Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon | Paper Citation Record

Observation 60bb9e6b-52c1-4116-9982-3b30e9f26cf4 · outbound

This paper cites Normal approximation for stochastic gradient descent via non-asymptotic rates of martingale clt.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Normal approximation for stochastic gradient descent via non-asymptotic rates of martingale clt

Reference 1

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This paper cites Adaptive control.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Adaptive control

Reference 2

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This paper cites Logarithmic regret for episodic continuous-time linear-quadratic reinforcement learning over a finite-time horizon.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Logarithmic regret for episodic continuous-time linear-quadratic reinforcement learning over a finite-time horizon

Reference 3

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This paper cites Adaptive control with the stochastic approximation algorithm: Geometry and convergence.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Adaptive control with the stochastic approximation algorithm: Geometry and convergence

Reference 4

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Observation aaad1fa6-b5a3-43de-927a-534f9dcfc526 · outbound

This paper cites Dynamic programming and optimal control: Volume I , volume 4.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Dynamic programming and optimal control: Volume I , volume 4

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:35.925538Z

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Observation 9b498ff2-d462-4347-bcde-18f845d587a2 · outbound

This paper cites Reinforcement learning applied to linear quadratic regulation.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Reinforcement learning applied to linear quadratic regulation

Reference 6

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Observation 1157fc72-6af4-465d-b37b-4467c5d41ba4 · outbound

This paper cites Linear-Quadratic Mean-Field Reinforcement Learning: Convergence of Policy Gradient Methods.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Linear-Quadratic Mean-Field Reinforcement Learning: Convergence of Policy Gradient Methods

Reference 7

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This paper cites Statistical inference for online decision making via stochastic gradient descent.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Statistical inference for online decision making via stochastic gradient descent

Reference 8

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Observation 39472f0f-c982-4e40-b087-97cc71a7fa31 · outbound

This paper cites Statistical inference for model parameters in stochastic gradient descent.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Statistical inference for model parameters in stochastic gradient descent

Reference 9

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This paper cites Robust inference via multiplier bootstrap.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Robust inference via multiplier bootstrap

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:35.130232Z

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Observation 618178cc-5fd5-4d0c-90fc-dc6a9eebd61d · outbound

This paper cites On the sample complexity of the linear quadratic regulator.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon On the sample complexity of the linear quadratic regulator

Reference 11

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Observation a2d1892e-a99d-49fe-a8bd-3a3e62f4c9fe · outbound

This paper cites Challenges of reinforcement learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Challenges of reinforcement learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:34.966921Z

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Observation 61a1fb16-e1db-4c3e-a0b2-89e0f6070336 · outbound

This paper cites Challenges of real-world reinforcement learning: definitions, benchmarks and analysis.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Challenges of real-world reinforcement learning: definitions, benchmarks and analysis

Reference 13

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This paper cites On the convergence theory of debiased model-agnostic meta-reinforcement learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon On the convergence theory of debiased model-agnostic meta-reinforcement learning

Reference 14

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This paper cites Online bootstrap confidence intervals for the stochastic gradient descent estimator.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Online bootstrap confidence intervals for the stochastic gradient descent estimator

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:34.253477Z

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Observation 43d704f2-298b-4d3d-a850-d1d5cad672cc · outbound

This paper cites Global convergence of policy gradient methods for the linear quadratic regulator.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Global convergence of policy gradient methods for the linear quadratic regulator

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:34.063605Z

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Observation 784d7f5b-b5ee-4f7f-9fc0-2518b2c347cc · outbound

This paper cites Convergence of policy gradient methods for finite-horizon exploratory linear-quadratic control problems.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Convergence of policy gradient methods for finite-horizon exploratory linear-quadratic control problems

Reference 17

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This paper cites Reinforcement learning for linear-convex models with jumps via stability analysis of feedback controls.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Reinforcement learning for linear-convex models with jumps via stability analysis of feedback controls

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:33.518251Z

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Observation 5e84d419-1be6-43ef-a171-90223ace1d2d · outbound

This paper cites Policy gradient methods for the noisy linear quadratic regulator over a finite horizon.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Policy gradient methods for the noisy linear quadratic regulator over a finite horizon

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:33.307106Z

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This paper cites Bootstrapping upper confidence bound.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Bootstrapping upper confidence bound

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:33.045307Z

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This paper cites Model-based or model-free, a review of approaches in reinforcement learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Model-based or model-free, a review of approaches in reinforcement learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:32.809383Z

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This paper cites Improved zeroth-order variance reduced algorithms and analysis for nonconvex optimization.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Improved zeroth-order variance reduced algorithms and analysis for nonconvex optimization

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:32.496520Z

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This paper cites On incomplete learning and certainty-equivalence control.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon On incomplete learning and certainty-equivalence control

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:32.213608Z

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This paper cites Iterated least squares in multiperiod control.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Iterated least squares in multiperiod control

Reference 24

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This paper cites Fast inference for quantile regression with tens of millions of observations.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Fast inference for quantile regression with tens of millions of observations

Reference 25

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This paper cites Statistical Estimation and Inference via Local SGD in Federated Learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Statistical Estimation and Inference via Local SGD in Federated Learning

Reference 26

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This paper cites Unifying offline causal inference and online bandit learning for data driven decision.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Unifying offline causal inference and online bandit learning for data driven decision

Reference 27

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This paper cites A generalized reinforcement-learning model: Convergence and applications.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon A generalized reinforcement-learning model: Convergence and applications

