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Paper Citation Record · LEDGER

Compute Requirements for Algorithmic Innovation in Frontier AI Models

As of 19 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 1 inbound Pith citation observation for arXiv:2507.10618.

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

pith.paper-citation-record.v1
2507.10618 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:52:50.798959Z

measured 62 of 62 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T11:04:06.709639Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved37
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f69a9172-d663-48b3-a565-bfe80254bfc2 · outbound

This paper cites write newline.

Compute Requirements for Algorithmic Innovation in Frontier AI Models write newline

Reference 1

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source=arxiv_source observed=2026-08-06T17:52:50.166870Z digest=sha256:16df5a4fe6d0e693ed907861636ebd13ba372cd7f3dbea008f24a94b333e0975

Observation c305ddff-6da6-4a5d-ab32-b8602446b4ea · outbound

This paper cites Keep the Future Human: Why and How We Should Close the Gates to AGI and Superintelligence, and What We Should Build Instead.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Keep the Future Human: Why and How We Should Close the Gates to AGI and Superintelligence, and What We Should Build Instead

Reference 2

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source=arxiv_source observed=2026-08-06T17:52:50.176240Z digest=sha256:9f474d08ba67927c9af6b0fdee169b3d0efc10bfec4ae68027e624da639b6157

Observation d6dc3a6a-fbcd-4f24-bce8-82a034c30d40 · outbound

This paper cites d., Zemlyanskiy, Y., Lebron, F., and Sanghai, S.

Compute Requirements for Algorithmic Innovation in Frontier AI Models d., Zemlyanskiy, Y., Lebron, F., and Sanghai, S

Reference 3

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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 f721723a-5b41-490c-945f-15ee9eb3f56e · outbound

This paper cites Singe: leveraging warp specialization for high performance on GPUs.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Singe: leveraging warp specialization for high performance on GPUs

Reference 4

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source=arxiv_source observed=2026-08-06T17:52:50.195116Z digest=sha256:f0520dec8d8a6bdc2eb888f7005d077bb05bb509bb2c36e3d945210093d95bdd

Observation f5d8c39d-7c79-4d93-bd95-c6f69a639ac3 · outbound

This paper cites Efficient Training of Language Models to Fill in the Middle.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Efficient Training of Language Models to Fill in the Middle

Reference 5

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source=arxiv_source observed=2026-08-06T17:52:50.205358Z digest=sha256:6daba2804b7fef4ac673cf6fe52bb86752964353b4848934962f66b5f309a874

Observation 1dc6f337-8d56-4551-bb60-06fbabc6a2b2 · outbound

This paper cites and Aarne, O.

Compute Requirements for Algorithmic Innovation in Frontier AI Models and Aarne, O

Reference 6

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Observation 719b0000-6b6f-417a-b092-9fc69b516320 · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

Compute Requirements for Algorithmic Innovation in Frontier AI Models DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 7

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source=arxiv_source observed=2026-08-06T17:52:50.222545Z digest=sha256:12d9858aff1d1b1ba2dc27256358d3f4b1312b020a82c7909aec75cd85131c1c

Observation ff819399-79ba-46d1-9d9f-9a8e93c0fcad · outbound

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

Compute Requirements for Algorithmic Innovation in Frontier AI Models Y., Ermon, S., Rudra, A., and Ré, C

Reference 8

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Observation ccf5aff4-cd22-4ee0-84a7-531d541564d2 · outbound

This paper cites AI capabilities can be significantly improved without expensive retraining.

Compute Requirements for Algorithmic Innovation in Frontier AI Models AI capabilities can be significantly improved without expensive retraining

Reference 9

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source=arxiv_source observed=2026-08-06T17:52:50.240992Z digest=sha256:77c132e4e27fdc51c0eefa656b735bd26f0aba1f00b30cf7c8d3967328a64e83

Observation 5cfba068-da66-49e2-8e5a-d27aa0780433 · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

Compute Requirements for Algorithmic Innovation in Frontier AI Models DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 10

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Observation 4a20838f-463c-4426-9131-4dc3232d29c5 · outbound

This paper cites LLM .int8(): 8-bit matrix multiplication for transformers at scale.

Compute Requirements for Algorithmic Innovation in Frontier AI Models LLM .int8(): 8-bit matrix multiplication for transformers at scale

Reference 11

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

source=arxiv_source observed=2026-08-06T17:52:50.257459Z digest=sha256:193798225f8145ae1e5aeca1228e56c2d5e324c44b4877b3b27a0df3e1b5f02d

Observation 719527bf-0822-43b7-ac90-8e208eac7646 · outbound

This paper cites DiLoCo: Distributed Low-Communication Training of Language Models.

