Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-16T06:26:38.569394Z
Paper Citation Record · LEDGER
MiniMax-01: Scaling Foundation Models with Lightning Attention
As of 4 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 59 inbound Pith citation observations for arXiv:2501.08313.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T14:43:02.535332Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T06:15:00.866473Z
Reference resolution
68 of 68 outbound references displayed
- verified exact10
- verified fuzzy37
- unresolved15
- parse uncertain5
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 52010afa-8fd0-4a6e-bf6c-6be316561a6c · outbound
This paper cites MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark.
MiniMax-01: Scaling Foundation Models with Lightning Attention MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark
Reference 1
- Resolution
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- local_arxiv, observed 2026-05-16T06:26:38.699617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation de9885bc-bfbc-4aa3-be2e-d6a1bfa726e2 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.882376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 50af0b87-f250-4e48-8a44-cf8773550a5d · outbound
This paper cites This process repeats iteratively until the response is complete, ensuring that every sentence in the output aligns with human preferences.
MiniMax-01: Scaling Foundation Models with Lightning Attention This process repeats iteratively until the response is complete, ensuring that every sentence in the output aligns with human preferences
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.886142Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8499b188-36a5-4391-8a78-1e700e7b111d · outbound
This paper cites The training objective is to mini- mize the negative log-likelihood loss between the model’s output and the corrected answer.
MiniMax-01: Scaling Foundation Models with Lightning Attention The training objective is to mini- mize the negative log-likelihood loss between the model’s output and the corrected answer
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.890943Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d9334395-c75f-446a-a918-73ac815bd78a · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.897336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3ab095c7-a182-4833-b76a-521320ec0ee8 · outbound
This paper cites • Generation Methods:The study compares the classic sentence-by-sentence correction pipeline with a new continue generation pipeline.
MiniMax-01: Scaling Foundation Models with Lightning Attention • Generation Methods:The study compares the classic sentence-by-sentence correction pipeline with a new continue generation pipeline
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.900336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 55701cb4-e343-4a72-8dc3-a2d248d8d032 · outbound
This paper cites It also achieves the performance of Aligner-70B using only 2B parameters, showcasing both superior performance and efficiency.
MiniMax-01: Scaling Foundation Models with Lightning Attention It also achieves the performance of Aligner-70B using only 2B parameters, showcasing both superior performance and efficiency
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.904587Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e63eab76-754b-4583-ab9d-bfc4359c4510 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.908642Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 80411abb-1a1a-4ce5-b47a-0bbf87fba682 · outbound
This paper cites It achieves significant improvements in helpfulness, harmlessness, and reasoning abilities, making it a promising approach for aligning LLMs with human values.
MiniMax-01: Scaling Foundation Models with Lightning Attention It achieves significant improvements in helpfulness, harmlessness, and reasoning abilities, making it a promising approach for aligning LLMs with human values
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.912395Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e53e8b88-7999-4632-bb59-6f16e9752b58 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.915578Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 904c42f4-6e68-4a37-a8d3-255c7cbe05dd · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 11
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 536b43cc-7f5a-49e8-a036-f008fe47a973 · outbound
This paper cites neurones multimodaux.
MiniMax-01: Scaling Foundation Models with Lightning Attention neurones multimodaux
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.704489Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 92eedfeb-55ce-4793-89c7-7c5410e85c4a · outbound
This paper cites Traduisez cette phrase du chinois à l’anglais.
MiniMax-01: Scaling Foundation Models with Lightning Attention Traduisez cette phrase du chinois à l’anglais
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.708923Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2c8e47ba-08bf-407c-8a2c-9415e7d2450b · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 14
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b87eb815-df59-47df-bd77-1f403273bcb5 · outbound
This paper cites Nous avons égale- ment discuté de l’évolution, des limitations et de l’avenir de l’AGI.
MiniMax-01: Scaling Foundation Models with Lightning Attention Nous avons égale- ment discuté de l’évolution, des limitations et de l’avenir de l’AGI
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.716836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cba3d9af-a2f5-4e86-ba5e-3025f1c3383a · outbound
This paper cites Shigihara Y, Zeki S.
