Pith. sign in

Paper Citation Record · LEDGER

Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment

As of 9 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 0 inbound Pith citation observations for arXiv:2605.27659.

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

pith.paper-citation-record.v1
2605.27659 v1

Coverage vector

measured 3 of 3 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T18:02:31.000447Z

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

3 of 3 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved1
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 018e76cc-686f-49b9-b23e-a29735985d5b · outbound

This paper cites Stooke, A., Achiam, J., and Abbeel, P.

Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment Stooke, A., Achiam, J., and Abbeel, P

Reference 1

Resolution
unresolved
no resolver link, observed 2026-06-29T18:02:31.000447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-29T18:02:31.000447Z digest=sha256:ddef40f207c1359113e495ab3cd92e5d61f92ad444c938f1e86d530f93395c2e

Observation 633b528b-47a3-434b-9bb6-8af44e840e21 · outbound

This paper cites A Survey of Constraint Formulations in Safe Reinforcement Learning.

Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment A Survey of Constraint Formulations in Safe Reinforcement Learning

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T18:03:47.877433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T18:02:31.000447Z digest=sha256:7d61734b776ced1252846e3483e7fc63c30acd6bf6125ca616c7c4befe650511

Observation 35a38c0a-f87b-4a53-be89-b1b3993d2930 · outbound

This paper cites w/o latent encoder.

Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment w/o latent encoder

Reference 3

Resolution
malformed identifier
no resolver link, observed 2026-06-29T18:02:31.000447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-29T18:02:31.000447Z digest=sha256:9b626b0151ed1a4bf26fd007870f1bfaee31ddbe8fb7f65c3ba8fb4721fbe4b8

Pith citing papers

No inbound Pith citation observations are available.