02b6fb · inbound

Residual Reward Models for Preference-based Reinforcement Learning cites this paper.

Residual Reward Models for Preference-based Reinforcement Learning Active Preference-Based Gaussian Process Regression for Reward Learning

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:17:43.559189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f0f231be-1acc-4612-8e83-f3a3a9ba6fef · inbound

Generalizing Preference-based Reinforcement Learning: a Rationality Model for Incomparability cites this paper.

Generalizing Preference-based Reinforcement Learning: a Rationality Model for Incomparability Active Preference-Based Gaussian Process Regression for Reward Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-14T05:38:58.035337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.