Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL | Paper Citation Record

Observation 3be00b87-80c9-4e0d-83fb-77693bf1b357 · outbound

This paper cites Constrained policy optimization.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Constrained policy optimization

Reference 1

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Observation b8e8779d-b6d3-40c8-8977-23a777fb2748 · outbound

This paper cites Reinforcement learning: Theory and algorithms.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Reinforcement learning: Theory and algorithms

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:50.087909Z

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Observation c1eb6107-27ea-47da-b206-13c9cf8efe86 · outbound

This paper cites Reincarnating reinforcement learning: Reusing prior computation to accelerate progress.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Reincarnating reinforcement learning: Reusing prior computation to accelerate progress

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:50.071758Z

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Observation aeba181c-5585-4ce2-88a1-953ce5a8e638 · outbound

This paper cites Efficient Online Reinforcement Learning with Offline Data.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Efficient Online Reinforcement Learning with Offline Data

Reference 4

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Observation f57d225d-8fdb-48d5-9a7b-b1e140eff677 · outbound

This paper cites Improving TD3-BC: Relaxed Policy Constraint for Offline Learning and Stable Online Fine-Tuning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Improving TD3-BC: Relaxed Policy Constraint for Offline Learning and Stable Online Fine-Tuning

Reference 5

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Observation 931c0e32-c4c3-48b9-a8da-f1bc7699846c · outbound

This paper cites Decision transformer: Reinforcement learning via sequence modeling.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Decision transformer: Reinforcement learning via sequence modeling

Reference 6

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Observation 8d97be98-45b7-48a3-8e26-6d41cd6f76c7 · outbound

This paper cites Safe Exploration in Continuous Action Spaces.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Safe Exploration in Continuous Action Spaces

Reference 7

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Observation 16a0bb77-79d9-41f5-bf6e-e2a850b4f462 · outbound

This paper cites Uncertainty-aware model-based offline reinforcement learning for automated driving.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Uncertainty-aware model-based offline reinforcement learning for automated driving

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:50.047352Z

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Observation 1be9be94-cf64-49a2-a916-7783e452b959 · outbound

This paper cites D4RL: Datasets for Deep Data-Driven Reinforcement Learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 9

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Observation 3b822ef4-6f86-4a48-95c5-9a5f7ddfd70f · outbound

This paper cites A minimalist approach to offline reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL A minimalist approach to offline reinforcement learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:48.978973Z

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Observation 26167c32-88bf-4702-b62e-2c88e1012874 · outbound

This paper cites Addressing function approximation error in actor-critic methods.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Addressing function approximation error in actor-critic methods

Reference 11

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Observation 3e884ace-2ae7-4635-b915-da21ba897fbc · outbound

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

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Off-policy deep reinforcement learning without exploration

Reference 12

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Observation 94ccdcad-0bf9-47a6-ab8c-1e72494dfeba · outbound

This paper cites Extreme Q-Learning: MaxEnt RL without Entropy.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Extreme Q-Learning: MaxEnt RL without Entropy

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:48.991946Z

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Observation 1078a651-dda5-442a-99a1-292e83de04f2 · outbound

This paper cites Open and real-world human-ai coordination by heterogeneous training with communication.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Open and real-world human-ai coordination by heterogeneous training with communication

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:50.001318Z

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Observation 791cd18e-9715-4197-8547-41090e436c30 · outbound

This paper cites A simple unified uncertainty-guided framework for offline-to-online reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL A simple unified uncertainty-guided framework for offline-to-online reinforcement learning

Reference 15

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Observation a2a59874-9d4a-42a2-8e17-a87128268627 · outbound

This paper cites Reinforcement learning with deep energy-based policies.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Reinforcement learning with deep energy-based policies

Reference 16

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Observation 680d33f4-22a6-4f31-8ff5-940f5489d238 · outbound

This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.010070Z

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Observation f919f741-e582-43b1-9b2d-b1242342896c · outbound

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

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies

Reference 18

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Observation 516b2635-e169-418f-987d-e79741e2376e · outbound