Compute Requirements for Algorithmic Innovation in Frontier AI Models DiLoCo: Distributed Low-Communication Training of Language Models

Reference 12

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source=arxiv_source observed=2026-08-06T17:52:50.265538Z digest=sha256:da75c912ef047419370c6e05f0d7ff9385b29a13893c7485bc9bbf37b7bc415e

Observation 791c26f8-3758-47e5-9ac6-097a147c4c08 · outbound

This paper cites Data on machine learning hardware”, 10 2024 a.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Data on machine learning hardware”, 10 2024 a

Reference 13

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

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Observation 8a92075b-a35b-4bc6-8740-5dcaa71cdfc0 · outbound

This paper cites Data on notable ai models, 6 2024 b.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Data on notable ai models, 6 2024 b

Reference 14

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

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Observation 57512f90-59f4-4a18-853c-26f7737777c8 · outbound

This paper cites Y., Rozière, B., Lopez-Paz, D., and Synnaeve, G.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Y., Rozière, B., Lopez-Paz, D., and Synnaeve, G

Reference 15

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

source=arxiv_source observed=2026-08-06T17:52:50.291184Z digest=sha256:3368832221841e82fd23a649d07adbaf54df5b0870a3e25fd9738c035f07b4f4

Observation c05fc0aa-a08e-4158-8370-5129f4a950e5 · outbound

This paper cites The llama 3 herd of models, 2024.

Compute Requirements for Algorithmic Innovation in Frontier AI Models The llama 3 herd of models, 2024

Reference 16

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

source=arxiv_source observed=2026-08-06T17:52:50.300059Z digest=sha256:040d51d1c4d0162667cd0d5a68a9bef766dc9016e34a4c4a0272d1f3daba52b0

Observation 1abf9a50-f661-4232-83f2-f7ee662dfbca · outbound

This paper cites OLMo: Accelerating the Science of Language Models.

Compute Requirements for Algorithmic Innovation in Frontier AI Models OLMo: Accelerating the Science of Language Models

Reference 17

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source=arxiv_source observed=2026-08-06T17:52:50.309178Z digest=sha256:7c0292352331633f9227c53aff4ed162035c17ff08b83026434dee83ac3ed8ee

Observation d8ff9c9d-7180-4c3c-ad36-fd7448f3b024 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Compute Requirements for Algorithmic Innovation in Frontier AI Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 18

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source=arxiv_source observed=2026-08-06T17:52:50.316958Z digest=sha256:3faa06f207207c88915ef71cfe6b901a49ae56aefce85bac52696bb806fb6b29

Observation db65259c-1453-413a-ac3d-060312d30a94 · outbound

This paper cites Training Compute Thresholds: Features and Functions in AI Regulation.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Training Compute Thresholds: Features and Functions in AI Regulation

Reference 19

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Observation 1da85014-507c-4906-a44b-3e80fc7791d7 · outbound

This paper cites Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation

Reference 20

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source=arxiv_source observed=2026-08-06T17:52:50.335079Z digest=sha256:c0a26b99668d31df5bec5ac39f969769ae2efe9e463186a5bcee7d80e6829225

Observation 3d1c3aab-0e5e-4648-926c-6264bba90a94 · outbound

This paper cites C., Atkinson, D., Thompson, N., and Sevilla, J.

Compute Requirements for Algorithmic Innovation in Frontier AI Models C., Atkinson, D., Thompson, N., and Sevilla, J

Reference 21

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source=arxiv_source observed=2026-08-06T17:52:50.341994Z digest=sha256:2dcff6a6642378422e57b4d5270cbe690a7d8776f55319c8b35597de3acfaf78

Observation 42364564-f950-4926-8fa2-a5b69a4df9f8 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Training Compute-Optimal Large Language Models

Reference 22

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source=arxiv_source observed=2026-08-06T17:52:50.351042Z digest=sha256:e79bd5a253c516116b1139b7b0589b4dabb7b912c161dbb32a4a5770c8451c35

Observation 99f13ff3-60f1-4ef3-bd76-0e8884c2e7c1 · outbound

This paper cites X., Chen, D., Lee, H., Ngiam, J., Le, Q.

Compute Requirements for Algorithmic Innovation in Frontier AI Models X., Chen, D., Lee, H., Ngiam, J., Le, Q

Reference 23

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Observation abbd5c08-f795-45d7-ac53-55422ecfc97f · outbound

This paper cites OpenAI o1 System Card.

