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Paper Citation Record · LEDGER

Bridging the Human to Robot Dexterity Gap through Object-Oriented Rewards

As of 31 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.23289.

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

pith.paper-citation-record.v1
2410.23289 v1

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 2026-07-31T06:34:12.847434+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T00:23:04.763773Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T08:52:31.973364Z

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 d374ff46-e885-4174-8c12-8a6ca347d6e5 · inbound

FAST: Efficient Action Tokenization for Vision-Language-Action Models cites this paper.

FAST: Efficient Action Tokenization for Vision-Language-Action Models Bridging the Human to Robot Dexterity Gap through Object-Oriented Rewards

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:52:31.976627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-11T08:52:31.686474Z digest=sha256:98c03322481cf032b34b5b93d201fae543c8b305860221b45962b66aa3f36eb8

Observation 5ee111fe-b853-4545-9e2b-8728a67a17c8 · inbound

OmniTacTune: Policy-Agnostic Real-World RL for Tactile Residual Adaptation of Visual Policies cites this paper.

OmniTacTune: Policy-Agnostic Real-World RL for Tactile Residual Adaptation of Visual Policies Bridging the Human to Robot Dexterity Gap through Object-Oriented Rewards

Reference 61

Resolution
unresolved
no resolver link, observed 2026-07-12T00:23:04.763773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T00:23:04.763773Z digest=sha256:31fad71a4c30b6e12a96a22966ed94fbb44985193717c5565228dd6adc285330