Paper Citation Record · LEDGER

QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2407.15840.

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

pith.paper-citation-record.v1
2407.15840 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:44:26.254048Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T07:29:48.331582Z

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 97457d2d-7ad9-4b5b-a2f5-8c9d3975b673 · inbound

RoCoDA: Counterfactual Data Augmentation for Data-Efficient Robot Learning from Demonstrations cites this paper.

RoCoDA: Counterfactual Data Augmentation for Data-Efficient Robot Learning from Demonstrations QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T12:44:26.254048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d279eb44-77cc-4f50-be13-d1e106aaa76d · inbound

Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning cites this paper.

Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T13:38:41.671562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca6e0a4b-3e52-4a6f-aca0-5036622043c5 · inbound

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

FAST: Efficient Action Tokenization for Vision-Language-Action Models QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:52:32.044659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 55ced259-3f82-48e1-851a-8b98b333eb64 · inbound

Universal Actions for Enhanced Embodied Foundation Models cites this paper.

Universal Actions for Enhanced Embodied Foundation Models QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T19:29:39.816401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7356026b-cc33-4804-bdf7-e6f8bff70ad2 · inbound

Real-Time Execution of Action Chunking Flow Policies cites this paper.

Real-Time Execution of Action Chunking Flow Policies QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:18:51.797251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7b34fcd4-a7b9-4d1c-b766-6f083ef5fd42 · inbound

AMPLIFY: Actionless Motion Priors for Robot Learning from Videos cites this paper.

AMPLIFY: Actionless Motion Priors for Robot Learning from Videos QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:28.338494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 850e861c-fddc-4d2e-8fa3-7ba9680688be · inbound

DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge cites this paper.

DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 134

Resolution: verified exact; arxiv_id, observed 2026-05-16T15:42:41.636545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b2aa3951-a4e0-4330-91d2-252a445b1731 · inbound

UniT: Toward a Unified Physical Language for Human-to-Humanoid Policy Learning and World Modeling cites this paper.

UniT: Toward a Unified Physical Language for Human-to-Humanoid Policy Learning and World Modeling QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:16:06.362356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation df0dcd14-d87d-41e4-9885-fb7bdc2d57fd · inbound

COBALT: Crowdsourcing Robot Learning via Cloud-Based Teleoperation with Smartphones cites this paper.

COBALT: Crowdsourcing Robot Learning via Cloud-Based Teleoperation with Smartphones QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-20T08:58:10.322712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3df6b344-9e0c-410b-973a-70859e67745d · inbound

COBALT: Crowdsourcing Robot Learning via Cloud-Based Teleoperation with Smartphones cites this paper.

COBALT: Crowdsourcing Robot Learning via Cloud-Based Teleoperation with Smartphones QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:29:48.334190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.