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Paper Citation Record · LEDGER

The Sample Complexity of Policy Learning with Mu-Resets

As of 12 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 0 inbound Pith citation observations for arXiv:2608.07772.

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

pith.paper-citation-record.v1
2608.07772 v1

Coverage vector

measured 8 of 8 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:30:41.398232Z

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

8 of 8 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 39c382ac-20ad-4642-bb75-9a03f586cc32 · outbound

This paper cites an unresolved cited work.

The Sample Complexity of Policy Learning with Mu-Resets Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:30:41.602052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:30:41.348988Z digest=sha256:3cf12ba5ac872967e789f8cfc06c74c4b3bd63d8a65144f2990d83fdd1dcaf7d

Observation 3b247f1c-b591-4f8c-9fc5-6e1366df20e3 · outbound

This paper cites Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation.

The Sample Complexity of Policy Learning with Mu-Resets Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T00:30:41.356846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:30:41.356846Z digest=sha256:977c63c7acf993d467755825002e4263db14d07703d9219adb0db30b2c8e2a27

Observation 7d675ea8-45da-4779-b369-d2001e987117 · outbound

This paper cites an unresolved cited work.

The Sample Complexity of Policy Learning with Mu-Resets Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:30:41.578105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:30:41.365670Z digest=sha256:f8c6cb591b445095879b11407e60ec5b631fbbee092f14a7b141c23557e6f59f

Observation f870b210-e705-4f7a-b82e-b7d4e35e1d4e · outbound

This paper cites an unresolved cited work.

The Sample Complexity of Policy Learning with Mu-Resets Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:30:41.558858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:30:41.371949Z digest=sha256:b179b484ee15ead2f520df033910e8b7860c5160c9d3a9f862ba6873ce21b2fd

Observation 91420416-779b-46aa-9a4d-9dbcb282ecef · outbound

This paper cites an unresolved cited work.

The Sample Complexity of Policy Learning with Mu-Resets Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:30:41.535639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:30:41.378740Z digest=sha256:5d9e9b381c1e748dc7fba7edb9cd5fd25183b75c742caed8ec55ebed5ee49405

Observation b5bcdfdd-b616-45de-ab90-3c1e8ec7760b · outbound

This paper cites The Role of Environment Access in Agnostic Reinforcement Learning.

The Sample Complexity of Policy Learning with Mu-Resets The Role of Environment Access in Agnostic Reinforcement Learning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T00:30:41.384552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:30:41.384552Z digest=sha256:d3218a03f90f9a20aa6eeae91dd8308fd461f0a4866cb972792c089428112002

Observation 81858158-a262-47c7-9719-b0d8e3a201f2 · outbound

This paper cites Sekhari, C.

The Sample Complexity of Policy Learning with Mu-Resets Sekhari, C

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:30:41.515936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:30:41.391725Z digest=sha256:92dcdc0a8cfd8c70d20533fd8024b6755b755e26ef2c53db4c829884fe52872a

Observation adc54765-09e6-4982-91cd-563b716185c1 · outbound

This paper cites Xie and N.

The Sample Complexity of Policy Learning with Mu-Resets Xie and N

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:30:41.495668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:30:41.398232Z digest=sha256:7e388ef93bc4f8d593c042a95bd56fb3caede248fa16c2a7dc1d5b9386c31075

Pith citing papers

No inbound Pith citation observations are available.