Compute Requirements for Algorithmic Innovation in Frontier AI Models OpenAI o1 System Card

Reference 24

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source=arxiv_source observed=2026-08-06T17:52:50.370167Z digest=sha256:290aecbaf3be4cdb1d0f6fd15b63917a5212d9d74dc491053c15383b76985d23

Observation 6fd544a5-b38c-48c9-acec-fb8161a9432c · outbound

This paper cites INTELLECT-1 Technical Report.

Compute Requirements for Algorithmic Innovation in Frontier AI Models INTELLECT-1 Technical Report

Reference 25

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source=arxiv_source observed=2026-08-06T17:52:50.376961Z digest=sha256:fc690cbf79ee28cdb96222164b634479f8443742c0418a304d944eed658ed9e0

Observation e5a4203a-e4bb-4b07-a65c-2cd1d0b278e5 · outbound

This paper cites A., Casper, J., Lym, S., McAfee, L., Andersch, M., Shoeybi, M., and Catanzaro, B.

Compute Requirements for Algorithmic Innovation in Frontier AI Models A., Casper, J., Lym, S., McAfee, L., Andersch, M., Shoeybi, M., and Catanzaro, B

Reference 26

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Observation f3b1e7a6-34a1-4262-92a2-1bf319440393 · outbound

This paper cites and Richardson, J.

Compute Requirements for Algorithmic Innovation in Frontier AI Models and Richardson, J

Reference 27

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source=arxiv_source observed=2026-08-06T17:52:50.394582Z digest=sha256:752b02d3f422ea29d048a6cc8b599a38eebd4bc62546f24f08d699c9b125d0bd

Observation 89ce5661-ef05-4d88-912f-41043ec817b3 · outbound

This paper cites an unresolved cited work.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Unresolved cited work

Reference 28

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source=arxiv_source observed=2026-08-06T17:52:50.403601Z digest=sha256:331bb5f595d4c7b8f006d9f7c88f5865ff35701360bcca28ce645d965bce9d6e

Observation a567dbfd-b4cf-4dad-b443-62089bfd678f · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 29

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source=arxiv_source observed=2026-08-06T17:52:50.412315Z digest=sha256:c17904cb2b345dd67e91c5494f367fa1e6e6e8b9229ad986381ce108e951784f

Observation 5dfb8932-f712-4074-870c-aee3c2c76947 · outbound

This paper cites Breadth- First Pipeline Parallelism.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Breadth- First Pipeline Parallelism

Reference 30

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raw_fallback, observed 2026-08-06T17:52:51.708368Z

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

source=arxiv_source observed=2026-08-06T17:52:50.425421Z digest=sha256:13773a7bc15b09dd2f2167cc6a5077eab30c4a4308674fd8962d2a9bc48d0488

Observation c3f4d42b-6e93-4831-a992-d294155eb37e · outbound

This paper cites Y., Bansal, H., Guha, E., Keh, S.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Y., Bansal, H., Guha, E., Keh, S

Reference 31

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source=arxiv_source observed=2026-08-06T17:52:50.436796Z digest=sha256:9fa2e82ca144a297bad80ad6b7ee3ffa3ca5d2fd808ff822cef4b4f4eda4a7a1

Observation 88d4c21f-7482-4fcc-8d7a-fc3df3933a6a · outbound

This paper cites DeepSeek - V2 : A Strong , Economical , and Efficient Mixture -of- Experts Language Model , 2024 a.

Compute Requirements for Algorithmic Innovation in Frontier AI Models DeepSeek - V2 : A Strong , Economical , and Efficient Mixture -of- Experts Language Model , 2024 a

Reference 32

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raw_fallback, observed 2026-08-06T17:52:51.651652Z

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

source=arxiv_source observed=2026-08-06T17:52:50.445363Z digest=sha256:47aef030323f0e35b97cedf15aec1fee8b0cf913a4e6ffb7adfa47b3ee3397e3

Observation a231fb33-0500-4644-a31c-6828beb2a539 · outbound

This paper cites DeepSeek-V3 Technical Report , 2024 b.

Compute Requirements for Algorithmic Innovation in Frontier AI Models DeepSeek-V3 Technical Report , 2024 b

Reference 33

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

source=arxiv_source observed=2026-08-06T17:52:50.461792Z digest=sha256:0d9a512b4808948f536b13e5a22b9e087cf9a1fce300256a737ccb19ed31c0ef

Observation 169dd436-8c5e-4c78-89ef-3d3a6c658dcc · outbound

This paper cites RingAttention with Blockwise Transformers for Near - Infinite Context.

