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Paper Citation Record · LEDGER

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference

As of 14 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2511.21513.

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

pith.paper-citation-record.v1
2511.21513 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T20:02:51.284788Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved36
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 86852760-e6b4-4c0b-83a4-da9595acb95b · outbound

This paper cites write newline.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference write newline

Reference 1

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source=arxiv_source observed=2026-08-03T20:02:51.144056Z digest=sha256:b7fe75a30a73e0198fdb9f90db88656bb98bdcf6ac48132e90118e7760931a49

Observation c84ccaf8-56b2-449b-9ed2-791b10123512 · outbound

This paper cites L., Gao, J., and Choi, Y.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference L., Gao, J., and Choi, Y

Reference 2

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source=arxiv_source observed=2026-08-03T20:02:51.149256Z digest=sha256:35b6bfc43e97ced556ae9a3beb68accb865c7a9d9f9c2bdbda6912b9fd5cf533

Observation 04d8b239-edb1-45a7-93a9-4933487bdb46 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 3

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source=arxiv_source observed=2026-08-03T20:02:51.153441Z digest=sha256:22240dc2ad1691e7b771cb75bc653bc123c42e415f1243b38c5d80b1407e7893

Observation 4ce46f9b-7c26-4653-a9ce-1ead9397e79c · outbound

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

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Flashattention: Fast and memory-efficient exact attention with io-awareness

Reference 4

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source=arxiv_source observed=2026-08-03T20:02:51.159821Z digest=sha256:95be1ca498e068e49494cdb4fd49879cfe67288b4501186c2ede7870e9a56dbd

Observation be61cde2-7148-43ed-b3f4-e3c9734f2986 · outbound

This paper cites Y., Ermon, S., Rudra, A., and Re, C.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Y., Ermon, S., Rudra, A., and Re, C

Reference 5

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source=arxiv_source observed=2026-08-03T20:02:51.164046Z digest=sha256:701a4cfcb9887652d3bbb596f62101c289f4a22674c71ad91339e0773c26ff33

Observation 54c859e9-edfa-4d98-a32f-1e93c536ea84 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Imagenet: A large-scale hierarchical image database

Reference 6

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source=arxiv_source observed=2026-08-03T20:02:51.167968Z digest=sha256:01eee37a719740e4619da20e867c6073e1bbe3920ebb9cc0feac75995ad89248

Observation cbd33151-75e6-41b0-881a-0028331e0d46 · outbound

This paper cites an unresolved cited work.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Unresolved cited work

Reference 7

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source=arxiv_source observed=2026-08-03T20:02:51.171927Z digest=sha256:c733d95a641c3c85bc624319d43743ad940c4a73ed32b0b7c213fe1b97c38f9b

Observation 11d39b75-9549-4535-8010-80b555a9d741 · outbound

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

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference An image is worth 16x16 words: Transformers for image recognition at scale

Reference 8

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source=arxiv_source observed=2026-08-03T20:02:51.176027Z digest=sha256:5d0069a303cc22ca04b811c68f1528c2d0d2218ff596f2ee65c8a32ad390492f

Observation 1217367b-54de-4bc3-b6f2-95bc54fbb18a · outbound

This paper cites The Llama 3 Herd of Models.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference The Llama 3 Herd of Models

Reference 9

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source=arxiv_source observed=2026-08-03T20:02:51.179705Z digest=sha256:d63eee0ffe761f5f131774c20d2ffc9c4f48db3aaaa58954374b4dd6a0ad6f8f

Observation 329a9d90-5a8b-47e9-a247-d34504187587 · outbound

This paper cites The language model evaluation harness, 07 2024.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference The language model evaluation harness, 07 2024

Reference 10

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source=arxiv_source observed=2026-08-03T20:02:51.183865Z digest=sha256:f95b33ad2bf50e2e7c702acf5f3cfbb01871a1a6e6ea8a1c02c22d8aa086a8a6

Observation 490beeb3-ca10-49cc-9299-4a0cf099750c · outbound

This paper cites I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models

Reference 11

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Observation 046de272-849a-4d1c-93c4-c85676288ec8 · outbound

This paper cites Quantization and training of neural networks for efficient integer-arithmetic-only inference.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Quantization and training of neural networks for efficient integer-arithmetic-only inference

Reference 12

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source=arxiv_source observed=2026-08-03T20:02:51.191737Z digest=sha256:b72fd0901089dc362493bfa02da393c98b16d675056c098615559b24654afe9d

Observation fee7d037-74f3-49dc-bd2c-2b18d370faeb · outbound

This paper cites Turboattention: Efficient attention approximation for high throughputs llm.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Turboattention: Efficient attention approximation for high throughputs llm

Reference 13

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Observation 9c088b77-6c98-458b-82e0-6f27a42b93aa · outbound

This paper cites W., and Keutzer, K.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference W., and Keutzer, K

Reference 14

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Observation 4a2fe4d2-4b8c-4993-b511-f0e0c2983514 · outbound

This paper cites H., Gonzalez, J., Zhang, H., and Stoica, I.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference H., Gonzalez, J., Zhang, H., and Stoica, I

Reference 15

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Observation 061d8ef5-b739-4585-9845-5e05d9f8d27f · outbound

