Paper Citation Record · LEDGER

Improving Generalization in Meta Reinforcement Learning using Learned Objectives

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1910.04098.

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

pith.paper-citation-record.v1
1910.04098 v2

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 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:30:09.784023Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:39:36.932074Z

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 3b9ccf9b-f5c1-46f3-a123-94040a43390a · inbound

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery cites this paper.

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery Improving Generalization in Meta Reinforcement Learning using Learned Objectives

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:42:31.939786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 66b3e5a2-d896-4260-98de-f11cd29549b4 · inbound

Evolution and The Knightian Blindspot of Machine Learning cites this paper.

Evolution and The Knightian Blindspot of Machine Learning Improving Generalization in Meta Reinforcement Learning using Learned Objectives

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-10T16:30:09.784023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03ac8a00-206f-4612-8cc8-1788385badca · inbound

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution cites this paper.

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution Improving Generalization in Meta Reinforcement Learning using Learned Objectives

Reference 94

Resolution: verified exact; arxiv_id, observed 2026-05-16T13:58:58.832431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 433f340a-b352-4355-b2ed-0b4ccfb49494 · inbound

An Information-Theoretic Analysis of OOD Generalization in Meta-Reinforcement Learning cites this paper.

An Information-Theoretic Analysis of OOD Generalization in Meta-Reinforcement Learning Improving Generalization in Meta Reinforcement Learning using Learned Objectives

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T03:52:22.055863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b7b0897c-59d5-45fc-a415-8e087228e913 · inbound

Sakana Fugu Technical Report cites this paper.

Sakana Fugu Technical Report Improving Generalization in Meta Reinforcement Learning using Learned Objectives

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:39:36.933562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.