Compute Requirements for Algorithmic Innovation in Frontier AI Models RingAttention with Blockwise Transformers for Near - Infinite Context

Reference 34

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

source=arxiv_source observed=2026-08-06T17:52:50.472316Z digest=sha256:5c73f0e02b830c1dddf1ee8e624f4aeb353ae33b33bd56e830958fb672f874dc

Observation 9ec8f71e-88c0-4c41-885b-850e94f8bd57 · outbound

This paper cites and Hutter, F.

Compute Requirements for Algorithmic Innovation in Frontier AI Models and Hutter, F

Reference 35

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

source=arxiv_source observed=2026-08-06T17:52:50.483874Z digest=sha256:c24ff5406946850f97ede2464c85f6d52086f3ff196347e422e276fdda149896

Observation c20235db-a039-4655-995f-4d30b62fcac9 · outbound

This paper cites A Narrow Path , December 2024.

Compute Requirements for Algorithmic Innovation in Frontier AI Models A Narrow Path , December 2024

Reference 36

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source=arxiv_source observed=2026-08-06T17:52:50.495250Z digest=sha256:0b3439f800b9906b1dda9cce826cff8795a204721c1f1c4529d4a255e4891083

Observation 32f6c21a-cbc1-4442-97e5-a9de43da17e3 · outbound

This paper cites Efficient large-scale language model training on GPU clusters using megatron- LM.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Efficient large-scale language model training on GPU clusters using megatron- LM

Reference 37

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source=arxiv_source observed=2026-08-06T17:52:50.507043Z digest=sha256:db66fe8b680120df950c79308d7b72ae1a563bfce94384d0ffcc7711ca7d2022

Observation 4ef54b01-a8f3-417a-9951-9496e28b20a6 · outbound

This paper cites 8-bit Numerical Formats for Deep Neural Networks.

Compute Requirements for Algorithmic Innovation in Frontier AI Models 8-bit Numerical Formats for Deep Neural Networks

Reference 38

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source=arxiv_source observed=2026-08-06T17:52:50.520117Z digest=sha256:f649a2a3dd5931fce19339cd0781c74f9b547b121791c68dc885ec785db8ef7c

Observation 96c23c3a-279b-4e92-bae0-f37dcaeb5e94 · outbound

This paper cites 2 OLMo 2 Furious.

Compute Requirements for Algorithmic Innovation in Frontier AI Models 2 OLMo 2 Furious

Reference 39

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source=arxiv_source observed=2026-08-06T17:52:50.536159Z digest=sha256:174ec1e9d0ce123aacc92c7a35d358dd5802f37d8dafe5e7f539f29a2ec49827

Observation 274f74bb-7a5c-4c68-8e5e-0ced52b97744 · outbound

This paper cites Training language models to follow instructions with human feedback.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Training language models to follow instructions with human feedback

Reference 40

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source=arxiv_source observed=2026-08-06T17:52:50.545948Z digest=sha256:a7e96ab47bcd7dc50da6c42ca1d71ce9f13f2eb6286fc8998303e9355c6dc15f

Observation 4e004260-9480-4950-98a4-5d9a0ca18c8b · outbound

This paper cites FP8-LM: Training FP8 Large Language Models.

Compute Requirements for Algorithmic Innovation in Frontier AI Models FP8-LM: Training FP8 Large Language Models

Reference 41

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source=arxiv_source observed=2026-08-06T17:52:50.556519Z digest=sha256:44273f953fe27a72a87828a78065b8355df5e02ba94a3477e0c1525af72898e4

Observation 07d171ca-037e-48f1-bb9a-caee20574c4c · outbound

This paper cites Interim report: Mechanisms for flexible hardware-enabled guarantees.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Interim report: Mechanisms for flexible hardware-enabled guarantees

Reference 42

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source=arxiv_source observed=2026-08-06T17:52:50.567202Z digest=sha256:85c3cf81965c4818512c8703bed2d29b36745ce9f97c12ad70b7ae768b92368e

Observation ca69206e-a668-4bb2-9a07-da97a6c67d5b · outbound

This paper cites Zero Bubble ( Almost ) Pipeline Parallelism.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Zero Bubble ( Almost ) Pipeline Parallelism

Reference 43

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raw_fallback, observed 2026-08-06T17:52:51.529717Z

