Paper Citation Record · LEDGER

Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1907.12894.

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

pith.paper-citation-record.v1
1907.12894 v1

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 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:03:25.809592Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T01:46:18.556913Z

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 b9edcfba-e7ac-45d7-9864-73a70b203a45 · inbound

Learning to summarize from human feedback cites this paper.

Learning to summarize from human feedback Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-18T01:46:18.560471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 28d9f7d8-2d84-4c68-8936-eca7a58334a1 · inbound

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback cites this paper.

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-15T21:32:27.926085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 945bfaa9-cd47-4ce1-be80-991b4affb169 · inbound

Training Language Models to Self-Correct via Reinforcement Learning cites this paper.

Training Language Models to Self-Correct via Reinforcement Learning Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:04:10.554225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dc605c3a-310f-4ff3-9b8f-329b499d21c4 · inbound

e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs cites this paper.

e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:03:25.809592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.