This paper cites Uncertainty-driven pessimistic q-ensemble for offline-to- online reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Uncertainty-driven pessimistic q-ensemble for offline-to- online reinforcement learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.969216Z

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Observation 64af4ca2-64c0-40f6-9c16-df69ed7322cc · outbound

This paper cites Offline reinforcement learning with implicit q-learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Offline reinforcement learning with implicit q-learning

Reference 20

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Observation 6746a8bb-fd32-4958-a3e1-2deb673aa3ab · outbound

This paper cites Conservative q-learning for offline reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Conservative q-learning for offline reinforcement learning

Reference 21

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Observation 17fb3d7f-9744-436b-8fe3-685d92aaf3ba · outbound

This paper cites Batch policy learning under constraints.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Batch policy learning under constraints

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.935505Z

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Observation c00cb2d8-d4c6-46e5-b035-6c9dc9e02144 · outbound

This paper cites Offline-to-online reinforcement learning via balanced replay and pessimistic q-ensemble.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Offline-to-online reinforcement learning via balanced replay and pessimistic q-ensemble

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.919106Z

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Observation 391ffc41-f4b9-468d-a5cc-564f956456eb · outbound

This paper cites Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization

Reference 24

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Observation 7b857664-28ff-4841-a166-1eed0a315c88 · outbound

This paper cites PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.044417Z

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Observation 82fd9920-06d9-4eac-9227-6fc5976b813a · outbound

This paper cites Finetuning from Offline Reinforcement Learning: Challenges, Trade-offs and Practical Solutions.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Finetuning from Offline Reinforcement Learning: Challenges, Trade-offs and Practical Solutions

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.048977Z

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Observation 53a18ba4-5f14-4d3c-8f35-9dd8a1d5391c · outbound

This paper cites Mildly conservative q-learning for offline reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Mildly conservative q-learning for offline reinforcement learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.903853Z

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Observation 9dfaeb79-4d21-4164-9f6e-3c6368a1aa84 · outbound

This paper cites MOORe: Model-based Offline-to-Online Reinforcement Learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL MOORe: Model-based Offline-to-Online Reinforcement Learning

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-11T04:30:49.411742Z

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Observation fbd3e492-d978-437d-938e-9749de752dea · outbound

This paper cites Supported trust region optimization for offline reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Supported trust region optimization for offline reinforcement learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.887854Z

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Observation 1281f0c8-a005-4ff5-b632-a1173f4816a4 · outbound

This paper cites Fine-tuning offline policies with optimistic action selection.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Fine-tuning offline policies with optimistic action selection

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.872845Z

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Observation 5d037d44-40f3-4ef0-96c3-9441caeb1c8b · outbound

This paper cites Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-11T04:30:49.391005Z

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Observation 87cd898a-545a-4798-8d34-cfe6b3d63c7c · outbound

This paper cites AWAC: Accelerating Online Reinforcement Learning with Offline Datasets.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.075601Z

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Observation 2e2f4430-3cb6-4f79-ba2e-f0e4e1694785 · outbound

This paper cites Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.080017Z

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Observation 77df57cc-3353-487f-a5cf-429697734043 · outbound

This paper cites Bridging offline reinforcement learning and imitation learning: A tale of pessimism.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Bridging offline reinforcement learning and imitation learning: A tale of pessimism

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.858375Z

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Observation 16c7240c-2801-434c-9ca7-525d0eecf8fa · outbound

This paper cites Trust region policy optimization.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Trust region policy optimization

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.089965Z

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Observation 3f1115b8-aee4-4409-a4d4-0693a3fdc85d · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 36

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Observation 3b2e1149-fdc4-4d38-8b3e-976e37b5566f · outbound

This paper cites Proximal Policy Optimization Algorithms.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Proximal Policy Optimization Algorithms

Reference 37

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Observation 88530470-1a24-44bc-9604-bad92fa4e204 · outbound

This paper cites Sutton and AndrewG.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Sutton and AndrewG

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.831044Z

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Observation 601c7bc8-c6a0-41ef-9765-2c427eebd7dc · outbound

