Paper Citation Record · LEDGER

Extreme Q-Learning: MaxEnt RL without Entropy

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2301.02328.

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

pith.paper-citation-record.v1
2301.02328 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:38:30.228255Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:17:36.943655Z

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 575ff729-ed03-4652-b4e6-6f605c574e73 · inbound

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

IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies Extreme Q-Learning: MaxEnt RL without Entropy

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-13T13:48:36.476653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8b590690-0025-41e2-9905-07b1a5960926 · inbound

TD-M(PC)$^2$: Improving Temporal Difference MPC Through Policy Constraint cites this paper.

TD-M(PC)$^2$: Improving Temporal Difference MPC Through Policy Constraint Extreme Q-Learning: MaxEnt RL without Entropy

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T04:38:30.228255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 202fe6ac-af03-4756-8236-36e4ef3b38c3 · inbound

Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL cites this paper.

Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL Extreme Q-Learning: MaxEnt RL without Entropy

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T14:14:45.632354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14dd046c-95d9-4c78-9362-9a3b7e400315 · inbound

Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood cites this paper.

Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood Extreme Q-Learning: MaxEnt RL without Entropy

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T05:22:24.560434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b556c63-0a75-4c9d-a391-14da58e48501 · inbound

DoublyAware: Dual Planning and Policy Awareness for Temporal Difference Learning in Humanoid Locomotion cites this paper.

DoublyAware: Dual Planning and Policy Awareness for Temporal Difference Learning in Humanoid Locomotion Extreme Q-Learning: MaxEnt RL without Entropy

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T04:27:30.548506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09ecb643-05b9-49bf-94ae-8708d9a5997a · inbound

Fisher Decorator: Refining Flow Policy via a Local Transport Map cites this paper.

Fisher Decorator: Refining Flow Policy via a Local Transport Map Extreme Q-Learning: MaxEnt RL without Entropy

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:51:46.587307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d11e5360-8f6a-457d-9fe9-64a546f422c7 · inbound

Towards Efficient and Expressive Offline RL via Flow-Anchored Noise-conditioned Q-Learning cites this paper.

Towards Efficient and Expressive Offline RL via Flow-Anchored Noise-conditioned Q-Learning Extreme Q-Learning: MaxEnt RL without Entropy

Reference 48

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T08:56:00.657389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bf7a61dd-b81f-4142-a925-aa35fc35e55f · inbound

Beyond Autoregressive RTG: Conditioning via Injection Outside Sequential Modeling in Decision Transformer cites this paper.

Beyond Autoregressive RTG: Conditioning via Injection Outside Sequential Modeling in Decision Transformer Extreme Q-Learning: MaxEnt RL without Entropy

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:46:10.148459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3d758c3f-83aa-4a98-86e0-7347ec0464ca · inbound

Peng's Q($\lambda$) for Conservative Value Estimation in Offline Reinforcement Learning cites this paper.

Peng's Q($\lambda$) for Conservative Value Estimation in Offline Reinforcement Learning Extreme Q-Learning: MaxEnt RL without Entropy

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:45.853436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0729d11e-2144-4596-9322-bf9bc9c14bbb · inbound

Spectral Souping: A Unified Framework for Online Preference Alignment cites this paper.

Spectral Souping: A Unified Framework for Online Preference Alignment Extreme Q-Learning: MaxEnt RL without Entropy

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:59:50.924661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e8b078c2-2a53-450e-8180-6e537c3574f3 · inbound

Test-Time Gradient Guidance of Flow Policies in Reinforcement Learning cites this paper.

Test-Time Gradient Guidance of Flow Policies in Reinforcement Learning Extreme Q-Learning: MaxEnt RL without Entropy

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:17:36.945140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b8ac3f31-467e-42f2-b8c9-b082063529b4 · inbound

Reinforcement Learning: From Algorithms To Foundation Models cites this paper.

Reinforcement Learning: From Algorithms To Foundation Models Extreme Q-Learning: MaxEnt RL without Entropy

Reference 269

Resolution: unresolved; no resolver link, observed 2026-08-01T17:45:22.550304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.