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Paper Citation Record · LEDGER

Lossless Compression for LLM Tensor Incremental Snapshots

As of 19 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 2 inbound Pith citation observations for arXiv:2505.09810.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.09810 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:28:02.608611Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T20:16:16.466375Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-13T20:18:13.331054Z

Reference resolution

19 of 19 outbound references displayed

  • verified exact1
  • verified fuzzy4
  • unresolved13
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2c53359b-9943-4aba-a20b-4ef8c7a2d8e0 · outbound

This paper cites Efficient Decoding of Prefix Codes.

Lossless Compression for LLM Tensor Incremental Snapshots Efficient Decoding of Prefix Codes

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:28:03.120179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation e91e9822-d149-4c6a-ae99-968adfa24b14 · outbound

This paper cites an unresolved cited work.

Lossless Compression for LLM Tensor Incremental Snapshots Unresolved cited work

Reference 2

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unresolved
raw_fallback, observed 2026-08-15T21:28:03.107060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 5e0c0561-01d6-437b-8b6b-883da932a694 · outbound

This paper cites Peter Deutsch.

Lossless Compression for LLM Tensor Incremental Snapshots Peter Deutsch

Reference 3

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unresolved
no resolver link, observed 2026-08-15T21:28:02.547603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.547603Z digest=sha256:cabe55a9ce93c023807e5e9450273be570ee418230f03029058b36d1382d7fca

Observation 35bf08b6-0d5e-4ab6-aed2-e9443bcf1672 · outbound

This paper cites Lessons Learned from the Analysis of System Failures at Petascale: The Case of Blue Waters.

Lossless Compression for LLM Tensor Incremental Snapshots Lessons Learned from the Analysis of System Failures at Petascale: The Case of Blue Waters

Reference 4

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verified exact
doi, observed 2026-08-15T21:28:02.654065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation bb0de92d-319c-4c3c-8d32-024986e1fb74 · outbound

This paper cites Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms.

Lossless Compression for LLM Tensor Incremental Snapshots Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:28:03.093837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 4bd19245-148d-4f9a-b550-5bbeb3dfe379 · outbound

This paper cites Failures in large scale systems: long-term measurement, analysis, and implications.

Lossless Compression for LLM Tensor Incremental Snapshots Failures in large scale systems: long-term measurement, analysis, and implications

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T21:28:02.560433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.560433Z digest=sha256:1305bac24f1f2fedcd8aee5275ee00dc2d90280fe2a2225117b6188af31f52cd

Observation 87ca069d-cebd-4307-8eb8-1fa056f14073 · outbound

This paper cites Development of a Lossless Data Compression Algorithm for Multichannel Environmental Monitoring Systems.

Lossless Compression for LLM Tensor Incremental Snapshots Development of a Lossless Data Compression Algorithm for Multichannel Environmental Monitoring Systems

Reference 7

Resolution
malformed identifier
doi_truncated, observed 2026-08-15T21:28:02.977801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 12be063b-11f9-4a9e-a5c5-90054e9d6bf2 · outbound

This paper cites Bfloat16 Processing for Neural Networks.

Lossless Compression for LLM Tensor Incremental Snapshots Bfloat16 Processing for Neural Networks

Reference 8

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unresolved
no resolver link, observed 2026-08-15T21:28:02.568424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation edaea76d-d374-4f12-b6ca-495e907eb16c · outbound

This paper cites Language Models are Few-Shot Learners.

Lossless Compression for LLM Tensor Incremental Snapshots Language Models are Few-Shot Learners

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T21:28:02.572130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.572130Z digest=sha256:98d4e594037e9d3bfd19cdd3e164db34b68b4a18f99edf9a098f597406e16ffb

Observation efec317f-e165-4882-88be-70a475f5b614 · outbound

This paper cites CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery.

Lossless Compression for LLM Tensor Incremental Snapshots CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T21:28:02.575882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.575882Z digest=sha256:d54b9947d79bcaee40ef651368953b08bacfed3c26863c9de69e522661b7488d

Observation b48a83eb-70ad-4680-8764-75cb583c9a78 · outbound

This paper cites CheckFreq: Frequent, Fine-Grained DNN Checkpointing.

Lossless Compression for LLM Tensor Incremental Snapshots CheckFreq: Frequent, Fine-Grained DNN Checkpointing

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:28:03.080426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 08b287bb-8316-46b8-aa60-2fba7de77ad7 · outbound

This paper cites The MultiBERTs: BERT Reproductions for Robustness Analysis.

