Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T03:51:00.045896Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.29601.
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 2026-08-03T03:51:00.045896Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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
36 of 36 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 45018918-94ac-444e-9349-22f791115ca0 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Findings of the Association for Computational Linguistics: EMNLP 2023 , pages=
Reference 1
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Unavailable: canonical work link unavailable.
Observation 07253755-4749-4709-88e8-ff7947f56764 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Proceedings of the AAAI Conference on Artificial Intelligence , volume=
Reference 2
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Observation 30d0ee45-2c49-4357-91fb-e5f4c5b2c754 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Nature Machine Intelligence , volume=
Reference 3
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Observation 38350aaa-759f-403c-8b85-056547181446 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Findings of the Association for Computational Linguistics: EACL 2023 , pages =
Reference 4
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Observation c148fccc-aa2c-413d-957b-d0228746feeb · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Advances in Neural Information Processing Systems , volume =
Reference 5
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Observation 5c992202-3e17-4482-a5c7-0f0b443ccd15 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Proceedings of the 36th International Conference on Machine Learning , series =
Reference 6
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Observation 0f21f527-486a-4f15-96fe-2483a0aba867 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Wang, Lu and Chen, Weizhu , title =
Reference 7
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Observation 5910cea5-3385-4e28-9812-a20c1a716522 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , pages =
Reference 8
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Unavailable: canonical work link unavailable.
Observation df347900-eff2-4ac3-af10-49b45fbcb77e · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Unresolved cited work
Reference 9
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Observation 4bf36c49-7ab3-4517-8fed-f870f6bbc495 · outbound
Reference 10
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Observation 785ed27c-2d85-4e2f-b1bd-ee521acbbf25 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) , pages =
Reference 11
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Observation 0f6c7e5e-4678-4ee9-b7ed-44551e6c5f66 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Advances in Neural Information Processing Systems , volume =
Reference 12
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Observation cfdb1259-b35c-4799-8dc7-1c9afce076fd · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Unresolved cited work
Reference 13
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Unavailable: canonical work link unavailable.
Observation 7ec228e4-347b-48e9-b065-3355ecd60998 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs UniPELT: A unified framework for parameter-efficient language model tuning , booktitle =
Reference 14
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Observation 481c99d3-7b4e-46fa-a895-6ef23bcc7997 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages =
Reference 15
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Unavailable: canonical work link unavailable.
Observation 3410ecbc-9c14-46f3-afd3-b9e0c0a10827 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages =
Reference 16
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Observation 221b310a-cbcb-4dae-a670-8ff326de5077 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs AdapterFusion: Non-destructive task composition for transfer learning , booktitle =
Reference 17
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Observation 3808e523-d0f6-4f8f-83cd-f03c4d67e9fc · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Progressive Neural Networks
Reference 18
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Observation fb4dff3b-b020-4250-ad50-0c996a57523b · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Reference 19
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Unavailable: canonical work link unavailable.
Observation 7e265a5f-c706-4087-8eea-5f0e0b7845d6 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models
Reference 20
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Unavailable: canonical work link unavailable.
Observation 143fc603-97c9-4060-baf3-640385ead246 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Advances in Neural Information Processing Systems , volume =
Reference 21
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Unavailable: canonical work link unavailable.
Observation 7e0eecf9-0775-45c4-88dd-b3463b7da17c · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
Reference 22
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Observation dce76c63-7c73-4c37-ac19-d7e11911d089 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs IEEE Transactions on Knowledge and Data Engineering , volume =
Reference 23
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Unavailable: canonical work link unavailable.
Observation 891e5ca8-2274-4d12-915e-77838b9ed7b7 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Reference 24
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Observation 8b875ad6-5590-4349-8c7b-a8afcb801813 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
Reference 25
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Unavailable: canonical work link unavailable.
Observation db488867-646b-43f5-955a-eb3583255f3c · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
Reference 26
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Unavailable: canonical work link unavailable.
Observation f95fc609-8b2b-4b8c-88a5-72801ce26d94 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Unresolved cited work
Reference 27
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Unavailable: canonical work link unavailable.
Observation adcadb19-3cd8-4a19-a1de-0ea8b56f6c48 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers) , pages =
Reference 28
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Unavailable: canonical work link unavailable.
Observation 113a9142-769a-4291-9121-43e2a648acd2 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Unresolved cited work
Reference 29
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Observation 04622993-07b7-4915-82d9-9fc10043d3ad · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Unresolved cited work
Reference 30
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Observation 354bc783-aba8-4c5e-80c9-3249ca475f2c · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs ACM Computing Surveys , volume =
Reference 31
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Observation 94b7a491-dda5-4163-a5d8-1d6599ff2bed · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Parameter-Efficient Continual Fine-Tuning: A Survey
Reference 32
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Unavailable: canonical work link unavailable.
Observation 2b4893f7-3f76-4f33-a52c-a591f920ed5a · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs CHIRPs: Change-Induced Regret Proxy metrics for Lifelong Reinforcement Learning
Reference 33
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Observation d83adc6c-6466-4318-82d5-53c5b2060bff · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Bossens and Adam J
Reference 34
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Observation cb24f58e-f5b1-47f3-a22f-5a8e8f7f37e8 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs 2025 , eprint=
Reference 35
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Observation 9cf63e09-089a-4166-9b39-f98d685bddb5 · outbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs M o RE : A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Reference 36
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No inbound Pith citation observations are available.