MiniMax-01: Scaling Foundation Models with Lightning Attention Shigihara Y, Zeki S
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.720560Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a5ca0cd6-500b-460e-83bc-97485fe1feff · outbound
This paper cites Neuroplasticité.
MiniMax-01: Scaling Foundation Models with Lightning Attention Neuroplasticité
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.723980Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation dd0c97cf-3b70-4daa-bd7d-4c65f2d8301e · outbound
This paper cites Champs ré- cepteurs, interaction binoculaire et archi- tecture fonctionnelle dans le cortex visuel du chat.
MiniMax-01: Scaling Foundation Models with Lightning Attention Champs ré- cepteurs, interaction binoculaire et archi- tecture fonctionnelle dans le cortex visuel du chat
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.727749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 41a7893f-9321-4fce-86da-020e6158dc4b · outbound
This paper cites Le système d’attention du cerveau humain.
MiniMax-01: Scaling Foundation Models with Lightning Attention Le système d’attention du cerveau humain
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.731448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f1ef7688-07c0-41a3-b79d-534064e28475 · outbound
This paper cites Radford A, Narasimhan K, Sali- mans T, Sutskever I.
MiniMax-01: Scaling Foundation Models with Lightning Attention Radford A, Narasimhan K, Sali- mans T, Sutskever I
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.734952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 956ac970-b47d-4b68-9f07-1256ee015c55 · outbound
This paper cites Bassett DS, Bullmore E.
MiniMax-01: Scaling Foundation Models with Lightning Attention Bassett DS, Bullmore E
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.738392Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e5791146-ec1d-4721-a05c-91b34f37eec3 · outbound
This paper cites Xie S, Kiril–lov A, Girshick R, He K.
MiniMax-01: Scaling Foundation Models with Lightning Attention Xie S, Kiril–lov A, Girshick R, He K
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.741790Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 42df7ad6-ef3c-4d67-998f-d51ff80c13f8 · outbound
This paper cites Zhao L , L, Dai H, Wu Z, et al.
MiniMax-01: Scaling Foundation Models with Lightning Attention Zhao L , L, Dai H, Wu Z, et al
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.745399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6f2fd073-aee5-4d57-b702-e8217ea7a4f2 · outbound
This paper cites Yu X, Zhang L, Dai H, et al.
MiniMax-01: Scaling Foundation Models with Lightning Attention Yu X, Zhang L, Dai H, et al
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.748838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c8c38096-0aeb-40e7-a7a5-df658813ab64 · outbound
This paper cites Zhao L, Dai H, Wu Z, Zhu D, Liu T, Cnn CP-.
MiniMax-01: Scaling Foundation Models with Lightning Attention Zhao L, Dai H, Wu Z, Zhu D, Liu T, Cnn CP-
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.751989Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f407a3e8-5b7c-49ca-8673-1571a68a8e5a · outbound
This paper cites Ghosh-Dastidar S, Adeli H.
MiniMax-01: Scaling Foundation Models with Lightning Attention Ghosh-Dastidar S, Adeli H
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.755095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 42591909-ab5a-49be-94bf-4ce1bd65bb33 · outbound
This paper cites Créer des robots plus intelligents grâce au cal- cul inspiré du cerveau.
MiniMax-01: Scaling Foundation Models with Lightning Attention Créer des robots plus intelligents grâce au cal- cul inspiré du cerveau
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.758960Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 015844f6-4a1e-4866-84bb-883500c0a75b · outbound
This paper cites Vers une intelligence machine basée sur les pointes avec le calcul neuromorphique.
MiniMax-01: Scaling Foundation Models with Lightning Attention Vers une intelligence machine basée sur les pointes avec le calcul neuromorphique
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.762819Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a8038008-746d-4a7a-9ee4-f2284c4822cc · outbound
This paper cites TrueNorth : conception et flux de travail d’une puce neurosynaptique pro- grammable d’un million de neurones de 65 mw.