Reference 28

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This paper cites A review of uncertainty for deep reinforcement learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon A review of uncertainty for deep reinforcement learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:31.091172Z

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This paper cites Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments

Reference 30

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This paper cites Certainty equivalence is efficient for linear quadratic control.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Certainty equivalence is efficient for linear quadratic control

Reference 31

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This paper cites A linear quadratic regulator based speed control for remote-controlled racing cars.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon A linear quadratic regulator based speed control for remote-controlled racing cars

Reference 32

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This paper cites Black-box generalization: Stability of zeroth-order learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Black-box generalization: Stability of zeroth-order learning

Reference 33

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This paper cites Acceleration of stochastic approximation by averaging.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Acceleration of stochastic approximation by averaging

Reference 34

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This paper cites Temporal Difference Models: Model-Free Deep RL for Model-Based Control.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Temporal Difference Models: Model-Free Deep RL for Model-Based Control

Reference 35

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This paper cites Online bootstrap inference for policy evaluation in reinforcement learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Online bootstrap inference for policy evaluation in reinforcement learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:30.143073Z

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This paper cites The unintended consequences of discount regularization: Improving regularization in certainty equivalence reinforcement learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon The unintended consequences of discount regularization: Improving regularization in certainty equivalence reinforcement learning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:29.983187Z

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Observation 33bd0d6e-8c77-488e-8e73-9b1ae9647dd4 · outbound

This paper cites Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-05T21:35:28.059162Z

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This paper cites Efficient estimations from a slowly convergent robbins-monro process.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Efficient estimations from a slowly convergent robbins-monro process

Reference 39

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This paper cites Gaussian approximation and multiplier bootstrap for polyak-ruppert averaged linear stochastic approximation with applications to td learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Gaussian approximation and multiplier bootstrap for polyak-ruppert averaged linear stochastic approximation with applications to td learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:29.854106Z

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This paper cites Dynamic causal effects evaluation in a/b testing with a reinforcement learning framework.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Dynamic causal effects evaluation in a/b testing with a reinforcement learning framework

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:29.720305Z

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This paper cites Learning optimal controllers by policy gradient: Global optimality via convex parameterization.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Learning optimal controllers by policy gradient: Global optimality via convex parameterization

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:29.598742Z

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Observation 82b60fb8-3072-4679-a76d-90a8211c62c1 · outbound

This paper cites Optimal scheduling of entropy regularizer for continuous-time linear-quadratic reinforcement learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Optimal scheduling of entropy regularizer for continuous-time linear-quadratic reinforcement learning

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:29.477974Z

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Observation ec2992d7-cfff-4afc-8363-59c56f6cce3f · outbound

This paper cites Robust exploration in linear quadratic reinforcement learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Robust exploration in linear quadratic reinforcement learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:29.368728Z

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Observation 1b34a2f0-c3bf-415c-bbaf-e3679dd4cd02 · outbound

This paper cites Distributed lqr design for identical dynamically coupled systems: Application to load frequency control of multi-area power grid.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Distributed lqr design for identical dynamically coupled systems: Application to load frequency control of multi-area power grid

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:29.230310Z

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Observation d9516177-5a22-4215-8422-76abd2bc77a3 · outbound

This paper cites First-order regret in reinforcement learning with linear function approximation: A robust estimation approach.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon First-order regret in reinforcement learning with linear function approximation: A robust estimation approach

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:29.081763Z

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Observation 0771b835-b586-4bf6-bf9a-a262f3fbfb0f · outbound

This paper cites Residual Bootstrap Exploration for Bandit Algorithms.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Residual Bootstrap Exploration for Bandit Algorithms

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-08-05T21:35:27.961339Z

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Observation d0e2f6e8-73f4-4fb0-a457-ff4d79088e7b · outbound

This paper cites Exact asymptotics for linear quadratic adaptive control.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Exact asymptotics for linear quadratic adaptive control

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:28.929421Z

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Observation 8503830b-2585-4327-9b3c-0e64e498b5cf · outbound

This paper cites Continuous-time mean--variance portfolio selection: A reinforcement learning framework.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Continuous-time mean--variance portfolio selection: A reinforcement learning framework

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:28.818138Z

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Observation 2331a859-145c-48a3-9385-e20128b4e3ea · outbound

This paper cites Stochastic zeroth-order optimization in high dimensions.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Stochastic zeroth-order optimization in high dimensions

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:28.720661Z

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Observation adc91b51-daa4-48e6-b62d-13db23fe28cf · outbound

This paper cites Leveraging linear quadratic regulator cost and energy consumption for ultrareliable and low-latency iot control systems.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Leveraging linear quadratic regulator cost and energy consumption for ultrareliable and low-latency iot control systems

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:28.601244Z

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Observation e1e7ea49-2d11-44bf-b1b8-8a2588cd0fe3 · outbound

This paper cites Provably global convergence of actor-critic: A case for linear quadratic regulator with ergodic cost.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Provably global convergence of actor-critic: A case for linear quadratic regulator with ergodic cost

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:28.461702Z

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Observation 1456cc1b-6615-44cd-b6f3-899786ffcef2 · outbound

This paper cites Online covariance matrix estimation in stochastic gradient descent.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Online covariance matrix estimation in stochastic gradient descent

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:28.305913Z

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Observation a418e2f7-6b01-417e-86f2-07c3a8339bae · outbound

This paper cites Uncertainty quantification and exploration for reinforcement learning.

Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon Uncertainty quantification and exploration for reinforcement learning

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:35:28.187289Z

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