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

source=arxiv_source observed=2026-08-06T17:52:50.578212Z digest=sha256:a76b108b174f8a18f6429ab45c602535698f698d94f192d4636a186e655e1999

Observation 143b9edd-ac9c-4167-895d-b94549fb2c2a · outbound

This paper cites an unresolved cited work.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Unresolved cited work

Reference 44

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source=arxiv_source observed=2026-08-06T17:52:50.589967Z digest=sha256:3adb6ffa6a22b92586a308f58d34fc25c4d21326b70eb12e0f09db45229a629f

Observation 0d7c284c-e6b5-4f87-8d59-71be33809431 · outbound

This paper cites ZeRO : memory optimizations toward training trillion parameter models.

Compute Requirements for Algorithmic Innovation in Frontier AI Models ZeRO : memory optimizations toward training trillion parameter models

Reference 45

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raw_fallback, observed 2026-08-06T17:52:51.477580Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T17:52:50.602644Z digest=sha256:8c783ad1e52f2fb89e72b1680c8646fd0c0ee752a6d4c9e664a0451ec044029d

Observation 3e9c890e-d1b4-4d87-b305-89413aa8e87d · outbound

This paper cites Y., Ruwase, O., Yang, S., Zhang, M., Li, D., and He, Y.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Y., Ruwase, O., Yang, S., Zhang, M., Li, D., and He, Y

Reference 46

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raw_fallback, observed 2026-08-06T17:52:51.448105Z

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source=arxiv_source observed=2026-08-06T17:52:50.613676Z digest=sha256:455ab7c89b51321b1f0790262d75abb3e2af06b420c89adece28c4ca1ba199fe

Observation 7f7f17ce-2477-44f5-9ab0-727640d7fbab · outbound

This paper cites Computing Power and the Governance of Artificial Intelligence.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Computing Power and the Governance of Artificial Intelligence

Reference 47

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source=arxiv_source observed=2026-08-06T17:52:50.625602Z digest=sha256:4476418a92600d86543c765c055501c77893c43c435fe1b0b49a6951ed849252

Observation 0e0ba793-9521-4dfd-8f35-a3ecb8986113 · outbound

This paper cites and Thiergart, L.

Compute Requirements for Algorithmic Innovation in Frontier AI Models and Thiergart, L

Reference 48

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source=arxiv_source observed=2026-08-06T17:52:50.641809Z digest=sha256:65999008fbb0a58b810d027a05e38ad5b629198d92ef5311db96ed8e94780fe9

Observation ff1cae84-90b3-48ac-91d8-ec2eedec2f15 · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Neural Machine Translation of Rare Words with Subword Units

Reference 49

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source=arxiv_source observed=2026-08-06T17:52:50.652157Z digest=sha256:3e63bfe0e710a233e56021e2bb7f16d5388329fc556e5b35627628ae56586a8e

Observation c1e958a6-5658-4762-9752-fbb46c6c1a6b · outbound

This paper cites GLU Variants Improve Transformer.

Compute Requirements for Algorithmic Innovation in Frontier AI Models GLU Variants Improve Transformer

Reference 50

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source=arxiv_source observed=2026-08-06T17:52:50.663547Z digest=sha256:43fc086181e4ca6baebce3a62d80b57153eecf66a93d499700ef45a17803030c

Observation 33e57a43-69a5-46d7-9940-4cb47c0f34f9 · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 51

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source=arxiv_source observed=2026-08-06T17:52:50.678586Z digest=sha256:ce871ed2239e467242614e9745b953817648bece094048e4b72e25eb94369c46

Observation c865a99a-058a-4ac4-88ae-423faa6c7887 · outbound

This paper cites an unresolved cited work.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Unresolved cited work

Reference 52

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source=arxiv_source observed=2026-08-06T17:52:50.690833Z digest=sha256:3dac78a3facf10233f5c61116766ae18205aaadef764798f3c5d10152fe8dd5a

Observation e4a08b0b-2314-4b31-bfcd-745c0cfba9f7 · outbound

This paper cites RoFormer : Enhanced transformer with Rotary Position Embedding.

