Paper Citation Record · LEDGER

Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:1909.10618.

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

pith.paper-citation-record.v1
1909.10618 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:40:40.458635Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T18:33:19.672856Z

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 15027a86-8c42-4b44-879b-ea7aa56c3382 · inbound

A survey on intrinsic motivation in reinforcement learning cites this paper.

A survey on intrinsic motivation in reinforcement learning Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 122

Resolution: unresolved; no resolver link, observed 2026-08-14T12:33:26.217760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91f1ad85-01ad-4bfd-9515-72db994af8e0 · 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 Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-23T18:33:19.676006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4ad8a221-3ca4-48e7-b3b2-714542e6d7cf · inbound

Dynamic Legged Ball Manipulation on Rugged Terrains with Hierarchical Reinforcement Learning cites this paper.

Dynamic Legged Ball Manipulation on Rugged Terrains with Hierarchical Reinforcement Learning Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:40.458635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcddf38a-dbb8-477b-94fe-3c4062320186 · inbound

Hierarchical Reinforcement Learning in Multi-Goal Spatial Navigation with Autonomous Mobile Robots cites this paper.

Hierarchical Reinforcement Learning in Multi-Goal Spatial Navigation with Autonomous Mobile Robots Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:06.296472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a623326b-4058-4547-bc56-e0a87da4767f · inbound

Efficient Robotic Policy Learning via Latent Space Backward Planning cites this paper.

Efficient Robotic Policy Learning via Latent Space Backward Planning Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T22:36:05.463546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17db5c88-0c10-401c-a9a9-cdc1125de1a9 · inbound

Strict Subgoal Execution: Reliable Long-Horizon Planning in Hierarchical Reinforcement Learning cites this paper.

Strict Subgoal Execution: Reliable Long-Horizon Planning in Hierarchical Reinforcement Learning Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-22T00:54:31.216147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 885896cd-dfc5-465f-8fc6-464fde77d96f · inbound

Unsupervised Hierarchical Skill Discovery cites this paper.

Unsupervised Hierarchical Skill Discovery Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-03T06:26:50.472689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee3c3102-4c4a-4b30-ba41-4e8909a376b1 · inbound

Learning to Theorize the World from Observation cites this paper.

Learning to Theorize the World from Observation Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 197

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T23:21:30.269890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0b525fab-8dca-4884-9b5c-020ec92a322d · inbound

Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits cites this paper.

Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-12T11:01:30.382581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3584eb84-14fb-4507-b12c-f1b1d92f5acb · inbound

Implicit Safety Alignment from Crowd Preferences cites this paper.

Implicit Safety Alignment from Crowd Preferences Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T08:31:16.861243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6999f00b-6592-46a9-b71b-41aec32e366f · inbound

LEMUR: Learning to Align with Multi-Objective Reinforcement Learning from Preference Feedback cites this paper.

LEMUR: Learning to Align with Multi-Objective Reinforcement Learning from Preference Feedback Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Reference 238

Resolution: unresolved; no resolver link, observed 2026-08-03T04:39:32.103294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.