Paper Citation Record · LEDGER

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning

As of 21 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 1 inbound Pith citation observation for arXiv:2506.14058.

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

pith.paper-citation-record.v1
2506.14058 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:05:34.935087Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T20:52:08.062450Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T20:54:21.647943Z

Reference resolution

16 of 16 outbound references displayed

verified exact1
verified fuzzy10
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2deaca87-2bff-41fd-8f7e-860ed42a450d · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:34.859075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93bc56a0-3331-482d-9605-ce882d4f0f45 · outbound

This paper cites A survey on offline reinforcement learning: Taxonomy, re- view, and open problems,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning A survey on offline reinforcement learning: Taxonomy, re- view, and open problems,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.305797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 604314b4-3e27-4d90-8ca3-6f19d7d0d8a0 · outbound

This paper cites Beyond uniform sampling: Offline rein- forcement learning with imbalanced datasets,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Beyond uniform sampling: Offline rein- forcement learning with imbalanced datasets,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.292915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 236357e8-6ef3-4a9a-977a-73bbac6958dd · outbound

This paper cites The Importance of Pessimism in Fixed-Dataset Policy Optimization.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning The Importance of Pessimism in Fixed-Dataset Policy Optimization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:34.883014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8e25237-783c-40f6-ba56-904d2be06f7b · outbound

This paper cites A minimalist approach to offline reinforcement learning,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning A minimalist approach to offline reinforcement learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.280383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e73a3f8a-57a8-4dd5-9eab-d581031347f3 · outbound

This paper cites Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:34.892886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b35471d9-ad49-46ca-9c13-3370f8286c4e · outbound

This paper cites Spectral normalization for lipschitz-constrained poli- cies on learning humanoid locomotion,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Spectral normalization for lipschitz-constrained poli- cies on learning humanoid locomotion,

Reference 7

Resolution: verified exact; raw_fallback, observed 2026-08-15T20:05:35.119772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eec35a7d-9d51-4cb5-bf0b-4ba930e96ecd · outbound

This paper cites Off-policy deep reinforcement learning without exploration,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Off-policy deep reinforcement learning without exploration,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.265944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c7862269-d9a3-4488-95fd-24c8c5f651ca · outbound

This paper cites Conser- vative q-learning for offline reinforcement learning,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Conser- vative q-learning for offline reinforcement learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.252104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f5c72a33-f7f0-4801-b359-a790c5ca075e · outbound

This paper cites Uncertainty-based offline reinforcement learning with diversified Q-ensemble,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Uncertainty-based offline reinforcement learning with diversified Q-ensemble,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.235358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 204d28c3-6802-4fa4-b287-10233ce27d3a · outbound

This paper cites IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:34.915030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5be6ea27-521a-474d-bce6-e720a79165cd · outbound

This paper cites L2c2: Locally lipschitz continuous con- straint towards stable and smooth reinforcement learn- ing,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning L2c2: Locally lipschitz continuous con- straint towards stable and smooth reinforcement learn- ing,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.220917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 965f766b-652e-41a8-aa8a-b01fac3cd49c · outbound

This paper cites Monotonic value function factorisation for deep multi-agent reinforcement learn- ing,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Monotonic value function factorisation for deep multi-agent reinforcement learn- ing,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.207639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9028cea8-d25d-45e6-aefa-462185e76c73 · outbound

This paper cites Optnet: Differentiable opti- mization as a layer in neural networks,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Optnet: Differentiable opti- mization as a layer in neural networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.193515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c596da04-9ee7-4e72-9769-113a3ebad4c7 · outbound

This paper cites A theory of regularized Markov decision processes,.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning A theory of regularized Markov decision processes,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:05:35.179110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 29ba232e-c4c5-4f17-979a-8bad596bdc84 · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning Offline Reinforcement Learning with Implicit Q-Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:34.935087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation afe72333-69ab-4fb1-9db2-b6f349c12b10 · inbound

Density-Ratio Weighted Behavioral Cloning: Learning Control Policies from Corrupted Datasets cites this paper.

Density-Ratio Weighted Behavioral Cloning: Learning Control Policies from Corrupted Datasets Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:54:21.650231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.