Compute Requirements for Algorithmic Innovation in Frontier AI Models RoFormer : Enhanced transformer with Rotary Position Embedding

Reference 53

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source=arxiv_source observed=2026-08-06T17:52:50.701306Z digest=sha256:ad0eb39241e40247a19ee9a74c41d763ae7d629187ee76ec1755e72b19f65a02

Observation 8c9e014d-64cd-47e3-ac14-837f4dce1447 · outbound

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

Compute Requirements for Algorithmic Innovation in Frontier AI Models LLaMA: Open and Efficient Foundation Language Models

Reference 54

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source=arxiv_source observed=2026-08-06T17:52:50.710494Z digest=sha256:8492b52c2c1d36d6b0e2680a803096ea5dcdca1716b42bd040d8b5fcad8bc7de

Observation 1bc59c9e-4d4c-489c-9008-6f4400b94fb2 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 55

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source=arxiv_source observed=2026-08-06T17:52:50.724494Z digest=sha256:f663b468efe7fc59b7ccaa8eaa68c6c30354e8830ef4ee918d93832b892407c3

Observation 1e92a1f9-563d-4771-adda-acfda88560a6 · outbound

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

Compute Requirements for Algorithmic Innovation in Frontier AI Models N., Kaiser, ., and Polosukhin, I

Reference 56

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verified fuzzy
raw_fallback, observed 2026-08-06T17:52:51.404323Z

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=arxiv_source observed=2026-08-06T17:52:50.739062Z digest=sha256:05a7295d573236dd6b8b8f751bd6ebdb0bb4518a0ba16bcf963bdbcb50a377d7

Observation 0aa70b7c-96a6-4874-b10a-89baf9b25753 · outbound

This paper cites Auxiliary- Loss - Free Load Balancing Strategy for Mixture -of- Experts.

Compute Requirements for Algorithmic Innovation in Frontier AI Models Auxiliary- Loss - Free Load Balancing Strategy for Mixture -of- Experts

Reference 57

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raw_fallback, observed 2026-08-06T17:52:51.382124Z

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

source=arxiv_source observed=2026-08-06T17:52:50.746854Z digest=sha256:3d6ae83733e229872308b9ee292cdbb45d83ab79a42ccbdf116a7dc06aed315c

Observation a2a851bd-e006-4495-871c-b13c6e4a11ce · outbound

This paper cites CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data.

Compute Requirements for Algorithmic Innovation in Frontier AI Models CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 58

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source=arxiv_source observed=2026-08-06T17:52:50.757421Z digest=sha256:abef71d1cdd53811ccea61d720fe8856a8843617c6e54e978a4a72e5d6651473

Observation 51bc122c-b4c3-40af-9d2c-bce7d537755e · outbound

This paper cites A., Oguz, B., Khabsa, M., Fang, H., Mehdad, Y., Narang, S., Malik, K., Fan, A., Bhosale, S., Edunov, S., Lewis, M., Wang, S., and Ma, H.

Compute Requirements for Algorithmic Innovation in Frontier AI Models A., Oguz, B., Khabsa, M., Fang, H., Mehdad, Y., Narang, S., Malik, K., Fan, A., Bhosale, S., Edunov, S., Lewis, M., Wang, S., and Ma, H

Reference 59

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source=arxiv_source observed=2026-08-06T17:52:50.774046Z digest=sha256:8f79c245add86b9365ab8d37485c99bcb228afc4066dd3ec24d9c603e978afdc

Observation 43bdfeb4-5090-4e69-ac4b-6b151f68f56f · outbound

This paper cites and Sennrich, R.

Compute Requirements for Algorithmic Innovation in Frontier AI Models and Sennrich, R

Reference 60

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

source=arxiv_source observed=2026-08-06T17:52:50.786013Z digest=sha256:737f0234e0ddda039495757c4dd6e84b4b994c65071eb7c61e925557fda078a6

Observation 5dc1ac43-38ad-440f-8dcf-e4a9f8245472 · outbound

This paper cites PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel.

Compute Requirements for Algorithmic Innovation in Frontier AI Models PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel

Reference 61

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source=arxiv_source observed=2026-08-06T17:52:50.798959Z digest=sha256:281531e6f7e03dfe71d56a96e686cdef1b2c5ced2c6a161b10d8173f337779ea

Pith citing papers

Observation 299b95fc-a2c2-4edd-bc72-b193a081b56c · inbound

How to Catch a GPU: A Taxonomy of Verification and Enforcement Mechanisms for International AI Agreements cites this paper.

How to Catch a GPU: A Taxonomy of Verification and Enforcement Mechanisms for International AI Agreements Compute Requirements for Algorithmic Innovation in Frontier AI Models

Reference 8

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source=arxiv_source observed=2026-08-02T11:04:06.709639Z digest=sha256:9dddf1d7c113314349f45ea39b00005c8356429e37aaf7358e501c4ab617d965