MiniMax-01: Scaling Foundation Models with Lightning Attention TrueNorth : conception et flux de travail d’une puce neurosynaptique pro- grammable d’un million de neurones de 65 mw
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.767523Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 156d6f73-bb58-44ea-8a81-8a55dc62f7e8 · outbound
This paper cites Indiveri G, Douglas R.
MiniMax-01: Scaling Foundation Models with Lightning Attention Indiveri G, Douglas R
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.771113Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 08c323d1-4c42-4b0f-865e-33cace319b40 · outbound
This paper cites Devlin J, Cha–ng MW, Lee K, Toutanova K.
MiniMax-01: Scaling Foundation Models with Lightning Attention Devlin J, Cha–ng MW, Lee K, Toutanova K
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.775135Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ca6b9105-631a-443e-b6db-3b1a2479f12c · outbound
This paper cites Amélioration de la com- préhension du langage par la pré-formation générative.
MiniMax-01: Scaling Foundation Models with Lightning Attention Amélioration de la com- préhension du langage par la pré-formation générative
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.779604Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ee041a18-4a85-413c-aebd-6dc5bcfc9a12 · outbound
This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.
MiniMax-01: Scaling Foundation Models with Lightning Attention RoBERTa: A Robustly Optimized BERT Pretraining Approach
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T06:26:38.653364Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0f450d1a-5a13-489e-a6af-a4f10aa37aff · outbound
This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.
MiniMax-01: Scaling Foundation Models with Lightning Attention DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T06:26:38.670594Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation be888aa7-5ee0-4438-83c4-eda59be1c32d · outbound
This paper cites DeBERTa: Decoding-enhanced BERT with Disentangled Attention.
MiniMax-01: Scaling Foundation Models with Lightning Attention DeBERTa: Decoding-enhanced BERT with Disentangled Attention
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T06:26:38.683079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4c4cee9f-7db3-4662-bf58-b319e5e65482 · outbound
This paper cites Multitask Prompted Training Enables Zero-Shot Task Generalization.
MiniMax-01: Scaling Foundation Models with Lightning Attention Multitask Prompted Training Enables Zero-Shot Task Generalization
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T06:26:38.688305Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 386de7b3-4b36-40d4-bbcc-7dc5c61925f2 · outbound
This paper cites CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.
MiniMax-01: Scaling Foundation Models with Lightning Attention CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
Reference 37
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T06:26:38.694077Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4b54afb2-b5b9-488b-8db0-17fa88158b11 · outbound
This paper cites Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model.
MiniMax-01: Scaling Foundation Models with Lightning Attention Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T06:26:38.632248Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation da3810f0-ad63-4b9b-af39-5bdd428f222b · outbound
This paper cites Crosslingual Generalization through Multitask Finetuning.
MiniMax-01: Scaling Foundation Models with Lightning Attention Crosslingual Generalization through Multitask Finetuning
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.644752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4769a396-1bf0-43d5-bacc-d4820445d8b2 · outbound
This paper cites Jurassic-1 : Détails techniques et éval- uation.
MiniMax-01: Scaling Foundation Models with Lightning Attention Jurassic-1 : Détails techniques et éval- uation
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.783816Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 571e33ad-8893-4d12-925e-72cac4399069 · outbound
This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.
MiniMax-01: Scaling Foundation Models with Lightning Attention Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Reference 41
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T06:26:38.659096Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1d60456d-432a-4c76-8533-b2f181a1c9c4 · outbound
This paper cites ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation.
MiniMax-01: Scaling Foundation Models with Lightning Attention ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.665017Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1a044d63-ef83-4401-8645-d22d52d6467c · outbound
This paper cites Fun and Dystopia with Ai- BasedCodeGenerationUsingGpt-J-6b,June.
MiniMax-01: Scaling Foundation Models with Lightning Attention Fun and Dystopia with Ai- BasedCodeGenerationUsingGpt-J-6b,June
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.787730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5cce8672-5f20-48b6-a098-6ad63f20255d · outbound
This paper cites GPT-NeoX-20B: An Open-Source Autoregressive Language Model.