Lossless Compression for LLM Tensor Incremental Snapshots The MultiBERTs: BERT Reproductions for Robustness Analysis

Reference 12

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unresolved
no resolver link, observed 2026-08-15T21:28:02.583382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.583382Z digest=sha256:c2a3d69cc6cf2bcc1f813f6fcc08e67f0cf99988bb1c93efe0f6ed1a6a338ea5

Observation 6fe92119-caeb-4262-b039-5163b27a66e9 · outbound

This paper cites Check-N-Run: a Checkpointing System for Training Deep Learning Recommendation Models.

Lossless Compression for LLM Tensor Incremental Snapshots Check-N-Run: a Checkpointing System for Training Deep Learning Recommendation Models

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:28:03.067794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:28:02.587377Z digest=sha256:5422e0f16d0bbea8d5d621ce673429bc891399f2428e7b0ec6278ce731183d12

Observation 8e693bd4-686b-48d3-a605-27a25b010faf · outbound

This paper cites Time Series Compression Survey.

Lossless Compression for LLM Tensor Incremental Snapshots Time Series Compression Survey

Reference 14

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unresolved
no resolver link, observed 2026-08-15T21:28:02.590631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.590631Z digest=sha256:371a0c8961caa6639adafd941ee14ce6b1b979188dbaae5fcb24861b9861d310

Observation 240d7538-4a86-4b38-95e3-dbb34412972e · outbound

This paper cites GEMINI: Fast Failure Recovery in Distributed Training with In-Memory Checkpoints.

Lossless Compression for LLM Tensor Incremental Snapshots GEMINI: Fast Failure Recovery in Distributed Training with In-Memory Checkpoints

Reference 15

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unresolved
no resolver link, observed 2026-08-15T21:28:02.594011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.594011Z digest=sha256:8795de81c212bcabc46e0fbe7efe4019a8a4f718fdc36fbedcda71457f395c5a

Observation edd59a78-2237-44ef-bf43-ae3bf0aabdfb · outbound

This paper cites BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

Lossless Compression for LLM Tensor Incremental Snapshots BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 16

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unresolved
no resolver link, observed 2026-08-15T21:28:02.597366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.597366Z digest=sha256:59de1c4dc57a36b71b91bbcf8106c6641d40de8180aa1cfc980aff35e5e410f6

Observation d4feffb2-3cc1-4c96-a634-1f135c0fab26 · outbound

This paper cites FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data.

Lossless Compression for LLM Tensor Incremental Snapshots FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T21:28:02.601205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.601205Z digest=sha256:a72b6d5cfe927f69fd76ac62c550068b43356d68a6c08c886b3153259d1e44e0

Observation a90c7b12-ad66-442e-9279-120d0c445b71 · outbound

This paper cites Lossless and Near-Lossless Compression for Foundation Models.

Lossless Compression for LLM Tensor Incremental Snapshots Lossless and Near-Lossless Compression for Foundation Models

Reference 18

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unresolved
no resolver link, observed 2026-08-15T21:28:02.604797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:28:02.604797Z digest=sha256:270377547a369d249730a4a71959a1d44e2d681a59d76c5bdcbd581752e2fd70

Observation 72c8e21a-0a02-434b-96a6-b9034af4c588 · outbound

This paper cites A Comprehensive Survey of Compression Algorithms for Language Models.

Lossless Compression for LLM Tensor Incremental Snapshots A Comprehensive Survey of Compression Algorithms for Language Models

Reference 19

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unresolved
no resolver link, observed 2026-08-15T21:28:02.608611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

Observation b4430b74-9414-4963-9993-1fa4c30847d7 · inbound

FluxMoE: Decoupling Expert Residency for High-Performance MoE Serving cites this paper.

FluxMoE: Decoupling Expert Residency for High-Performance MoE Serving Lossless Compression for LLM Tensor Incremental Snapshots

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:18:13.333908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-13T20:16:16.466375Z digest=sha256:6bafc8c4a601ee937d05cf2fbbb516ddb5617cf90060c9351d953c40ab911046

Observation 61e9bca2-a7b1-43b8-aff1-7105c49690c4 · inbound

ZipCCL: Efficient Lossless Data Compression of Communication Collectives for Accelerating LLM Training cites this paper.

ZipCCL: Efficient Lossless Data Compression of Communication Collectives for Accelerating LLM Training Lossless Compression for LLM Tensor Incremental Snapshots

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:36:30.620231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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