Pith. sign in

Paper Citation Record · LEDGER

Weak Human Preference Supervision For Deep Reinforcement Learning

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2007.12904.

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

pith.paper-citation-record.v1
2007.12904 v2

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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-25T23:35:03.577967Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:40:00.112551Z

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 cb4e0346-dc79-40dd-9c63-4d0d24c39a9d · inbound

Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach cites this paper.

Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach Weak Human Preference Supervision For Deep Reinforcement Learning

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-23T18:33:19.643187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-23T18:30:38.818711Z digest=sha256:24db2f69fbcccf7f14a2a12e4208dcb14543bd9de0eac926873f839cf74d6fc2

Observation efd56d09-8f33-48f8-8e89-583583adf205 · inbound

Themis: An explainable AI-enabled framework for Reinforcement Learning with Human Feedback cites this paper.

Themis: An explainable AI-enabled framework for Reinforcement Learning with Human Feedback Weak Human Preference Supervision For Deep Reinforcement Learning

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-04T17:40:00.113955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-25T23:35:03.577967Z digest=sha256:2e1c58713b92312e2d2fd7d32fac7b465d82b245b9c4abbdc46df8d2c79d5026