MiniMax-01: Scaling Foundation Models with Lightning Attention GPT-NeoX-20B: An Open-Source Autoregressive Language Model
Reference 44
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T06:26:38.676743Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6fae50e7-b611-4831-82d2-b0c59f378991 · outbound
This paper cites Whispers of the Lost City.
MiniMax-01: Scaling Foundation Models with Lightning Attention Whispers of the Lost City
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.791844Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6f8edbbf-d92b-4596-89b1-45d209192605 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.795949Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0090577a-064b-45bf-bbe0-7a9d99256881 · outbound
This paper cites Usually, there will be a speed sign on the exit ramp of the expressway, so keep an eye out for it.
MiniMax-01: Scaling Foundation Models with Lightning Attention Usually, there will be a speed sign on the exit ramp of the expressway, so keep an eye out for it
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.800078Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a3e6f2aa-a889-45f5-9a15-5a64d00eaa3c · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 48
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 955cf025-ec66-443a-9f3c-8033f3c9b835 · outbound
This paper cites Be aware of curves and slopes on ramps and maintain an appropriate speed.
MiniMax-01: Scaling Foundation Models with Lightning Attention Be aware of curves and slopes on ramps and maintain an appropriate speed
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.808065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5b4f56d6-2c9f-4fbb-a1b9-b6855e23a502 · outbound
This paper cites Navigation will guide you through the next segments until you reach your destination.
MiniMax-01: Scaling Foundation Models with Lightning Attention Navigation will guide you through the next segments until you reach your destination
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.812203Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d276e8e8-b7c6-4bc5-9cff-72f692f0e7a9 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 51
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.815788Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a93323de-e104-4ebe-810b-785f503bcf65 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 55
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.818990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c4c2abf1-67ae-48e1-b709-ad880b4f272b · outbound
This paper cites Second row.
MiniMax-01: Scaling Foundation Models with Lightning Attention Second row
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.822464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4d35c28c-65d2-4a06-b060-abb573c2c287 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 57
- Resolution
- parse uncertain
- raw_fallback, observed 2026-05-16T06:26:38.825287Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c4771cec-cc04-4d47-8629-06d14abc7439 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 58
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.828985Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a46bca79-c35e-41c3-a127-0ee2809765ac · outbound
This paper cites Third row.
MiniMax-01: Scaling Foundation Models with Lightning Attention Third row
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.831825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fcf663a7-712c-4b6c-9218-cad77c255101 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 62
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.834994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7c1347fe-dfd4-4268-af60-480209668ab8 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 63
- Resolution
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- raw_fallback, observed 2026-05-16T06:26:38.839965Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e93c1a5b-bbfc-4402-9f97-f2e6717b5693 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 64
- Resolution
- parse uncertain
- raw_fallback, observed 2026-05-16T06:26:38.844386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c794769d-af61-4027-bcbb-64a28ce6c275 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 65
- Resolution
- parse uncertain
- raw_fallback, observed 2026-05-16T06:26:38.848060Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 75e919cf-0861-4294-ad3e-ceb429044dc1 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 66
- Resolution
- parse uncertain
- raw_fallback, observed 2026-05-16T06:26:38.851671Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 222c7ab8-7aaf-4634-9b01-93d61d93de73 · outbound
This paper cites Enter invoice details.
MiniMax-01: Scaling Foundation Models with Lightning Attention Enter invoice details
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.857791Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 62c39f62-624b-4b87-b594-253f1f532e5e · outbound
This paper cites This will significantly reduce the time spent on manual entry.
MiniMax-01: Scaling Foundation Models with Lightning Attention This will significantly reduce the time spent on manual entry
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.861908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3a8e1466-524d-49e2-9028-2df2218414d4 · outbound
This paper cites For example, use drop-down menus, auto-fill, and smart suggestion features to reduce user input time and error rates.
