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Paper Citation Record · LEDGER

INTELLECT-1 Technical Report

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2412.01152.

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

pith.paper-citation-record.v1
2412.01152 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:45:01.040578Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:40:00.416301Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation faaed0ed-f10b-403d-8154-f9f5530ced33 · inbound

A Survey on Foundation Models for Personalized Federated Intelligence cites this paper.

A Survey on Foundation Models for Personalized Federated Intelligence INTELLECT-1 Technical Report

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-22T15:34:57.726613Z

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.

source=pdf_text observed=2026-05-22T15:32:15.293888Z digest=sha256:b29030efd7c60e98f5f3175efd2f4811b942b3693d38822ce44453ce17e82b83

Observation a6668398-4f49-4ea9-a6f7-572b6afab45a · inbound

Prime Collective Communications Library -- Technical Report cites this paper.

Prime Collective Communications Library -- Technical Report INTELLECT-1 Technical Report

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T15:45:01.040578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:45:01.040578Z digest=sha256:6d39ac49e5b44430f3f1d918296b5eece87ded3b86e2464bf765c74b6b5cbff8

Observation 00911ebd-df77-41b9-9f9b-f5f8253a9625 · inbound

Incentivizing Permissionless Distributed Learning of LLMs cites this paper.

Incentivizing Permissionless Distributed Learning of LLMs INTELLECT-1 Technical Report

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T13:30:19.364823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:19.364823Z digest=sha256:2439919cc8586a00cf94f276f1ba5edddbe905eccb62a0990b07e24c75e3b7a8

Observation 4b21ee67-4582-411c-addc-45a3bf24a7fe · inbound

MuLoCo: Muon is a practical inner optimizer for DiLoCo cites this paper.

MuLoCo: Muon is a practical inner optimizer for DiLoCo INTELLECT-1 Technical Report

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:26.900794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:45:26.900794Z digest=sha256:879ad9dfae1a78f9f9372e3810a66979fa66a50f81a78711a128469ed676e2f5

Observation 3374d221-5816-47ef-83dd-ecb16684645c · inbound

NoLoCo: No-all-reduce Low Communication Training Method for Large Models cites this paper.

NoLoCo: No-all-reduce Low Communication Training Method for Large Models INTELLECT-1 Technical Report

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T04:20:02.210179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:20:02.210179Z digest=sha256:d71acb197f81ba7eaad7df072ca5cfbfce00fa8f373938544de921b44931cd9e

Observation 195eaabb-d4b2-442c-b067-97413a77223e · inbound

On the Surprising Effectiveness of a Single Global Merging in Decentralized Learning cites this paper.

On the Surprising Effectiveness of a Single Global Merging in Decentralized Learning INTELLECT-1 Technical Report

Reference 39

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T05:42:06.099167Z

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.

source=pdf_text observed=2026-05-19T05:39:53.088948Z digest=sha256:f48c9c967958af1579fcf49fcf697534b27a28bca23a508ad724ab1418253b23

Observation 07a44ee0-e93c-4d4c-9d71-4a30b70a4ca8 · inbound

DICE: Data Influence Cascade in Decentralized Learning cites this paper.

DICE: Data Influence Cascade in Decentralized Learning INTELLECT-1 Technical Report

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T19:00:01.481770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:00:01.481770Z digest=sha256:00e7a4fb20d174d4d70041f1cd6deaf1d80478dfc0ed451c815047c75baa7e4b

Observation 7a71f022-6493-413d-b924-f86804f953bc · inbound

Distributed and Decentralised Training: Technical Governance Challenges in a Shifting AI Landscape cites this paper.

Distributed and Decentralised Training: Technical Governance Challenges in a Shifting AI Landscape INTELLECT-1 Technical Report

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T18:37:46.302248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:37:46.302248Z digest=sha256:7fab0f24f58aedbc8d309ba2ea935b8652cf41e097b47f7ec993728550114e5c

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

Compute Requirements for Algorithmic Innovation in Frontier AI Models cites this paper.

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

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T17:52:50.376961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:52:50.376961Z digest=sha256:9da32992b0bc89afb2ae54ede007ff09c39f82d06cdf78cba11b1f7eacd7a815

Observation 63df926d-8e53-4189-88e7-22d9e4ffa8e5 · inbound

Overcoming the Communication-Performance Tradeoff in LLM Pretraining cites this paper.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining INTELLECT-1 Technical Report

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T17:50:42.768010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:50:42.768010Z digest=sha256:48f9688dd14ced750ed89ccfbbbfdb6cd1838ae142309cbb978b4f42e6ca76df

Observation e163af05-5ad3-4b11-9034-c2322da03950 · inbound

Overcoming the Communication-Performance Tradeoff in LLM Pretraining cites this paper.

