Paper Citation Record · LEDGER

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference

As of 13 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 3 inbound Pith citation observations for arXiv:2411.09909.

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

pith.paper-citation-record.v1
2411.09909 v2

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:16:46.747885Z

measured 82 of 82 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T03:16:46.835670Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T12:59:52.375868Z

Reference resolution

79 of 79 outbound references displayed

verified exact2
verified fuzzy3
unresolved74
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0d460748-316d-4f29-a5eb-0f26fa8cb920 · outbound

This paper cites online" 'onlinestring :=.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference online" 'onlinestring :=

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.517088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf838b11-4be0-4810-b88d-4dec84d265d5 · outbound

This paper cites write newline.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference write newline

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.521589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebfd8705-b48b-48ef-bf13-95d54bc8b407 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.525283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4c2b85f-a07b-4b03-9a83-0c33f9a26bc9 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.368826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 13fbc01c-44c9-4716-870b-2e81031b9dd4 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.360499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2d286ca5-3897-446b-a575-0f6218b5b895 · outbound

This paper cites QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.534082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eda7b5f6-7952-4f5f-a673-5a2778e96b81 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.352758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 563bb0bf-9cd4-443a-9e66-6c70ac8e21ae · outbound

This paper cites Qwen Technical Report.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Qwen Technical Report

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.539843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f413fdbb-acfb-4811-86ba-02fb4eead817 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.543084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50af3c53-4d5f-416e-8a46-40b90b78cdbc · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.545876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07c3ac3d-0e86-4caa-b235-1aef1d972794 · outbound

This paper cites PIQA: Reasoning about Physical Commonsense in Natural Language.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference PIQA: Reasoning about Physical Commonsense in Natural Language

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.548487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b81a593-743a-400f-9d8b-4014efaaddaa · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.551310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee243534-41c6-4c08-8b73-9688da854d78 · outbound

This paper cites Gonzalez, Ion Stoica, and Eric P.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Gonzalez, Ion Stoica, and Eric P

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.554389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bfb5f54-b4a3-48c2-b0fa-199767b1be8d · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference PaLM: Scaling Language Modeling with Pathways

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.556896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e60c6ff8-8a2b-41e7-b58d-ea1b114a9a9d · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Scaling Instruction-Finetuned Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.560380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e4bb3f4-d7f8-4132-8b18-fc3313137805 · outbound

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

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.563263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ed7fd9a-fe96-4193-b115-6024d96eaa95 · outbound

This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher R \'e.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Fu, Stefano Ermon, Atri Rudra, and Christopher R \'e

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.566248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4536c922-63af-44a6-be35-9959e1d9a8c2 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.331887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1ab0b232-5cf3-40b0-82b6-368e87fdc3ee · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.323701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c706b531-79c9-4b92-bbe5-9110db99ea0e · outbound

This paper cites Smith, and Matt Gardner.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Smith, and Matt Gardner

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:16:47.315768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e54a6312-435c-455a-90b1-0fdbfff593f4 · outbound

This paper cites LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.578279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e25b3d9e-209f-4ae5-bf4c-092760074120 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.581309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3332f99-edfb-4edd-aaa1-4eedf84fd08f · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.584962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3197a6e4-472f-4ae2-aa3b-95ada8f2e357 · outbound

This paper cites Abdelfattah, and Zhiru Zhang.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Abdelfattah, and Zhiru Zhang

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:16:47.300512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c5c4604a-2733-4f42-b29c-4e625847a735 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.293036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7b2e7694-2335-4d9d-b5b8-edca112359ab · outbound

This paper cites Scaling FP8 training to trillion-token LLMs.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Scaling FP8 training to trillion-token LLMs

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.594244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ba84230-b79b-43cd-ad8b-b82909b18fdb · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.596839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69cdb015-3074-4cd5-b8ab-3e5f9b158548 · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.599573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63cccda5-926e-4526-ab36-ab4b5c9881f3 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.602876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 368967e6-692d-43c4-9edc-7c1459819689 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.605476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50aa5b5f-b1a1-4d66-be6e-39e4de09344e · outbound

This paper cites LongCoder: A Long-Range Pre-trained Language Model for Code Completion.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference LongCoder: A Long-Range Pre-trained Language Model for Code Completion

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.608195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4c9acbb-516e-44a4-aa2a-54b395317d14 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Measuring Massive Multitask Language Understanding

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.610981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9eecf7c1-d121-41f4-bd88-b6bf5439c615 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.613870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e0fa700-8c61-4116-b3b7-53be4ba81543 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.284778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6eef2742-e735-41ad-a0fd-0631197cfb31 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.620217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c33963b-fd18-4f7a-9b7e-ceb50584974f · outbound

This paper cites Mistral 7B.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Mistral 7B

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.623213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf9ea5c7-07fe-4bc2-a88b-09a9239be50b · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.626010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e66241e-dc7f-49c6-adfb-8d2b5cf0843c · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.277385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9d37dadb-4fe5-4391-b751-9a63b5b98e21 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 39

Resolution: verified exact; doi, observed 2026-08-12T20:16:46.795920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9e339107-6273-4aa5-8ed1-9832a013d7f6 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 40

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9266036b-fa14-475d-aee1-05fdf4ef0e8f · outbound

This paper cites BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.639127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e33d2094-bee8-46f6-adc3-3d172eb57815 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.642032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e676f87-8c6a-47ab-9036-4de3395d07b9 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.644368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39d0738e-51c1-4a97-8582-1198dab4ba52 · outbound