MiniMax-01: Scaling Foundation Models with Lightning Attention For example, use drop-down menus, auto-fill, and smart suggestion features to reduce user input time and error rates
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.865452Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d94e48e8-1838-47b6-9c5d-5466342eb8bc · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 70
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.869057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c54814cd-94b2-4c8e-ac0b-7b5f09a92347 · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 71
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.872123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4bd8b78f-a4b5-491a-81a2-bc14ef85e7cb · outbound
This paper cites an unresolved cited work.
MiniMax-01: Scaling Foundation Models with Lightning Attention Unresolved cited work
Reference 72
- Resolution
- unresolved
- raw_fallback, observed 2026-05-16T06:26:38.875401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c0a3a900-5d71-42ae-9b86-a82035b7cd93 · outbound
This paper cites Enter invoice details.
MiniMax-01: Scaling Foundation Models with Lightning Attention Enter invoice details
Reference 73
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-16T06:26:38.878919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
Observation 3d1512fb-5401-4e5a-b585-ab8934f029a8 · inbound
LightTransfer: Your Long-Context LLM is Secretly a Hybrid Model with Effortless Adaptation cites this paper.
LightTransfer: Your Long-Context LLM is Secretly a Hybrid Model with Effortless Adaptation MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-05-23T18:33:19.550020Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 70cbb10f-d834-44e6-917c-872bc1fcfe16 · inbound
MoBA: Mixture of Block Attention for Long-Context LLMs cites this paper.
MoBA: Mixture of Block Attention for Long-Context LLMs MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 59
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b9bd8dc2-3dfb-4e97-bcef-6e0678c4f6fa · inbound
Qwen2.5-VL Technical Report cites this paper.
Qwen2.5-VL Technical Report MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-05-23T02:25:19.044130Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a6cc82a0-b045-4130-9a71-655fe31388d5 · inbound
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free cites this paper.
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d4ef5545-0d5b-4647-9c1f-e04512a18721 · inbound
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention cites this paper.
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 22
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 251c5e9b-7a2b-48e5-b9c3-1e728bd321ed · inbound
MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent cites this paper.
MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 29d89a47-7d27-49bc-8d14-8a498d83b218 · inbound
Causal2Vec: Improving Decoder-only LLMs as Embedding Models through a Contextual Token cites this paper.
Causal2Vec: Improving Decoder-only LLMs as Embedding Models through a Contextual Token MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T02:21:59.265338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6e8b9b0f-0fb6-4214-bccd-f7592a609d0f · inbound
InfiniPipe: Elastic Pipeline Parallelism for Efficient Variable-Length Long-Context LLM Training cites this paper.
InfiniPipe: Elastic Pipeline Parallelism for Efficient Variable-Length Long-Context LLM Training MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T14:06:27.257150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c97209c8-b2a4-46f5-b362-09d302fc60b5 · inbound
StateX: Enhancing RNN Recall via Post-training State Expansion cites this paper.
StateX: Enhancing RNN Recall via Post-training State Expansion MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T12:31:22.112906Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 792e798f-6720-4832-9689-43d6818dabde · inbound
OctoPipe: Reducing Pipeline Bubbles for Heterogeneous Models via Co-Optimizing Partitioning, Placement, and Scheduling cites this paper.
OctoPipe: Reducing Pipeline Bubbles for Heterogeneous Models via Co-Optimizing Partitioning, Placement, and Scheduling MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T14:42:59.377440Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bd1c0ab8-89ca-4471-956a-5a7afbdc86fa · inbound
ChunkLLM: A Lightweight Pluggable Framework for Accelerating LLMs Inference cites this paper.
ChunkLLM: A Lightweight Pluggable Framework for Accelerating LLMs Inference MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T14:43:02.535332Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1634359b-11f0-46c9-868c-92ac777ae4dc · inbound
SpikingMamba: Towards Energy-Efficient Large Language Models via Knowledge Distillation from Mamba cites this paper.
SpikingMamba: Towards Energy-Efficient Large Language Models via Knowledge Distillation from Mamba MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T09:46:12.416706Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3d902561-7af7-45e5-b1b6-8875eda90177 · inbound
Hybrid Architectures for Language Models: Systematic Analysis and Design Insights cites this paper.