Overcoming the Communication-Performance Tradeoff in LLM Pretraining INTELLECT-1 Technical Report

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-05T17:50:42.668228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:50:42.668228Z digest=sha256:5920fd41293bb865f46d13d3f83e0f02222a0eecf053fa3fcf2d654568f2c4b4

Observation 647c8c9a-07b9-4908-a2a5-e37755e586de · inbound

Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models cites this paper.

Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models INTELLECT-1 Technical Report

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-04T22:56:05.180826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:56:05.180826Z digest=sha256:b98073a69104f7801422a326b1ad48e54f2ae62b04c89cf71a06d12dc8775302

Observation 34e76acd-4b2f-4c0b-a9d1-b1c781910ed1 · inbound

Local MixVR: Breaking the Communication-Sample Dependence in Distributed Learning cites this paper.

Local MixVR: Breaking the Communication-Sample Dependence in Distributed Learning INTELLECT-1 Technical Report

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:16:14.065730Z

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.

source=pdf_text observed=2026-06-28T17:22:36.503465Z digest=sha256:3719ae1b539e3882344fa4e434f22dcd2d8101f99fd6d5308820bf0159d72abe

Observation 985c4fc3-02a0-44e9-997a-8e30db86c681 · inbound

Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models cites this paper.

Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models INTELLECT-1 Technical Report

Reference 44

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T11:28:04.431492Z

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.

source=arxiv_source observed=2026-06-27T09:34:02.484344Z digest=sha256:a2f8c9805bd28923d969b086f890b7ce1c1224ec1ab77916358596ffad29ad7a

Observation ab925268-e317-4233-a56e-ee827934545f · inbound

Decentralised AI Training and Inference with BlockTrain cites this paper.

Decentralised AI Training and Inference with BlockTrain INTELLECT-1 Technical Report

Reference 90

Resolution
verified exact
arxiv_id, observed 2026-07-04T17:40:00.417773Z

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.

source=arxiv_source observed=2026-06-25T23:32:43.585170Z digest=sha256:8ce1683b1062f51cf3347058867037780f5a8e437846d4ac0ad6fdca4fe5982c

Observation 2d469e1d-4c0b-4743-8b6e-15df9c522b53 · inbound

Decentralised AI Training and Inference with BlockTrain cites this paper.

Decentralised AI Training and Inference with BlockTrain INTELLECT-1 Technical Report

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-12T12:29:35.403453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T12:29:35.403453Z digest=sha256:011fd5b5ef5485a78cb39d352892be49ed44b4dbc59babb7adb7ca441ee6a40d

Observation 037c166a-20dd-4130-a804-44adab04a24a · inbound

SLIM-RL: Risk-Budgeted Random-Masking RL for Diffusion LLMs Without Trajectory Slicing cites this paper.

SLIM-RL: Risk-Budgeted Random-Masking RL for Diffusion LLMs Without Trajectory Slicing INTELLECT-1 Technical Report

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T19:07:17.225982Z

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.

source=pdf_text observed=2026-07-02T19:05:59.651008Z digest=sha256:271c441219a2d24430b2f76d9a714dd3e2f0e59c44567b58044834bf793d8ed3

Observation bf4ff253-9c99-413e-92ae-c7b20e10f294 · inbound

Can Model Merging Improve Aggregation in DiLoCo? cites this paper.

Can Model Merging Improve Aggregation in DiLoCo? INTELLECT-1 Technical Report

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-12T05:28:12.811678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T05:28:12.811678Z digest=sha256:d1a1ab5ba11f841394c12f511cac99b946dd0d9c6946848e1198fc7c1121153d

Observation 7aedcfdd-a57b-4403-afd6-fa849777268f · inbound

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers cites this paper.

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers INTELLECT-1 Technical Report

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-11T13:03:39.236118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T13:03:39.236118Z digest=sha256:b8e1ab57a7c78bfb8fb4833bcf6169ffb7094d08ff8d345bb430602121ee1136

Observation b32fbf9f-afa9-4c10-916d-278015236b0d · inbound

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers cites this paper.

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers INTELLECT-1 Technical Report

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-14T16:21:05.570023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T16:21:05.570023Z digest=sha256:7a5b7cd098dae0cc92868c538977f13e6b4f11f2ef0229cd582d733e7fc28506