Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T15:39:41.455438Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2607.11889.
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 2026-08-02T15:39:41.455438Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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
43 of 43 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation cb6ad59f-2a92-4ec4-bd20-3a38d758c01c · outbound
Scaling Point-in-Time Language Models Scalable Second Order Optimization for Deep Learning
Reference 1
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Observation 9647fff0-760b-4d3f-8553-4e43a915f84f · outbound
Scaling Point-in-Time Language Models DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
Reference 3
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Observation 3f3a08d2-b253-441f-ba5d-719e68bbfe60 · outbound
Scaling Point-in-Time Language Models LoRA Learns Less and Forgets Less
Reference 4
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Observation ab636576-8d04-4099-b7ec-d50e2f1669bd · outbound
Scaling Point-in-Time Language Models GPTScore: Evaluate as You Desire
Reference 10
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Observation 13d42076-af85-40c8-ab8b-de368453724b · outbound
Scaling Point-in-Time Language Models Representation Degeneration Problem in Training Natural Language Generation Models
Reference 11
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Observation 82ad7db4-c7d2-42bf-9d2d-7108063ab95e · outbound
Scaling Point-in-Time Language Models The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Reference 12
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Observation 62b7253c-cf4c-4b74-904b-323c4d3ddb86 · outbound
Scaling Point-in-Time Language Models Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis
Reference 13
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Observation b510c958-6b20-475c-b8eb-991fa208eee5 · outbound
Scaling Point-in-Time Language Models Continual Pre-Training of Large Language Models: How to (re)warm your model?
Reference 14
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Observation a53751f2-49d5-4490-bef0-d7637f4e4c2d · outbound
Scaling Point-in-Time Language Models Chronologically Consistent Large Language Models
Reference 16
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Observation 827cc41d-17dd-44f8-850e-6a1002c4bfef · outbound
Scaling Point-in-Time Language Models Scaling Laws for Neural Language Models
Reference 18
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Observation a6e68a9f-f59c-4174-9689-4b9adf2fb501 · outbound
Scaling Point-in-Time Language Models Continual Pre-training of Language Models
Reference 19
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Observation fa718e08-6813-4975-81cb-7350208e9b59 · outbound
Scaling Point-in-Time Language Models Understanding Catastrophic Forgetting in Language Models via Implicit Inference
Reference 20
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Observation 53e34363-fa6c-48b0-9d03-cfd979299f22 · outbound
Scaling Point-in-Time Language Models Tulu 3: Pushing Frontiers in Open Language Model Post-Training
Reference 21
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Observation 4a83669e-bd95-4d7a-bf67-c65b80da2199 · outbound
Scaling Point-in-Time Language Models Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning
Reference 22
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Observation 67cd5d86-b2b8-4b58-bc41-af628a67289c · outbound
Scaling Point-in-Time Language Models From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline
Reference 23
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Observation 231d62bb-421a-469e-b33c-a37d1f0f0f43 · outbound
Scaling Point-in-Time Language Models G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
Reference 24
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Observation fa552c9a-bddf-4e73-9c47-9f22269e42f2 · outbound
Scaling Point-in-Time Language Models Training language models to follow instructions with human feedback
Reference 25
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Observation 34512196-4827-4674-96a8-cb95e41436b2 · outbound
Scaling Point-in-Time Language Models Lookahead bias in pretrained language models
Reference 28
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Observation a4339ad7-c961-4d2c-b8d3-e476c273cedf · outbound
Scaling Point-in-Time Language Models Unresolved cited work
Reference 29
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Observation 29ba1025-8b9c-4bad-857f-43d089431b57 · outbound
Scaling Point-in-Time Language Models Gemma 3 Technical Report
Reference 30
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Observation 41a7b25e-e31e-446f-94bf-f4bb4ef046cd · outbound
Scaling Point-in-Time Language Models Gemma 2: Improving Open Language Models at a Practical Size
Reference 31
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Observation ea430f53-6fc1-4c0e-8a0f-9a48d1842216 · outbound
Scaling Point-in-Time Language Models LLaMA: Open and Efficient Foundation Language Models
Reference 32
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Observation 87b7ff20-00ef-478a-bb84-90714660267a · outbound
Scaling Point-in-Time Language Models Large Language Models are not Fair Evaluators
Reference 33
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Observation 28d7413b-f8d4-4e07-af76-27c644bff19c · outbound
Scaling Point-in-Time Language Models Finetuned Language Models Are Zero-Shot Learners
Reference 35
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Observation 5eec8c89-7ded-4ce5-a570-d84249f49c0f · outbound
Scaling Point-in-Time Language Models Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Reference 36
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Observation 9e99ce94-e893-4a5a-9221-65c1ac332435 · outbound
Scaling Point-in-Time Language Models DatedGPT: Preventing Lookahead Bias in Large Language Models with Time-Aware Pretraining
Reference 37
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Observation cbae58dc-14c7-430b-ba38-daaf56ad0918 · outbound
Scaling Point-in-Time Language Models Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge
Reference 38
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Observation 84d408ba-4509-4f6d-b005-2f79998aa2be · outbound
Scaling Point-in-Time Language Models HellaSwag: Can a Machine Really Finish Your Sentence?
Reference 39
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Observation 19bee359-5d2a-4e08-85d9-69e08810bd15 · outbound
Scaling Point-in-Time Language Models LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report
Reference 40
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Observation fd3875b1-f33e-4c95-9cb1-418577fba973 · outbound
Scaling Point-in-Time Language Models Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates
Reference 41
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Observation 32a4545c-bc50-4129-943f-083306887139 · outbound
Scaling Point-in-Time Language Models Instruction-Following Evaluation for Large Language Models
Reference 42
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Observation ce59e45b-da86-4834-964c-c04b5a410923 · outbound
Scaling Point-in-Time Language Models Value Residual Learning
Reference 43
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Observation a020f25c-afe2-4026-a937-d1f8316d3bc8 · outbound
Reference 44
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Observation cd1fbd95-250e-4462-8414-a82160610f38 · outbound
Scaling Point-in-Time Language Models Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,
Reference 1999
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Observation e0b36825-18f0-4136-b9bb-cf79b5e5a7be · outbound
Scaling Point-in-Time Language Models Training Compute-Optimal Large Language Models
Reference 2008
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Observation db6076a0-f5b2-49bf-89e4-fff2dbae6c71 · outbound
Scaling Point-in-Time Language Models Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations
Reference 2018
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Observation 50410378-b1fc-4b6c-b814-488b57fc1a8a · outbound
Scaling Point-in-Time Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Reference 2019
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Observation 4bd0a868-1c11-4661-83df-534d919fd76c · outbound
Scaling Point-in-Time Language Models Multitask Prompted Training Enables Zero-Shot Task Generalization
Reference 2021
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Observation 8a46a709-477f-4666-aea3-e7bf095daf4b · outbound
Scaling Point-in-Time Language Models Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models
Reference 2022
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Observation 7cc9cfde-0496-4cc1-9811-d1c0a82b1012 · outbound
Scaling Point-in-Time Language Models Scaling Instruction-Finetuned Language Models
Reference 2023
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Observation 70fab7eb-bbf5-4f05-a9ed-43bb7b754f71 · outbound
Reference 2024
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Observation 421e9056-0d74-47db-801a-056fae582872 · outbound
Scaling Point-in-Time Language Models Can Large Language Models Be an Alternative to Human Evaluations?
Reference 2025
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Observation 83fc76ca-087f-4985-b418-b84ca836e962 · outbound
Scaling Point-in-Time Language Models Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators
Reference 2026
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No inbound Pith citation observations are available.