This paper cites DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.646879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e2dd394-8023-4a0e-9c34-571a6de17b2c · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.260737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e04ec32e-c4a6-43f5-a1f6-4ae013878da7 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.253107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6e828ef5-327d-4346-a2cb-42b3ee3f33a9 · outbound

This paper cites RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.656140Z

Source-reported events for the cited work

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Observation d6958d14-fbe6-4985-b9c9-8cce1dea6218 · outbound

This paper cites OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.658807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ce9b41c-6cd5-4359-9753-7a1d93d68248 · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference SpinQuant: LLM quantization with learned rotations

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.662054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 719ecbe5-de22-479a-8281-1572c51b0eae · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.665073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bff8dcee-48cd-41da-a4f5-def0dc198e0a · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.667728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29d5dffc-4652-49f3-8d13-0e072fddf65e · outbound

This paper cites Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.670974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 475e6bb7-ca06-4bbb-b84f-c67292ad7304 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.673503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 274d9692-60bc-46fb-be65-dc868ff411c7 · outbound

This paper cites DocVQA: A Dataset for VQA on Document Images.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference DocVQA: A Dataset for VQA on Document Images

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.676547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 406b99c7-4d5a-4802-8544-1b80e0badd67 · outbound

This paper cites Pointer Sentinel Mixture Models.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Pointer Sentinel Mixture Models

Reference 55

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Observation cee0afab-6c7b-4040-8139-df357b4f4d3b · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.238009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f22c19de-987f-4625-b303-9f8d3bafe8c0 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.229980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a57013cb-b83e-47ed-af12-646ed71bbda7 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.222113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f7f9d3e4-0d1c-47c7-ac48-0792f0a3bb1c · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.214095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3b552fd3-73a4-4e2b-9e02-d70ad1f55b1f · outbound

This paper cites National Library of Medicine.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference National Library of Medicine

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:16:47.205646Z

Source-reported events for the cited work

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Observation 855957e0-90b2-49ad-bf51-9b254fc4292d · outbound

This paper cites GPT-4 Technical Report.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference GPT-4 Technical Report

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.696011Z

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Observation e5039859-6dcd-444f-add7-23117a3ffb31 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.197981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 959aa0db-96b4-4463-baca-1b0164f3a122 · outbound

This paper cites Microscaling Data Formats for Deep Learning.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Microscaling Data Formats for Deep Learning

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.702310Z

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Observation 233440c6-1f6a-4248-94fb-62b943b0f6db · outbound

This paper cites WinoGrande: An Adversarial Winograd Schema Challenge at Scale.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.705431Z

Source-reported events for the cited work

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Observation 6b07a9bc-7d49-465c-aecf-d4947494b0d7 · outbound

This paper cites Liu, and Christopher D.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Liu, and Christopher D

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.708230Z

Source-reported events for the cited work

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Observation 399f52ff-eb12-486c-8145-99a13d5b7267 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.189993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 70331bae-2b1c-44ad-b827-077b23075f1c · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.713372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d63e50f-86d5-4c88-8cd4-b45a709f5f74 · outbound

This paper cites CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.715882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d478789e-a5be-46ab-9df2-25ccdb0e66ab · outbound

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

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.718730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18f74528-6290-4488-86f9-6cfdf8c83eb2 · outbound

This paper cites SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.721707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b86b6525-42cd-4585-bcb5-ceab0b2f929b · outbound

This paper cites Mitigating Quantization Errors Due to Activation Spikes in GLU-Based LLMs.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Mitigating Quantization Errors Due to Activation Spikes in GLU-Based LLMs

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.724558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48bbc508-8b13-4666-8fc8-4c23abf3b39d · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.727389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33696941-02df-4e16-8aa2-cf8defcd300c · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.177972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d46cc071-ab06-4c1a-85bf-2234bf421842 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.733080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f13e054f-ab6f-40b2-8048-3896da884190 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:16:47.169847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5e7e5004-a446-457f-b8d4-e5f111b71744 · outbound

This paper cites LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.738832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b61d2b81-d828-4234-8750-e2005d9a4c6e · outbound

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

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference OPT: Open Pre-trained Transformer Language Models

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.741608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc2cb726-04c6-495a-af4e-0c6b8cbd3a33 · outbound

This paper cites an unresolved cited work.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Unresolved cited work

Reference 78

Resolution: verified exact; doi, observed 2026-08-12T20:16:46.770555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ce9bb16b-6252-4a50-b9ac-bab01567b1f2 · outbound

This paper cites Gonzalez, and Ion Stoica.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Gonzalez, and Ion Stoica

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-12T20:16:46.747885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 8321e320-30be-4ab1-ad6c-6aca5d875991 · inbound

SharQ: Bridging Activation Sparsity and FP4 Quantization for LLM Inference cites this paper.

SharQ: Bridging Activation Sparsity and FP4 Quantization for LLM Inference AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:59:52.377428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3face000-3f1b-4ca2-8d4d-6d25804bea43 · inbound

GyRot: Leveraging Hidden Synergy between Rotation and Fine-grained Group Quantization for Low-bit LLM Inference cites this paper.

GyRot: Leveraging Hidden Synergy between Rotation and Fine-grained Group Quantization for Low-bit LLM Inference AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T03:16:46.835670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50a66e32-18a7-4fe6-a72a-821c7fa425e8 · inbound

LightRot: A Light-Weighted Rotation Scheme and Architecture for Accurate Low-Bit Large Language Model Inference cites this paper.

LightRot: A Light-Weighted Rotation Scheme and Architecture for Accurate Low-Bit Large Language Model Inference AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T03:01:45.534266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.