Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning | Paper Citation Record

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This paper cites Machine learning , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Machine learning , volume=

Reference 1

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This paper cites Machine learning , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Machine learning , volume=

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning 1998 , publisher=

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This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the AAAI conference on artificial intelligence , volume=

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This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 5

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This paper cites and Singh, Satinder P.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning and Singh, Satinder P

Reference 6

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This paper cites Advances in neural information processing systems , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in neural information processing systems , volume=

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This paper cites International conference on machine learning , pages=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning International conference on machine learning , pages=

Reference 8

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This paper cites Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening

Reference 9

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Observation e25c9158-9fed-4f50-b4a8-a1f00e1ef290 · outbound

This paper cites Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities

Reference 10

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Observation 66e53fed-4356-44a0-808e-a68d3b469e54 · outbound

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

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Offline Reinforcement Learning with Implicit Q-Learning

Reference 11

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Extreme Q-Learning: MaxEnt RL without Entropy

Reference 12

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Econometrica: Journal of the Econometric Society , pages=

Reference 13

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Observation 68355baa-5fdd-4f87-a493-481468fe76aa · outbound

This paper cites Advances in neural information processing systems , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in neural information processing systems , volume=

Reference 14

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This paper cites Forty-second International Conference on Machine Learning , year=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Forty-second International Conference on Machine Learning , year=

Reference 15

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Observation dab51c5b-b274-4c6b-a9a5-8c193c8191d0 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 16

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This paper cites International Conference on Learning Representations , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning International Conference on Learning Representations , volume=

Reference 17

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Observation a9994f8e-f09f-4a61-92c5-328bb4e16d45 · outbound

This paper cites What Matters in Learning from Offline Human Demonstrations for Robot Manipulation.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

Reference 18

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Observation 74d2f582-6ada-4aa0-a076-048f86a3b609 · outbound

This paper cites Revisiting the Minimalist Approach to Offline Reinforcement Learning , url =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Revisiting the Minimalist Approach to Offline Reinforcement Learning , url =

Reference 19

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This paper cites Flow Matching for Generative Modeling.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Flow Matching for Generative Modeling

Reference 20

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This paper cites The International Journal of Robotics Research , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning The International Journal of Robotics Research , volume=

Reference 21

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This paper cites The Thirteenth International Conference on Learning Representations , year=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning The Thirteenth International Conference on Learning Representations , year=

Reference 22

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This paper cites 2026 , eprint=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning 2026 , eprint=

Reference 23

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This paper cites Value-Based Deep.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Value-Based Deep

Reference 24

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning The Thirty-eighth Annual Conference on Neural Information Processing Systems , year=

Reference 25

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This paper cites 2025 , url=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning 2025 , url=

Reference 26

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Unresolved cited work

Reference 27

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This paper cites , title =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning , title =

Reference 28

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This paper cites 2024 , eprint=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning 2024 , eprint=

Reference 29

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This paper cites 2026 , eprint=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning 2026 , eprint=

Reference 30

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This paper cites Deep Reinforcement Learning and the Deadly Triad.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Deep Reinforcement Learning and the Deadly Triad

Reference 31

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the 1993 connectionist models summer school , pages=

Reference 32

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This paper cites Advances in neural information processing systems , volume=.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in neural information processing systems , volume=

Reference 33

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Sur les op

Reference 34

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning 2014 , publisher=

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Generalized quantiles as risk measures , journal =

Reference 36

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning 2013 , month =

Reference 37

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 38

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This paper cites Proceedings of the 36th International Conference on Machine Learning (ICML) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the 36th International Conference on Machine Learning (ICML) , year =

Reference 39

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This paper cites Advances in Neural Information Processing Systems 32 (NeurIPS) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in Neural Information Processing Systems 32 (NeurIPS) , year =

Reference 40

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This paper cites Advances in Neural Information Processing Systems 33 (NeurIPS) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in Neural Information Processing Systems 33 (NeurIPS) , year =

Reference 41

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This paper cites Advances in Neural Information Processing Systems 34 (NeurIPS) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in Neural Information Processing Systems 34 (NeurIPS) , year =

Reference 42

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This paper cites International Conference on Learning Representations (ICLR) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning International Conference on Learning Representations (ICLR) , year =

Reference 43

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This paper cites International Conference on Learning Representations (ICLR) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning International Conference on Learning Representations (ICLR) , year =

Reference 44

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 89319c69-97f7-4606-a6ce-d3faec6eef93 · outbound

This paper cites Advances in Neural Information Processing Systems 35 (NeurIPS) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in Neural Information Processing Systems 35 (NeurIPS) , year =