This paper cites Questa: Expanding reasoning capacity in llms via question augmentation.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Questa: Expanding reasoning capacity in llms via question augmentation

Reference 16

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Observation e7e1fb80-df5c-40a3-855c-12c2083e7513 · outbound

This paper cites and Gu, Q.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference and Gu, Q

Reference 17

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Observation dc5c4fc5-b139-4946-9b6a-4fc184816359 · outbound

This paper cites Consmax: Hardware-friendly alternative softmax with learnable parameters.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Consmax: Hardware-friendly alternative softmax with learnable parameters

Reference 18

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Observation 1154984f-4196-4ba9-b3c5-99a46332378e · outbound

This paper cites Pointer sentinel mixture models.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Pointer sentinel mixture models

Reference 19

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Observation b8073b15-6f0c-4c36-9673-a62c7e0c72b1 · outbound

This paper cites FP8 Formats for Deep Learning.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference FP8 Formats for Deep Learning

Reference 20

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Observation 37879aaf-3a60-4857-83f5-e0033daa9c60 · outbound

This paper cites The lambada dataset: Word prediction requiring a broad discourse context.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference The lambada dataset: Word prediction requiring a broad discourse context

Reference 21

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Observation 7b40a9c0-21b8-4794-bf82-33e59adf9d98 · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 22

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Observation d39db26a-dfb7-47b5-8dac-aa3cb966c3d9 · outbound

This paper cites L., Bhagavatula, C., and Choi, Y.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference L., Bhagavatula, C., and Choi, Y

Reference 23

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Observation bc988903-3d45-44cc-b5ef-ff315387ccb5 · outbound

This paper cites Flashattention-3: Fast and accurate attention with asynchrony and low-precision.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Flashattention-3: Fast and accurate attention with asynchrony and low-precision

Reference 24

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Observation c155ce13-584e-4da4-99f6-0bd270080904 · outbound

This paper cites an unresolved cited work.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Unresolved cited work

Reference 25

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Observation 52522623-20b6-4e82-a730-dc9ec9db5af8 · outbound

This paper cites R., Venkatesan, R., Dai, S., Khailany, B., and Raghunathan, A.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference R., Venkatesan, R., Dai, S., Khailany, B., and Raghunathan, A

Reference 26

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Observation f6d2b996-cdaf-44f6-9074-c3b7feb18445 · outbound

This paper cites Gemma 3 Technical Report.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Gemma 3 Technical Report

Reference 27

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source=arxiv_source observed=2026-08-03T20:02:51.248806Z digest=sha256:efce3cf98ba5cda561a19bc878c764aed45aea82e920d5bca498a6ae51a0040f

Observation f4d503c4-8374-47d4-940a-4519a3de6204 · outbound

This paper cites Training data-efficient image transformers & distillation through attention.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Training data-efficient image transformers & distillation through attention

Reference 28

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source=arxiv_source observed=2026-08-03T20:02:51.253229Z digest=sha256:a1176732a59dc1768f0c42ca147303e1405ff64a56bbbaff5666bfe385863101

Observation 2aabb028-e852-421f-8605-c1ce97d34e8c · outbound

This paper cites Going deeper with image transformers.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Going deeper with image transformers

Reference 29

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Observation 29b32b43-b3ec-469e-ad7d-c65424e52ed8 · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference N., Kaiser, ., and Polosukhin, I

Reference 30

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Observation 41b793be-d5ad-41c0-9a70-154b598a8100 · outbound

This paper cites Qwen3 Technical Report.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Qwen3 Technical Report

Reference 31

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Observation 5e58f2ae-53eb-455e-8da7-0c092b5a2c8c · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019

Reference 32

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Observation 5afe1b56-e159-4104-9da2-3a16cfa21c26 · outbound

This paper cites Sageattention2: Efficient attention with thorough outlier smoothing and per-thread int4 quantization.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Sageattention2: Efficient attention with thorough outlier smoothing and per-thread int4 quantization

Reference 33

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source=arxiv_source observed=2026-08-03T20:02:51.272636Z digest=sha256:ae5a7f72a608307286b646ad98b0c0813fbe0c45caa57bebe358211d619c0827

Observation 025b1bed-e5e5-43fb-9bd6-1303e4503a2f · outbound

This paper cites Sageattention3: Microscaling FP 4 attention for inference and an exploration of 8-bit training.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Sageattention3: Microscaling FP 4 attention for inference and an exploration of 8-bit training

Reference 34

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source=arxiv_source observed=2026-08-03T20:02:51.276270Z digest=sha256:0839c4d2c891e58779d532675992e0de0973a82d0d47f6575a3a5dd3c1d85001

Observation c5759337-4c36-486b-b963-7d639996dd2e · outbound

This paper cites Sageattention: Accurate 8-bit attention for plug-and-play inference acceleration.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Sageattention: Accurate 8-bit attention for plug-and-play inference acceleration

Reference 35

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Observation f0058924-423b-40c9-a6e8-8e7fcb9c5e2d · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference OPT: Open Pre-trained Transformer Language Models

Reference 36

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Pith citing papers

No inbound Pith citation observations are available.