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Paper Citation Record · LEDGER

Advantages and Limitations of using Successor Features for Transfer in Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1708.00102.

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

pith.paper-citation-record.v1
1708.00102 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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:49:59.757366Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T12:01:13.166991Z

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 9072b30e-c353-4a7c-ad3e-a3e318973037 · inbound

Successor Features for Transfer in Alternating Markov Games cites this paper.

Successor Features for Transfer in Alternating Markov Games Advantages and Limitations of using Successor Features for Transfer in Reinforcement Learning

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:01:13.174637Z

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.

source=arxiv_source observed=2026-08-06T12:01:13.115590Z digest=sha256:269579fcad20c3c09a4fb2d89631c983130e55d63af49db6cdbf9186d67faf8f

Observation 741d5ac3-a158-4028-83ef-8c6e7ea260c1 · inbound

Adaptive Policy Backbone via Shared Network cites this paper.

Adaptive Policy Backbone via Shared Network Advantages and Limitations of using Successor Features for Transfer in Reinforcement Learning

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T15:49:59.757366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:49:59.757366Z digest=sha256:8f4eeaf0ad972342724e7d1eb5a6c8f01a83138ce842f0f74c949a6562da73c5