Paper Citation Record · LEDGER

A data-driven approach for learning to control computers

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2202.08137.

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

pith.paper-citation-record.v1
2202.08137 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:49:09.040202Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T06:38:36.723394Z

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 729b5b0e-04aa-4987-985b-7db1624e4749 · inbound

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances cites this paper.

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances A data-driven approach for learning to control computers

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:24:06.165391Z

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 42fb3717-b7df-4c49-ab1d-bd1c54aa3b32 · inbound

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models cites this paper.

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models A data-driven approach for learning to control computers

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:38:36.726325Z

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 0b0bc8bb-8f61-49ac-9690-25ecb4844780 · inbound

Cracking the Code of Action: a Generative Approach to Affordances for Reinforcement Learning cites this paper.

Cracking the Code of Action: a Generative Approach to Affordances for Reinforcement Learning A data-driven approach for learning to control computers

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T10:49:09.040202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76a3f48c-2a84-444e-944e-a844c3e606b5 · inbound

GUI Agents with Reinforcement Learning: Toward Digital Inhabitants cites this paper.

GUI Agents with Reinforcement Learning: Toward Digital Inhabitants A data-driven approach for learning to control computers

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:31:29.781054Z

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.