Hybrid Architectures for Language Models: Systematic Analysis and Design Insights MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 28
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T10:21:15.043518Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e911b3eb-3eb6-4c01-be23-aac7d558d4b8 · inbound
Kimi Linear: An Expressive, Efficient Attention Architecture cites this paper.
Kimi Linear: An Expressive, Efficient Attention Architecture MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 67
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 305c7c14-d515-4b80-a7ee-fd3a08b5476b · inbound
SpatialBench: Benchmarking Multimodal Large Language Models for Spatial Cognition cites this paper.
SpatialBench: Benchmarking Multimodal Large Language Models for Spatial Cognition MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T04:59:04.221022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 67bb743a-09cb-4541-adbc-23e5221ac94f · inbound
Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models cites this paper.
Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T04:55:42.327280Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f5023faf-b806-43fe-b7d0-9e5e5da4f723 · inbound
Three non-Hermitian random matrix universality classes of complex edge statistics: Spacing ratios and distributions cites this paper.
Three non-Hermitian random matrix universality classes of complex edge statistics: Spacing ratios and distributions MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T16:19:49.419805Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14ad3b12-c98d-48e9-86ed-b39ccc917e37 · inbound
HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention cites this paper.
HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 11
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cca06ad0-3628-40b8-8f66-a19ac566dc39 · inbound
BOSCH: Black-Box Binary Optimization for Short-Context Attention-Head Selection in LLMs cites this paper.
BOSCH: Black-Box Binary Optimization for Short-Context Attention-Head Selection in LLMs MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 76c10caf-d8e9-4243-a208-288a16825518 · inbound
ClawGuard: A Runtime Security Framework for Tool-Augmented LLM Agents Against Indirect Prompt Injection cites this paper.
ClawGuard: A Runtime Security Framework for Tool-Augmented LLM Agents Against Indirect Prompt Injection MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation da1adabd-becb-436d-9e3b-2f0faaeec788 · inbound
ClawGuard: A Runtime Security Framework for Tool-Augmented LLM Agents Against Indirect Prompt Injection cites this paper.
ClawGuard: A Runtime Security Framework for Tool-Augmented LLM Agents Against Indirect Prompt Injection MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 39b5c90c-9661-479e-a685-fe7f33a6264b · inbound
Disposition Distillation at Small Scale: A Three-Arc Negative Result cites this paper.
Disposition Distillation at Small Scale: A Three-Arc Negative Result MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0f67708f-8d6e-4cc8-90f0-fae9ba2a1827 · inbound
MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games cites this paper.
MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation efaa45f3-60b0-4416-9126-253f1830d444 · inbound
Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling cites this paper.
Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ac351d55-cee3-4002-870c-fd6dc7686261 · inbound
OralMLLM-Bench: Evaluating Cognitive Capabilities of Multimodal Large Language Models in Dental Practice cites this paper.
OralMLLM-Bench: Evaluating Cognitive Capabilities of Multimodal Large Language Models in Dental Practice MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 700f524e-a97b-48d2-b68a-10ebd624ece3 · inbound
When Is the Same Model Not the Same Service? A Measurement Study of Hosted Open-Weight LLM APIs cites this paper.
When Is the Same Model Not the Same Service? A Measurement Study of Hosted Open-Weight LLM APIs MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8709af53-2f17-4b2d-b7cc-ac5f60bdd131 · inbound
When Is the Same Model Not the Same Service? A Measurement Study of Hosted Open-Weight LLM APIs cites this paper.
When Is the Same Model Not the Same Service? A Measurement Study of Hosted Open-Weight LLM APIs MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3225da1d-0068-4b81-a447-c7ca3b7877b8 · inbound
The Impossibility Triangle of Long-Context Modeling cites this paper.
The Impossibility Triangle of Long-Context Modeling MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 55dcb398-add9-4c41-9f4b-98cb451f8a15 · inbound
MDN: Parallelizing Stepwise Momentum for Delta Linear Attention cites this paper.
