Paper Citation Record · LEDGER

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs

As of 16 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2504.13989.

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

pith.paper-citation-record.v1
2504.13989 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:09:58.030422Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

verified exact2
verified fuzzy10
unresolved22
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 86c87acc-c3e4-40e3-abe3-74eb8f650ecb · outbound

This paper cites SliceGPT: Compress Large Language Models by Deleting Rows and Columns.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.862024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a34c4ed4-32ad-436f-8bf4-35fce4c08590 · outbound

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

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.868237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd88d39d-ccf9-4868-ba89-3da7d4b87012 · outbound

This paper cites QuIP: 2-Bit Quantization of Large Language Models With Guarantees.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs QuIP: 2-Bit Quantization of Large Language Models With Guarantees

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.664330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d5bc7b90-b37f-4f49-8425-8a3a359e467f · outbound

This paper cites PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.878624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c443f7a-9ca4-4069-9718-ac8d7d5509c5 · outbound

This paper cites PACT: Parameterized Clipping Activation for Quantized Neural Networks.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs PACT: Parameterized Clipping Activation for Quantized Neural Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.884243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 887ca33d-69b4-40f4-83b6-f41838afe2ea · outbound

This paper cites Extreme Value Theory.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Extreme Value Theory

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.890010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98a9f086-ffe8-41c6-9154-f049e085912d · outbound

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

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.649968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f3fad53e-445b-4241-89fc-8796cdd25ec0 · outbound

This paper cites Differentiable Model Compression via Pseudo Quantization Noise.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Differentiable Model Compression via Pseudo Quantization Noise

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.899034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 945fb518-1ac8-4c20-b855-4bbbe0540d1c · outbound

This paper cites Learned Step Size Quantization.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Learned Step Size Quantization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.904252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e535ed3-b364-49a3-90a1-a43a51c32b7f · outbound

This paper cites Improving Quantization with Post-Training Model Expansion.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Improving Quantization with Post-Training Model Expansion

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.908970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6d75e20-6ca4-41cf-a7a5-13c92c0cafb1 · outbound

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

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.914155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 678dfe5d-7c1b-4b41-800e-ae8776face67 · outbound

This paper cites A Survey of Quantization Methods for Efficient Neural Network Inference.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.919431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01b231fd-8970-46e4-984c-bca8458b718a · outbound

This paper cites A Survey on Methods and Theories of Quantized Neural Networks, December.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs A Survey on Methods and Theories of Quantized Neural Networks, December

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.635023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 354b0ca1-5d4c-4b94-bbed-63c07d7d48cf · outbound

This paper cites an unresolved cited work.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-16T12:09:58.618961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2e25ae29-f3d9-4364-88c1-787f9da4977a · outbound

This paper cites RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.942902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc3fbb15-45c0-4248-90d1-0df33063d4f4 · outbound

This paper cites LightRot: A Light-weighted Rotation Scheme and Architecture for Accurate Low-bit Large Language Model Inference.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs LightRot: A Light-weighted Rotation Scheme and Architecture for Accurate Low-bit Large Language Model Inference

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.947393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1365ca31-6124-487e-bd08-2a32bc8d6c9e · outbound

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

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.588625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dafef2af-4617-4a17-8aba-b00585a845e3 · outbound

This paper cites Defensive Quantization: When Efficiency Meets Robustness.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Defensive Quantization: When Efficiency Meets Robustness

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.957446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dcd214c-1bb8-4a84-843c-e8d8c2a2ad43 · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs SpinQuant: LLM quantization with learned rotations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.963040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71a85a44-1d70-456a-96cc-fd5efc3e2973 · outbound

This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.967681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d39f4ec-95d0-4bfb-8a67-4f57637d555f · outbound

This paper cites Applying maximum entropy principle on quantized neural networks correlates with high accuracy.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Applying maximum entropy principle on quantized neural networks correlates with high accuracy

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.572064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 98677ebc-dbe7-41d4-a815-9166739c8b99 · outbound

This paper cites Precision Where It Matters: A Novel Spike Aware Mixed-Precision Quantization Strategy for LLaMA-based Language Models.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Precision Where It Matters: A Novel Spike Aware Mixed-Precision Quantization Strategy for LLaMA-based Language Models

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-16T12:09:58.204110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 410c4b62-7c16-4e36-b806-d58295a603f6 · outbound

This paper cites Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.981017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 013c7246-32a0-4777-89ba-7d53d7b3f38f · outbound

This paper cites Pre- fixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Pre- fixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.557534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 12454ad5-b722-49ec-ad98-6faabe51ba8c · outbound

This paper cites High-Dimensional Probability: An Introduction with Applica- tions in Data Science.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs High-Dimensional Probability: An Introduction with Applica- tions in Data Science

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.541603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4168ccd0-b698-44a5-93f2-d2169f6b5090 · outbound

This paper cites BitNet: Scaling 1-bit Transformers for Large Language Models.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs BitNet: Scaling 1-bit Transformers for Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.998757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9467dd6-8133-4c6c-b586-6606bd970425 · outbound

This paper cites Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:58.003309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6eb51ddc-0838-4d99-b671-2a7da9c3b1c9 · outbound

This paper cites URL https://www.cambridge.org/core/books/ highdimensional-probability/797C466DA29743D2C8213493BD2D2102.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs URL https://www.cambridge.org/core/books/ highdimensional-probability/797C466DA29743D2C8213493BD2D2102

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.994492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4eb85cc4-06d3-474c-8a9a-a8be5437cad0 · outbound

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

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.526112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4b703a1e-00d9-4762-9115-97e6ae4f2b15 · outbound

This paper cites Post- Training Quantization for Re-parameterization via Coarse & Fine Weight Splitting, December.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Post- Training Quantization for Re-parameterization via Coarse & Fine Weight Splitting, December

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.511025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1aa0b935-c05e-4665-934a-2705a729ef38 · outbound

This paper cites DFRot: Achieving Outlier-Free and Massive Activation-Free for Rotated LLMs with Refined Rotation.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs DFRot: Achieving Outlier-Free and Massive Activation-Free for Rotated LLMs with Refined Rotation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:58.007686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2978e13b-6bd7-42fa-bae6-43cb41915d0f · outbound

This paper cites Trained Ternary Quantization.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Trained Ternary Quantization

Reference 32

Resolution: malformed identifier; no resolver link, observed 2026-08-16T12:09:58.030422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66e8fb5d-0f03-434e-a56d-3f6e1f61586a · outbound

This paper cites FracBits: Mixed Precision Quantization via Fractional Bit-Widths.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs FracBits: Mixed Precision Quantization via Fractional Bit-Widths

Reference 35

Resolution: verified exact; doi, observed 2026-08-16T12:09:58.067601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 65212913-0a54-45ac-9ac8-f4e3d0156aee · outbound

This paper cites Google-Books-ID: oR_HDgAAQBAJ.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Google-Books-ID: oR_HDgAAQBAJ

Reference 2012

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:09:58.603826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e5c4ba70-91ae-486f-824d-8ee8454d6a2f · outbound

This paper cites A Survey on Methods and Theories of Quantized Neural Networks.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs A Survey on Methods and Theories of Quantized Neural Networks

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-16T12:09:57.928927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e625a395-fe0c-46c1-9054-e4daead71b42 · outbound

This paper cites Post-Training Quantization for Re-parameterization via Coarse & Fine Weight Splitting.

Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Post-Training Quantization for Re-parameterization via Coarse & Fine Weight Splitting

Reference 2023

Resolution: metadata mismatch; local_arxiv, observed 2026-08-16T12:09:58.124044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.