Paper Citation Record · LEDGER

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers

As of 21 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 2 inbound Pith citation observations for arXiv:2507.16676.

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

pith.paper-citation-record.v1
2507.16676 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:11:14.757058Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T04:14:11.793614Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:06:24.646981Z

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy21
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1726cef6-75a7-4ce1-837c-824687e063c7 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.258961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4da5dd94-c367-4018-ba04-582409e69339 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers LLaMA: Open and Efficient Foundation Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:12.939944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1afa995-413d-4e94-b78c-a71235cd3281 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.241717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 20d921e8-6919-4c0d-9d9e-0a0a27c4412e · outbound

This paper cites Attention is all you need,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Attention is all you need,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:13.029505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a09977e7-0f39-4512-bbe8-e4077bc9fbe9 · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers BERT: Pre-training of deep bidirectional transformers for language understanding,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.213824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2a891ef4-de55-4400-92cc-4e2116c50824 · outbound

This paper cites ALBERT: A lite bert for self-supervised learning of language represen- tations,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers ALBERT: A lite bert for self-supervised learning of language represen- tations,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.195794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1537dfb6-9156-4d47-bb92-c1090cd701a8 · outbound

This paper cites Longformer: The Long-Document Transformer.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Longformer: The Long-Document Transformer

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:13.311438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67ea9787-9010-4110-b306-2a138b8e6fe1 · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Generating Long Sequences with Sparse Transformers

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:13.465021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3642d0b-c345-4a11-bca0-c8daf9967d3b · outbound

This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Transformers are rnns: Fast autoregressive transformers with linear attention,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.174047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2b1bdcbb-ad84-4906-8dea-3dd5314f9036 · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Linformer: Self-Attention with Linear Complexity

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:13.710772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2a02d83-144b-4fc3-805c-e5fa7ff7d6b0 · outbound

This paper cites Flashattention: Fast and memory-efficient exact attention with IO-awareness,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Flashattention: Fast and memory-efficient exact attention with IO-awareness,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.159661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 224d45e6-ed93-4230-ba39-554804dfef5c · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:13.979517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 638ae11d-b20d-40e9-b01c-805952011d9b · outbound

This paper cites Self-attention Does Not Need $O(n^2)$ Memory.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Self-attention Does Not Need $O(n^2)$ Memory

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:14.081783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f871cac0-fd3d-409c-915f-bb332ca2a661 · outbound

This paper cites Testability and dependability of ai hardware: Survey, trends, challenges, and perspectives,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Testability and dependability of ai hardware: Survey, trends, challenges, and perspectives,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.146191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 71bc6a85-2426-4b23-83df-16ba079075cb · outbound

This paper cites Radiation-induced soft errors in advanced semiconductor technologies,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Radiation-induced soft errors in advanced semiconductor technologies,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.133086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7ca68cc3-8aee-44dc-b5f6-ffa33f6aa9dc · outbound

This paper cites Designing reliable systems from unreliable components: the challenges of transistor variability and degradation,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Designing reliable systems from unreliable components: the challenges of transistor variability and degradation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.118044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ee666352-902a-450a-bdd1-06b1f0d9933f · outbound

This paper cites Koren and C.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Koren and C

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.103951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0cbad548-a087-4880-8e34-edd838c1435d · outbound

This paper cites Algorithm-based fault tolerance for matrix operations,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Algorithm-based fault tolerance for matrix operations,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.089713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7bb21ce6-8621-46fb-a2d0-12c872287a08 · outbound

This paper cites Towards practical algorithm based fault tolerance in dense linear algebra,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Towards practical algorithm based fault tolerance in dense linear algebra,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.074743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e996bb4f-9dc7-4655-bc83-9b40101f8eac · outbound

This paper cites Low-cost online convolution checksum checker,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Low-cost online convolution checksum checker,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.059694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 36c45af1-b32d-4f3d-a4bb-903cd44c9458 · outbound

This paper cites Making convolutions resilient via algorithm-based error detection techniques,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Making convolutions resilient via algorithm-based error detection techniques,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.046116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 191a8307-dc79-4808-9aa7-2b79db652095 · outbound

This paper cites GCN-ABFT: Low-cost online error checking for graph convolutional networks,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers GCN-ABFT: Low-cost online error checking for graph convolutional networks,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.032332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cd30ca60-d1c9-4606-802d-66762c458f80 · outbound

This paper cites ApproxABFT: Approximate Algorithm-Based Fault Tolerance for Neural Network Processing.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers ApproxABFT: Approximate Algorithm-Based Fault Tolerance for Neural Network Processing

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:14.722039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8023e98d-5b9e-4789-aca6-5a691cffcec9 · outbound

This paper cites ATTNChecker: Highly-optimized fault tolerant attention for large language model train- ing,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers ATTNChecker: Highly-optimized fault tolerant attention for large language model train- ing,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:15.017561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5d8a004a-ae2c-4111-9990-a4fac118f290 · outbound

This paper cites Error resilient transformers: A novel soft error vulnerability guided approach to error checking and suppression,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Error resilient transformers: A novel soft error vulnerability guided approach to error checking and suppression,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:14.998636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation aa88b97b-615f-45d0-9b79-48bd054a1690 · outbound

This paper cites Language models are unsupervised multitask learn- ers,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Language models are unsupervised multitask learn- ers,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:14.983410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 11c98e64-7fa8-4204-b16c-3efb622cb0ab · outbound

This paper cites Attention is all you need,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Attention is all you need,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:14.969704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d201a12b-bd95-42cb-ba83-5c45b9d0acbc · outbound

This paper cites Mnnfast: a fast and scalable system architecture for memory-augmented neural networks,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Mnnfast: a fast and scalable system architecture for memory-augmented neural networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:14.955836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7d34483d-868d-4fac-a524-80541c150029 · outbound

This paper cites Online normalizer calculation for softmax.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Online normalizer calculation for softmax

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:14.746427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b25e2d2f-7a4a-4b63-a6d5-3c82c9e06d6b · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T15:11:14.752400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8973ae6c-3569-4362-b91e-d8841794b4e3 · outbound

This paper cites Automatic detection of floating- point exceptions,.

Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers Automatic detection of floating- point exceptions,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:11:14.940425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 5ada3721-6945-4e6a-a34f-318d1719c932 · inbound

Not All Errors Are Equal: A Systematic Study of Error Propagation in Large Language Model Inference cites this paper.

Not All Errors Are Equal: A Systematic Study of Error Propagation in Large Language Model Inference Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers

Reference 80

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:06:24.648870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6658f018-4ac8-44a5-ac88-3c0f9c2152f5 · inbound

Self-Verifying Measurement Records: Hash-Linked Evidence Graphs for Hardware Benchmarking cites this paper.

Self-Verifying Measurement Records: Hash-Linked Evidence Graphs for Hardware Benchmarking Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-01T17:05:50.955968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.