MDN: Parallelizing Stepwise Momentum for Delta Linear Attention MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 75
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d09d34ce-851e-428a-b575-500410bb32d5 · inbound
UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification cites this paper.
UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1d8eaca9-34ec-4343-ad59-a6f847d3af5e · inbound
MISA: Mixture of Indexer Sparse Attention for Long-Context LLM Inference cites this paper.
MISA: Mixture of Indexer Sparse Attention for Long-Context LLM Inference MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7f19f137-4353-4a55-ac88-3c5ab6a3a62b · inbound
EpiGraph: Building Generalists for Evidence-Intensive Epilepsy Reasoning in the Wild cites this paper.
EpiGraph: Building Generalists for Evidence-Intensive Epilepsy Reasoning in the Wild MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 228575b1-9198-4f75-a558-f970e38a90bb · inbound
EpiGraph: Building Generalists for Evidence-Intensive Epilepsy Reasoning in the Wild cites this paper.
EpiGraph: Building Generalists for Evidence-Intensive Epilepsy Reasoning in the Wild MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f588b8c9-2806-4213-be57-769b4169f552 · inbound
Position: LLM Inference Should Be Evaluated as Energy-to-Token Production cites this paper.
Position: LLM Inference Should Be Evaluated as Energy-to-Token Production MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:26:38.921226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8bf94a16-1a1c-41d9-a149-1f628ad911c8 · inbound
Text2CAD-Bench: A Benchmark for LLM-based Text-to-Parametric CAD Generation cites this paper.
Text2CAD-Bench: A Benchmark for LLM-based Text-to-Parametric CAD Generation MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 37
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-20T12:53:17.765087Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1501e24d-69b3-4e98-8d61-69998b07d431 · inbound
Exact Linear Attention cites this paper.
Exact Linear Attention MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T20:59:01.534780Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 81d0f246-f5e9-4ce9-bd6c-4483dce2661b · inbound
Exact Linear Attention cites this paper.
Exact Linear Attention MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T08:49:53.935730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b36a1873-d35d-4f0f-ac3b-4c1e33d9a878 · inbound
Exact Linear Attention cites this paper.
Exact Linear Attention MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T14:25:45.806380Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 706d01f6-b00d-442f-8919-fde418195236 · inbound
Learning Design Skills as Memory Policies for Agentic Photonic Inverse Design cites this paper.
Learning Design Skills as Memory Policies for Agentic Photonic Inverse Design MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T08:03:13.861236Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0d1b6457-13f8-4a4e-8741-38ea5d9a7eee · inbound
I-WebGenBench : Evaluating Interactivity in LLM-Generated Scientific Web Applications cites this paper.
I-WebGenBench : Evaluating Interactivity in LLM-Generated Scientific Web Applications MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T19:42:36.177475Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation db43bba0-673c-46e1-ac58-cacb77edd73a · inbound
Asuka-Bench: Benchmarking Code Agents on Underspecified User Intent and Multi-Round Refinement cites this paper.
Asuka-Bench: Benchmarking Code Agents on Underspecified User Intent and Multi-Round Refinement MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 16
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T14:27:04.317255Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9b2131ca-4824-4aa8-a247-4929cd1dfbd3 · inbound
You Only Index Once: Cross-Layer Sparse Attention with Shared Routing cites this paper.
You Only Index Once: Cross-Layer Sparse Attention with Shared Routing MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T13:36:59.564415Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 997b2ac0-2e84-48f7-97fd-80e477a23c2a · inbound
Repetition Mismatch: Why Data Mixture Experiments Don't Scale and How to Fix Them cites this paper.
Repetition Mismatch: Why Data Mixture Experiments Don't Scale and How to Fix Them MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T23:22:46.220068Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9886cd55-1e75-4bc2-aa85-35f009651b3e · inbound
SIFT: Selective-Index For Fast Compute of RAG Prefill by Exploiting Attention Invariance cites this paper.
