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Paper Citation Record · LEDGER

Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.03655.

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

pith.paper-citation-record.v1
2110.03655 v3

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:30:08.821159Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T18:33:19.656604Z

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 14296821-3e0f-4b7e-95aa-f25b2fb2a2c4 · 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 Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-23T18:33:19.659829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-23T18:30:38.818711Z digest=sha256:c8adcee7664a44c4ed88c5a7916f7e53d85abbb0b9ef12c1663c474d85793d8d

Observation 25b28b81-9e1c-4f35-8b04-746d71789b3c · inbound

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills cites this paper.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-09T14:30:08.821159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.821159Z digest=sha256:9e26c1fa4f7766c0caddc25315c4e6a47086316e13788ca3c7133f44dfb5474d