Reference 45

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Observation ac5e6bf4-0354-4fbc-b3dd-dd336d88f302 · outbound

This paper cites Offline Reinforcement Learning as Anti-Exploration , booktitle =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Offline Reinforcement Learning as Anti-Exploration , booktitle =

Reference 46

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Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the 40th International Conference on Machine Learning (ICML) , year =

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.746685Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ab042adc-a7c6-412f-b1f8-2eb7a29ffcfe · outbound

This paper cites Proceedings of the 38th International Conference on Machine Learning (ICML) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the 38th International Conference on Machine Learning (ICML) , year =

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.715621Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5842a013-6e7a-4a2f-bc18-2744fa0eb4f2 · outbound

This paper cites Advances in Neural Information Processing Systems 34 (NeurIPS) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in Neural Information Processing Systems 34 (NeurIPS) , year =

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.680986Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3a063cd4-19df-4bcd-8aa6-9244456288f8 · outbound

This paper cites Proceedings of the 35th International Conference on Machine Learning (ICML) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the 35th International Conference on Machine Learning (ICML) , year =

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.648641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f72edb3c-a79a-46cc-80a0-7570cc6b2ef4 · outbound

This paper cites Proceedings of the 37th International Conference on Machine Learning (ICML) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the 37th International Conference on Machine Learning (ICML) , year =

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.616154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4cfd3ffa-40db-4761-9787-4ac0b52919a1 · outbound

This paper cites Revisiting.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Revisiting

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.587948Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d4f97450-5921-4a03-8ad3-c1241a9a3717 · outbound

This paper cites Advances in Neural Information Processing Systems 38 (NeurIPS) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in Neural Information Processing Systems 38 (NeurIPS) , year =

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.552686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c4301007-bce7-4822-b88c-31f0c0d25283 · outbound

This paper cites and Munos, R.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning and Munos, R

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.513390Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e47060d1-6c2b-4120-86cf-347cfc7966fd · outbound

This paper cites Statistics and Samples in Distributional Reinforcement Learning , booktitle =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Statistics and Samples in Distributional Reinforcement Learning , booktitle =

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.456611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e848eb86-a4b3-430a-aa00-676d2b8aa517 · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning International Conference on Learning Representations (ICLR) , year =

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.430630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 33ded815-72d9-416e-a63f-8e8804e547fc · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning International Conference on Learning Representations (ICLR) , year =

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.403649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 670b1a81-6766-4050-ba76-1cf70d38fee3 · outbound

This paper cites and Zhou, Mingyuan , title =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning and Zhou, Mingyuan , title =

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.382181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a72d2690-b344-4752-ae67-70ee42ca6f48 · outbound

This paper cites and Kumar, Vikash and Levine, Sergey and Finn, Chelsea , title =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning and Kumar, Vikash and Levine, Sergey and Finn, Chelsea , title =

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.358454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a67bb99a-ebe4-4c44-8289-3586cbede48f · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T15:06:50.483090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b159dcac-838a-448f-9c8b-ea97161450e4 · outbound

This paper cites Advances in Neural Information Processing Systems 36 (NeurIPS) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in Neural Information Processing Systems 36 (NeurIPS) , year =

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.325830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9a7f8a6a-1557-4061-8488-4eaf0592c0d5 · outbound

This paper cites and Smith, Laura and Kostrikov, Ilya and Levine, Sergey , title =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning and Smith, Laura and Kostrikov, Ilya and Levine, Sergey , title =

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.276547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 174d633a-e74d-4d99-9707-6fb712d0387c · outbound

This paper cites and Bellemare, Marc G.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning and Bellemare, Marc G

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.247226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6b04cae4-6669-4745-a134-b74f16b7b5cc · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume =

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.207655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4e9b1ee6-c62b-4dea-acdb-6b592f06a8f2 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume =

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.156893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ab82142d-8529-443d-84e3-95f35dbfd25b · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning International Conference on Learning Representations (ICLR) , year =

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.120731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8e1bd23b-ad48-41e2-a5c0-b5d1b711de30 · outbound

This paper cites Advances in Neural Information Processing Systems 37 (NeurIPS) , year =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Advances in Neural Information Processing Systems 37 (NeurIPS) , year =

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.090106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f33cebe7-29a0-40cf-ac69-445cb37dc799 · outbound

This paper cites Atti del Congresso Internazionale dei Matematici, Bologna , volume =.

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning Atti del Congresso Internazionale dei Matematici, Bologna , volume =

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:06:51.060220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers