Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T08:30:57.861433Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2601.16956.
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 2026-08-03T08:30:57.861433Z
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, observed 2026-05-25T05:52:30.402478Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T05:55:24.657761Z
38 of 38 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation d605c9a5-7744-434a-be3f-d4ee79ae7a19 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Towards an AI co-scientist
Reference 1
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Observation 408b28a6-ed92-4010-a027-ecea474b4c25 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Scaling llama 3 training with efficient parallelism strategies,
Reference 2
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Observation 84f44455-5f6d-4334-9f65-ed77f287944e · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers BLOOM: A 176B-Parameter Open-Access Multilingual Language Model,
Reference 3
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Observation a5a9ef2c-86dc-4768-b88c-c86f9ba68e29 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers DeepSpeed: System Optimizations Enable Training Deep Learning Models with Over 100 Billion Parameters,
Reference 4
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Observation 92d54919-66cd-4825-a8e5-b7a6181c66e8 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
Reference 5
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Observation 3fa05e02-df14-4849-bd47-c134ef97c201 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Robust llm training infrastructure at bytedance,
Reference 6
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Unavailable: canonical work link unavailable.
Observation b2aed746-885f-4953-a74d-4220c88282ac · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Unicron: Economizing self-healing llm training at scale,
Reference 7
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Unavailable: canonical work link unavailable.
Observation c63a0b42-d534-471a-9761-203a00acd1b7 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Spike No More: Stabilizing the Pre-training of Large Language Models
Reference 8
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Observation 7fc18c1c-7f90-4ad5-86e0-a9d0a804edd4 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers FastPersist: Accelerating Model Checkpointing in Deep Learning
Reference 9
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Unavailable: canonical work link unavailable.
Observation c9f1de20-8b8f-4fbe-b57d-225d92fc3d7a · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Datastates-llm: Lazy asynchronous checkpointing for large language models,
Reference 10
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Observation 51f573d2-766b-4c3b-add4-9a99b71594b4 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Welcome to the torchsnapshot documentation,
Reference 11
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Unavailable: canonical work link unavailable.
Observation d28926fd-ef96-4cd1-9080-94b2ae94240b · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers CheckFreq: Frequent, Fine-Grained DNN checkpointing,
Reference 12
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Unavailable: canonical work link unavailable.
Observation 82835cb8-493f-4363-8f87-5484abfd7394 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Gemini: Fast failure recovery in distributed training with in-memory checkpoints,
Reference 13
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Unavailable: canonical work link unavailable.
Observation 3c97120e-1d6f-4131-aaff-86f91a5f9f31 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers DeepFreeze: Towards Scalable Asynchronous Checkpointing of Deep Learning Models,
Reference 14
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Unavailable: canonical work link unavailable.
Observation 8215de6d-c59d-4afb-96cb-00aae19ec539 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Reliable and efficient in-memory fault tolerance of large language model pretraining,
Reference 15
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Unavailable: canonical work link unavailable.
Observation ae48085a-f023-4995-a895-81031b58143f · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Optimize Checkpoint Performance for Large Models - Azure Machine Learning,
Reference 16
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Unavailable: canonical work link unavailable.
Observation 06e409a5-02f4-4eb3-8a9a-e9f613a64cea · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Zero- infinity: breaking the gpu memory wall for extreme scale deep learning,
Reference 17
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Unavailable: canonical work link unavailable.
Observation 8f83c0ba-35da-4f22-b9ca-68e46dc9ae71 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Megatron-LM: Training Multi-Billion Parameter Language Mod- els Using Model Parallelism,
Reference 18
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Unavailable: canonical work link unavailable.
Observation 2ae6e332-9d87-40fa-92a3-2d5207d3e625 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers ZeRO: Memory Optimizations Toward Training Trillion Parameter Models,
Reference 19
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Unavailable: canonical work link unavailable.
Observation e8fde21f-36ea-4ae7-a3df-4345f259b720 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Understanding llm checkpoint/restore i/o strategies and patterns,
Reference 20
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Unavailable: canonical work link unavailable.
Observation 413dc35e-aba8-4037-849b-aba4f18523e6 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers A cost-efficient failure-tolerant scheme for distributed dnn training,
Reference 21
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Unavailable: canonical work link unavailable.
Observation 347f7a01-18c5-4cd1-9588-62fd6da8892c · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Transom: An efficient fault-tolerant system for training llms,
Reference 22
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Unavailable: canonical work link unavailable.
Observation 59c1728f-cd2d-446c-83c7-39cad25b5f66 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Berkeley lab checkpoint/restart (blcr) for linux clusters,
Reference 23
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Unavailable: canonical work link unavailable.
Observation 9f7c1e1f-8c4d-400e-a40a-7a66bb9a2c78 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Checuda: A checkpoint/restart tool for cuda applications,
Reference 24
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Unavailable: canonical work link unavailable.
Observation 937fca11-d27c-4518-966f-59980c61fac8 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers VeloC: Towards High Performance Adaptive Asynchronous Check- pointing at Large Scale,
Reference 25
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Unavailable: canonical work link unavailable.
Observation 434eb340-2dce-453b-9863-493b5a62673f · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Towards Efficient Cache Allocation for High-Frequency Checkpointing,
Reference 26
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Unavailable: canonical work link unavailable.
Observation 333af9dc-f4cd-434f-b808-ab0fc767a0a6 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers GPU-Enabled Asynchronous Multi-level Checkpoint Caching and Prefetching,
Reference 27
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Unavailable: canonical work link unavailable.
Observation 1c341511-4424-4445-96bd-507ea5834b8c · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Checkpoint restart support for heterogeneous hpc applications,
Reference 28
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Unavailable: canonical work link unavailable.
Observation c72bbc8a-17ef-427d-bc60-a73dc6a72564 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Adios 2: The adaptable input output system. a framework for high-performance data management,
Reference 29
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Observation e3f0cd8b-0f5c-477d-9128-36a56a691d98 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers An overview of gradient descent optimization algorithms,
Reference 30
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Unavailable: canonical work link unavailable.
Observation 4d951ac7-d575-42a4-9883-708b82301d30 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Adam: A method for stochastic optimization,
Reference 31
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Observation 79ac9fa6-930f-436d-9db4-42135a710bbc · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Mixed Precision Training
Reference 32
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Unavailable: canonical work link unavailable.
Observation f47b20f2-689e-457a-a4d7-222ee2868f08 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Adam: A Method for Stochastic Optimization
Reference 33
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Observation b5726e1c-a469-4c55-9868-aa892988d9a3 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Polaris,
Reference 34
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Observation bffa5578-05b1-4d36-8146-29c46a95ee6b · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Asynccheckpointio– pytorch lightning,
Reference 35
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Observation 9d1dde8f-43cb-4a54-85ed-c1e81e725bc8 · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Llama 2: Open Foundation and Fine-Tuned Chat Models,
Reference 36
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Unavailable: canonical work link unavailable.
Observation 94c7494d-6f77-431b-a8b3-03bfd525090c · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers Lustre: Building a file system for 1000-node clusters,
Reference 37
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Unavailable: canonical work link unavailable.
Observation d4d5a879-a7d5-44bc-b7a3-fe72d6472b1c · outbound
DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers An overview of gradient descent optimization algorithms
Reference 2017
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Observation 62c009ef-6082-45fa-b036-27c0b91d5df8 · inbound
ReCoVer: Resilient LLM Pre-Training System via Fault-Tolerant Collective and Versatile Workload DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 16ac29bb-b626-4a74-95e5-39a9cdfd2880 · inbound
ReCoVer: Resilient LLM Pre-Training System via Fault-Tolerant Collective and Versatile Workload DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.