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Paper Citation Record · LEDGER

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning

As of 7 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.19397.

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

pith.paper-citation-record.v1
2607.19397 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T08:51:17.043206Z

measured 23 of 23 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

23 of 23 outbound references displayed

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Outbound references

Observation de18760f-e064-47e9-aced-5d24ca98b8a6 · outbound

This paper cites nature518(7540), 529–533 (2015).

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning nature518(7540), 529–533 (2015)

Reference 1

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Observation 27f69fc0-91d3-49c2-89cf-ca407ad0460f · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Playing Atari with Deep Reinforcement Learning

Reference 2

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Observation bc063bf2-8af5-47ee-931e-f3e6a40abde4 · outbound

This paper cites In: Learning for Dynamics and Control, pp.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning In: Learning for Dynamics and Control, pp

Reference 3

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Observation 6a4f00f1-2ce8-4570-a95d-3f9413ee3c41 · outbound

This paper cites Understanding Multi-Step Deep Reinforcement Learning: A Systematic Study of the DQN Target.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Understanding Multi-Step Deep Reinforcement Learning: A Systematic Study of the DQN Target

Reference 4

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Observation 6fef3440-7959-4a7e-84f6-016b71815860 · outbound

This paper cites Deep Reinforcement Learning and the Deadly Triad.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Deep Reinforcement Learning and the Deadly Triad

Reference 5

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Observation b15736b1-ef4e-4de5-8fd5-5f056a3e76c6 · outbound

This paper cites Understanding and Preventing Capacity Loss in Reinforcement Learning.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Understanding and Preventing Capacity Loss in Reinforcement Learning

Reference 6

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Observation 494d3c43-0e25-40ef-9d55-e59f3e8fcdad · outbound

This paper cites In: International Conference on Machine Learning, pp.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning In: International Conference on Machine Learning, pp

Reference 7

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Observation b8d94531-4d36-4433-ac82-77f3dfd45f21 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning In: International Conference on Machine Learning, pp

Reference 8

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Observation 1197497d-a717-49f6-854c-351490334ed5 · outbound

This paper cites In: Uncertainty in Artificial Intelligence Workshop on Uncertainty in Deep Learning (2018).

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning In: Uncertainty in Artificial Intelligence Workshop on Uncertainty in Deep Learning (2018)

Reference 9

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Observation 9dc1c19f-a641-460f-b256-a829623950d0 · outbound

This paper cites Continuous control with deep reinforcement learning.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Continuous control with deep reinforcement learning

Reference 10

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Observation 39101a50-030b-434a-8518-7e7801c455cd · outbound

This paper cites In: International Conference on Machine Learning, pp.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning In: International Conference on Machine Learning, pp

Reference 11

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Observation 3ca5855c-c39e-4989-976b-c3d976f8bc22 · outbound

This paper cites In: 17 International Conference on Machine Learning, pp.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning In: 17 International Conference on Machine Learning, pp

Reference 12

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Observation dbde4dde-87cc-4428-8d3e-4a19a9f86d64 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning In: International Conference on Machine Learning, pp

Reference 13

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Observation 3c037691-866e-4791-b487-80e4377eb9ea · outbound

This paper cites Advances in Neural Information Processing Systems35, 17703–17716 (2022).

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Advances in Neural Information Processing Systems35, 17703–17716 (2022)

Reference 14

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Observation 3aef960c-934a-4938-8528-e304a4dd1541 · outbound

This paper cites Simplifying Deep Temporal Difference Learning.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Simplifying Deep Temporal Difference Learning

Reference 15

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Observation 904f1cdf-1fc4-482e-8d29-ec178fd09b9b · outbound

This paper cites Averaging Weights Leads to Wider Optima and Better Generalization.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Averaging Weights Leads to Wider Optima and Better Generalization

Reference 16

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Observation c652b0d4-0148-4092-a8c1-6022c9a43563 · outbound

This paper cites In: Proceedings of the European Conference on Computer Vision (ECCV), pp.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning In: Proceedings of the European Conference on Computer Vision (ECCV), pp

Reference 17

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Observation d49eb7ca-38ac-4d78-8ca1-41223131e6a4 · outbound

This paper cites Journal of Machine Learning Research23(274), 1–18 (2022).

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Journal of Machine Learning Research23(274), 1–18 (2022)

Reference 18

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Observation fca750f4-d18b-4c44-a8dc-cef602c5d5de · outbound

This paper cites Advances in Neural Information Processing Systems38(2026).

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Advances in Neural Information Processing Systems38(2026)

Reference 19

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Observation aa69fea0-4a5a-4dc7-a5ed-1f27a36e6da0 · outbound

This paper cites Layer Normalization.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Layer Normalization

Reference 20

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Observation d6fde913-fe6b-47d7-b25d-6c1a436a441f · outbound

This paper cites Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning

Reference 21

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Observation 102d8910-45df-4d31-9be8-23a7c37a95ef · outbound

This paper cites Scaling CrossQ with Weight Normalization.

Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Scaling CrossQ with Weight Normalization

Reference 22

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Observation 81088ef8-7965-41f1-b1fc-0f816f23f8da · outbound

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Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning Unresolved cited work

Reference 23

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