Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-11T01:57:40.347786Z
Paper Citation Record · LEDGER
As of 4 August 2026, this Paper Citation Record lists 100 of 187 outbound references and 0 inbound Pith citation observations for arXiv:2605.07063.
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 2026-05-11T01:57:40.347786Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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
100 of 187 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation cd2794c9-5276-4f19-95b2-5267c3b7c174 · outbound
Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Advances in Neural Information Processing Systems , pages =
Reference 1
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Transactions on Machine Learning Research , note =
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training SmolLM2: When Smol Goes Big--Data-Centric Training of a Small Language Model , journal =
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Hashimoto , title =
Reference 4
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Journal of machine learning research , number =
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Reference 8
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training OPT 2024: Optimization for Machine Learning , year =
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Optimization methods for large-scale machine learning , journal =
Reference 10
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Open problems and fundamental limitations of reinforcement learning from human feedback , journal =
Reference 12
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training The Twelfth International Conference on Learning Representations , year =
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Advances in Neural Information Processing Systems , year =
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Advances in neural information processing systems , volume =
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Observation 7e1988eb-f0b6-4474-bf33-1dd3e8cac730 · outbound
Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Transactions of the Association for Computational Linguistics , pages =
Reference 17
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Observation 730aef85-8074-4ed9-b2b8-e96f014666ee · outbound
Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Frustratingly easy domain adaptation , booktitle =
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Advances in neural information processing systems , pages =
Reference 20
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Unresolved cited work
Reference 21
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training International Conference on Machine Learning , organization =
Reference 22
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Naval research logistics quarterly , number =
Reference 23
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Domain-adversarial training of neural networks , journal =
Reference 24
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training International conference on machine learning , organization =
Reference 26
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training EMNLP-IJCNLP 2019 , pages =
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Information and Software Technology , pages =
Reference 28
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Textbooks are all you need , journal =
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Proceedings of the 2018 conference on empirical methods in natural language processing , pages =
Reference 32
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Gradient Descent Happens in a Tiny Subspace
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Observation 7ce1f0a4-1949-4ad3-ac17-531e5730bcc1 · outbound
Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Don’t stop pretraining: Adapt language models to domains and tasks , booktitle =
Reference 35
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Findings of the Association for Computational Linguistics: EMNLP 2021 , doi =
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Observation 399afc03-72c8-46b7-bb5f-1cb91b78b3c4 · outbound
Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Transactions on Machine Learning Research , url =
Reference 37
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Reference 38
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Foundations and Trends in Optimization , number =
Reference 39
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training First Conference on Language Modeling , url =
Reference 40
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Forty-second International Conference on Machine Learning , year =
Reference 41
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Reference 42
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Reference 43
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Advances in Neural Information Processing Systems , editor =
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Ma and Han Zhao , title =
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Reference 49
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Communications in Statistics-Simulation and Computation , number =
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Reference 54
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Reference 57
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Reference 63
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Reference 64
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Reference 67
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Reference 68
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Reference 69
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Reference 70
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Reference 71
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Reference 72
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Reference 73
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Reference 74
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Reference 75
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Reference 76
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Reference 77
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training IEEE Transactions on knowledge and data engineering , number =
Reference 78
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Reference 79
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Reference 80
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Reference 81
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Reference 83
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Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Albalak, Y
Reference 116
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Observation 4ac4052f-64d9-4cbc-bd54-92c7e658be65 · outbound
Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Ben-David, J
Reference 120
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Reference 121
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