Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T17:09:59.692161Z
Paper Citation Record · LEDGER
As of 11 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2607.17760.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T17:09:59.692161Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
59 of 59 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation ed4851a7-4f04-4232-811b-8e244ad42bc8 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 1990 , doi =
Reference 1
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Observation 145b0cdc-7475-49d2-ae9c-3f8cea3d12ce · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Journal of Basic Engineering , volume=
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Observation c9f5b4f5-087c-435f-805a-507a70486bc2 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Scaling Learning Algorithms Towards
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Observation 1a008e90-dad3-466b-a021-8bf5810a4be9 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning and Osindero, Simon and Teh, Yee Whye , journal =
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Observation 98f7329c-a5a7-416b-bf0b-552960a556d2 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 2016 , publisher=
Reference 5
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Observation 30bfb89e-3fbd-4eba-b344-b8d93285b072 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 2018 , publisher=
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Observation f5234d46-996c-4379-a284-061db527c00b · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning and Russell, Stuart J
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Observation 83f9554e-75e2-4751-8da5-2d593751a66e · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning International Conference on Machine Learning , year=
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Observation 2b42e777-8c35-4118-b247-ba39adbd6969 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 2017 , eprint=
Reference 9
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Observation 4baecfa6-466f-4b8f-b9db-04adab1df920 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 2016 , eprint=
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Observation 3da0040a-582e-47e7-b255-74b8820e0961 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in Neural Information Processing Systems , editor=
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Observation 2dcd94bc-24fc-4a5b-bd06-63dfaedb0ff1 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning International Conference on Learning Representations , year=
Reference 12
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Observation fa04c3d8-987f-4bbe-965b-711e182214bb · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=
Reference 13
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Observation eeeca7d3-d2e3-444f-bc3d-783746d44ba5 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning D4RL: Datasets for Deep Data-Driven Reinforcement Learning
Reference 14
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Observation bdf8ccc1-50d9-4737-b4b1-382d9bea0b30 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 2024 IEEE International Conference on Robotics and Automation (ICRA) , pages=
Reference 15
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Observation 9a614bc0-45e2-43ea-9500-fc52255c1916 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Conference on robot learning , pages=
Reference 16
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Observation 5c89edee-61a3-479c-8f33-09684b0e64f2 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 2020 , url =
Reference 17
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Observation 3e371397-935e-4fa2-878f-226b70d6a26e · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Conference on robot learning , pagesfu2018airl=
Reference 18
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Observation f5965891-aa36-43d8-b866-e321867e46ef · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Proceedings of the 38th International Conference on Machine Learning , pages =
Reference 19
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Observation ca9f53ad-4ccc-4ea4-be52-f77719301f04 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Neural Information Processing Systems , year=
Reference 20
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Observation 9c9f290f-70f7-45f4-8dd4-dad648fef37f · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Dragan and Sergey Levine , booktitle=
Reference 21
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Observation 02726ff4-49ef-42c7-be18-38fac7c05aad · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 2021 , url=
Reference 22
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Observation 46d758b9-bfaa-4f70-b4fc-d5ad5265cc10 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Deep RL Workshop NeurIPS 2021 , year=
Reference 23
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Observation 8a678b3f-475c-425e-9198-7efcb65f1f51 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Proceedings of the 39th International Conference on Machine Learning , pages =
Reference 24
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Observation f448c726-385f-429a-acda-c276ca681972 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Proceedings of the 40th International Conference on Machine Learning , year =
Reference 25
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Observation 19635bc5-f388-401f-ac98-e1d89af84d96 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning International conference on machine learning , pages=
Reference 26
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Observation f2187602-b055-4215-875c-3dd93a80a367 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in neural information processing systems , volume=
Reference 27
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Observation e71173d9-2272-4b83-bfc7-01d9b07a44ef · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in Neural Information Processing Systems , volume=
Reference 28
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Observation fd33467c-72e8-4e5a-86d3-82b8393ef5c2 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning International conference on machine learning , pages=
Reference 29
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Observation 9a6d5318-6d45-48b1-b5e3-a37593624a16 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning The Twelfth International Conference on Learning Representations , year=
Reference 30
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Observation 42fb8990-ed7e-44ae-9717-23a6d41ad606 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Proceedings of the 39th International Conference on Machine Learning , year =
Reference 31
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Observation 6bcbc127-9687-4eb9-911c-e31587ad68b2 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning The Eleventh International Conference on Learning Representations , year=
Reference 32
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Observation ac4ec188-4b73-4f70-b01b-8a878c6f626f · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in Neural Information Processing Systems , editor=
Reference 33
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Observation 90e97231-995f-438e-9252-e0b26587f322 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning , author=
Reference 34
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Observation ea12df81-3c0b-4786-b567-75fcd3f21cbc · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning International Conference on Learning Representations , year=
Reference 35
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Observation d07a7f70-cb26-415f-9aa5-0c985b13e7f5 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos
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Observation 41142d47-1ae0-474d-bf18-7f28945f2f28 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 2nd Conference on Robot Learning , year=
Reference 37
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Observation dc7bfc09-67dc-4ce0-a557-7f276775133c · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 2018 , eprint=
Reference 38
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Observation fa3b6d2d-dbb8-4e18-ac6f-385908cbddd4 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Proceedings of the 38th International Conference on Machine Learning , year =
Reference 39
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Conference on robot learning , pages=
Reference 40
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in neural information processing systems , volume=
Reference 41
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Observation 6df95de4-3235-4d91-9e19-c8e4366c83d6 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning
Reference 42
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Observation d5090d62-7bfc-47ce-a40c-c6bcbdcd7ac3 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in neural information processing systems , volume=
Reference 43
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Observation e773526f-6a99-4e7e-8b4b-aacc54b7472c · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Forty-first International Conference on Machine Learning , year=
Reference 44
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning 6th Annual Conference on Robot Learning , year=
Reference 45
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning International Conference on Learning Representations , year=
Reference 46
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Unresolved cited work
Reference 47
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in Neural Information Processing Systems , volume=
Reference 48
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Observation 5decf9e6-fb01-487a-b515-ac1233f6c478 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in Neural Information Processing Systems , volume=
Reference 49
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in Neural Information Processing Systems , volume=
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Observation 8ef9b015-621c-4459-b4a8-0da76857d944 · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning International Conference on Learning Representations , year=
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Observation 41d0aba9-2e18-4870-9067-6a7c787f821f · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Advances in neural information processing systems , volume=
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Observation f3acf74e-2024-4613-9ab9-b9d4745650dc · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning CoRR , volume =
Reference 53
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning ICML , year =
Reference 54
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Observation 1681649f-a104-462b-8bc7-11be0fa1c5bb · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning ArXiv , year=
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Proceedings of the 37th International Conference on Machine Learning , articleno =
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Proceedings of the 37th International Conference on Machine Learning , articleno =
Reference 57
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Observation ff3f9f21-7086-4c93-acea-b5e6ccfc1d4c · outbound
Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Proximal Policy Optimization Algorithms
Reference 58
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Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning Conference on Robot Learning (CoRL) , year=
Reference 59
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No inbound Pith citation observations are available.