This paper cites Lever- aging factored action spaces for efficient offline reinforcement learning in healthcare.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Lever- aging factored action spaces for efficient offline reinforcement learning in healthcare

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.815625Z

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Observation a778597d-eb97-48f1-a963-2c861bc24650 · outbound

This paper cites CORL: Research-oriented deep offline reinforcement learning library.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL CORL: Research-oriented deep offline reinforcement learning library

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.801226Z

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Observation 01c0eaf4-3bea-4485-811b-50926caddbbc · outbound

This paper cites Reward Constrained Policy Optimization.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Reward Constrained Policy Optimization

Reference 41

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Observation d2f83805-5139-4b0d-a893-8b0679a025e8 · outbound

This paper cites Jump-start reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Jump-start reinforcement learning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.786819Z

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Observation d77c9109-c886-4784-b58a-52e7e42c26cf · outbound

This paper cites Train once, get a family: State-adaptive balances for offline-to- online reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Train once, get a family: State-adaptive balances for offline-to- online reinforcement learning

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.772852Z

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Observation 7cafb6e8-c05c-48d4-ba66-1963ea3253e7 · outbound

This paper cites Supported policy optimization for offline reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Supported policy optimization for offline reinforcement learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.758387Z

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Observation d7ec5233-1756-45db-b3f8-afee46f24507 · outbound

This paper cites Policy finetuning: Bridging sample-efficient offline and online reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Policy finetuning: Bridging sample-efficient offline and online reinforcement learning

Reference 45

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Observation 7759f3da-00c4-4d39-b472-4b77da252b4d · outbound

This paper cites A policy-guided imitation approach for offline reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL A policy-guided imitation approach for offline reinforcement learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.733631Z

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Observation 20d6d736-a044-495b-8099-7d0881f00018 · outbound

This paper cites Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.142024Z

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Observation 7bafb258-e4a9-481d-8b7f-b1ff5d9a276c · outbound

This paper cites Actor-critic alignment for offline-to-online reinforcement learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Actor-critic alignment for offline-to-online reinforcement learning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.717995Z

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Observation 4058ab69-5d44-424e-977b-1bd44d22b625 · outbound

This paper cites Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-11T04:30:49.280625Z

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Observation f05126e9-b6dd-412d-9435-c2f8ec460bd6 · outbound

This paper cites Policy Expansion for Bridging Offline-to-Online Reinforcement Learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Policy Expansion for Bridging Offline-to-Online Reinforcement Learning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.155903Z

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Observation 36075a83-cc30-4203-aa73-eade42be6aea · outbound

This paper cites ENOTO: Improving Offline-to-Online Reinforcement Learning with Q-Ensembles.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL ENOTO: Improving Offline-to-Online Reinforcement Learning with Q-Ensembles

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.160669Z

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Observation f1c5647e-6306-4562-ab2d-7b441ae543d8 · outbound

This paper cites Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T04:30:49.165225Z

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Observation 652d11f2-dc55-47c1-92c3-2f48f7e03ee6 · outbound

This paper cites Online decision transformer.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Online decision transformer

Reference 53

Resolution: malformed identifier; raw_fallback, observed 2026-08-11T04:30:49.702843Z

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

Observation 6a610778-6fdc-45ac-94b5-8d919abe8ac1 · outbound

This paper cites However, our O2SAC still outperforms it with less computational cost during online fine-tuning and less requirements for offline policy.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL However, our O2SAC still outperforms it with less computational cost during online fine-tuning and less requirements for offline policy

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.688112Z

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

Observation 2de3f5ca-53a8-465d-90c2-41cd7ee63c22 · outbound

This paper cites For model-based O2O RL, [31] explores regions with high uncertainty and returns in learned model.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL For model-based O2O RL, [31] explores regions with high uncertainty and returns in learned model

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.673069Z

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.

Observation 292accf8-fd76-46a6-88f4-c3b9448ede9b · outbound

This paper cites Moreover, [4] find that LayerNorm is favourable for efficient online RL with offline data.

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL Moreover, [4] find that LayerNorm is favourable for efficient online RL with offline data

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:30:49.658434Z

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.

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