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Paper Citation Record · LEDGER

DARLA: Improving Zero-Shot Transfer in Reinforcement Learning

As of 22 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1707.08475.

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

pith.paper-citation-record.v1
1707.08475 v2

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 2026-07-21T06:31:05.380196+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-24T06:18:51.073571Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-24T06:18:59.659746Z

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 04038a5a-d2ee-48d2-999c-9d23b4d243c5 · inbound

Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy cites this paper.

Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy DARLA: Improving Zero-Shot Transfer in Reinforcement Learning

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-05-24T06:18:59.663247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

source=pdf_text observed=2026-05-24T06:18:51.073571Z digest=sha256:dd4e844e4a81822660c099fb7ec4bd9392ccc9599797a93f11a5c2ae4927c2fa

Observation 310b6b3c-5307-415f-910a-cb36c3c380a9 · inbound

State-Conditional Adversarial Learning: An Off-Policy Visual Domain Transfer Method for End-to-End Imitation Learning cites this paper.

State-Conditional Adversarial Learning: An Off-Policy Visual Domain Transfer Method for End-to-End Imitation Learning DARLA: Improving Zero-Shot Transfer in Reinforcement Learning

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-05-21T18:24:18.192100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

source=pdf_text observed=2026-05-21T18:22:02.372554Z digest=sha256:edd012fc272fcc04d911f9b9028165907b96028f3c73fa9468cdc03577ad880d