SIFT: Selective-Index For Fast Compute of RAG Prefill by Exploiting Attention Invariance MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T01:37:31.233073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a037c08f-918a-4be7-9e33-2a96be25df55 · inbound
MiniMax Sparse Attention cites this paper.
MiniMax Sparse Attention MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T15:28:34.108034Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 000d381e-f945-4d26-8741-2c315dd81ba8 · inbound
From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI cites this paper.
From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 150
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T11:29:32.433234Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8fcfcd22-d17c-4ac3-b190-7f3fda49cd85 · inbound
Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI cites this paper.
Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 183
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T17:28:44.967152Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 91a833c0-9a30-4de1-80ec-c97cfbe396d7 · inbound
MoECodec: Image Compression for joint human and machine perception via Mixture-of-Experts cites this paper.
MoECodec: Image Compression for joint human and machine perception via Mixture-of-Experts MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 31
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T07:39:38.956389Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1526636a-4f93-457f-82bc-e007caaa2034 · inbound
MacroLens: A Multi-Task Benchmark for Contextual Financial Reasoning under Macroeconomic Scenarios cites this paper.
MacroLens: A Multi-Task Benchmark for Contextual Financial Reasoning under Macroeconomic Scenarios MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 2
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T16:09:56.472425Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 95f96e7f-80ef-403b-aeac-c119992d545f · inbound
Focusing on What Matters: Saliency-Harnessing Accurate Routing for Diffusion MoE cites this paper.
Focusing on What Matters: Saliency-Harnessing Accurate Routing for Diffusion MoE MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 16
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T13:29:51.526571Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f26578f6-3af1-41af-8fd2-87c1a49a2ea7 · inbound
One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining cites this paper.
One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T06:44:18.897171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a0a682e5-c591-43a5-bc88-691f7ab343e7 · inbound
AeroVerse-SatAgent: UAV-Satellite Collaborative Spatial Reasoning Inspired by the Dual Visual Pathway Theory of Cognitive Neuroscience cites this paper.
AeroVerse-SatAgent: UAV-Satellite Collaborative Spatial Reasoning Inspired by the Dual Visual Pathway Theory of Cognitive Neuroscience MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 98
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T09:45:39.833249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0597f712-b328-4e5f-abe0-6cc59828d3ae · inbound
TileLens: Efficiently Using Large-Granularity Memory Systems with Transparent Two-Dimensional Memory Layout cites this paper.
TileLens: Efficiently Using Large-Granularity Memory Systems with Transparent Two-Dimensional Memory Layout MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T22:11:17.609849Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e14401c-64c0-47bb-9163-d80145054659 · inbound
MOSAIC: Adaptive Inter-layer Composition for Efficient Heterogeneous Vision-Language Models cites this paper.
MOSAIC: Adaptive Inter-layer Composition for Efficient Heterogeneous Vision-Language Models MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T00:53:20.749426Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a6800d9-0742-4de5-b3a5-7b6ece99915e · inbound
Transforming Rank: How Architecture Navigates the Spectral Pathologies of Depth cites this paper.
Transforming Rank: How Architecture Navigates the Spectral Pathologies of Depth MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:08:34.681235Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 48d550e0-9866-4015-b7a5-8de17b06aa84 · inbound
The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale cites this paper.
The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T06:39:23.351213Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 306bfd41-a9ac-42fe-8b08-b3b61a28e156 · inbound
The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale cites this paper.
The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T02:03:25.363111Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14d80a31-c68c-4dd0-8df0-39123973a78c · inbound
LISA: Linear-Indexed Sparse Attention for Efficient Long-Context Reasoning cites this paper.
LISA: Linear-Indexed Sparse Attention for Efficient Long-Context Reasoning MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:48:54.132284Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c457dcc-ced8-4f86-8e6d-43d37c92b5be · inbound
SOAP, Muon, and Beyond: Pushing LLM Pretraining Scales cites this paper.
SOAP, Muon, and Beyond: Pushing LLM Pretraining Scales MiniMax-01: Scaling Foundation Models with Lightning Attention
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T06:45:16.519251Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.