Paper Citation Record · LEDGER

EfQAT: An Efficient Framework for Quantization-Aware Training

As of 22 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 5 inbound Pith citation observations for arXiv:2411.11038.

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

pith.paper-citation-record.v1
2411.11038 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:06:18.400866Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:26:47.095465Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy2
unresolved22
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation fc95658c-a858-40da-a293-a7cbc2001775 · outbound

This paper cites QUIK: Towards End-to-End 4-Bit Inference on Generative Large Language Models.

EfQAT: An Efficient Framework for Quantization-Aware Training QUIK: Towards End-to-End 4-Bit Inference on Generative Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.340688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5578bc1-a225-48de-9fa8-042e90d719de · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

EfQAT: An Efficient Framework for Quantization-Aware Training PaLM: Scaling Language Modeling with Pathways

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.352036Z

Source-reported events for the cited work

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Observation 882f3586-3f01-4868-ae5a-38b85f0a12e9 · outbound

This paper cites SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression.

EfQAT: An Efficient Framework for Quantization-Aware Training SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.357781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44e10853-2e57-440b-a80e-de5049643793 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

EfQAT: An Efficient Framework for Quantization-Aware Training BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.360444Z

Source-reported events for the cited work

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Observation a28fc436-bcb7-48c8-94c4-cffc42dcebc2 · outbound

This paper cites Sharpness-Aware Minimization for Efficiently Improving Generalization.

EfQAT: An Efficient Framework for Quantization-Aware Training Sharpness-Aware Minimization for Efficiently Improving Generalization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.365535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9b75f70-055b-4883-9404-b9fb2d5e5239 · outbound

This paper cites Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning.

EfQAT: An Efficient Framework for Quantization-Aware Training Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.368478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dba140b1-9515-4d69-92d4-64c0fb456701 · outbound

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

EfQAT: An Efficient Framework for Quantization-Aware Training GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.371280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fce9b5e-2e95-4275-9023-802644d8b28a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

EfQAT: An Efficient Framework for Quantization-Aware Training Adam: A Method for Stochastic Optimization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.376609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecfaafdc-0356-43df-88d1-c5048b38d10d · outbound

This paper cites A White Paper on Neural Network Quantization.

EfQAT: An Efficient Framework for Quantization-Aware Training A White Paper on Neural Network Quantization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.379029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ba679c8-0e83-4367-afb9-a307c21a5c56 · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

EfQAT: An Efficient Framework for Quantization-Aware Training SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.381386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4bcb6c4-6970-4d12-a86e-4f06c582241f · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

EfQAT: An Efficient Framework for Quantization-Aware Training HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.386609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bff13d3-38d5-47be-b73b-59aca6490406 · outbound

This paper cites Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation.

EfQAT: An Efficient Framework for Quantization-Aware Training Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.389380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49ee58e8-5185-4521-b9b2-f273e969351f · outbound

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

EfQAT: An Efficient Framework for Quantization-Aware Training SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.392175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f41e075-36e8-4339-9937-0ccabc18468f · outbound

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

EfQAT: An Efficient Framework for Quantization-Aware Training OPT: Open Pre-trained Transformer Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.394680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fe7d26c-a55b-458e-bcdb-a8e38a086084 · outbound

This paper cites DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients.

EfQAT: An Efficient Framework for Quantization-Aware Training DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.396786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47c6e67f-2c55-4851-97fa-b317993d6517 · outbound

This paper cites Figure 4 shows the result of two different frequencies over the EfQAT-CWPN in the BERTbase and ResNet-50.

EfQAT: An Efficient Framework for Quantization-Aware Training Figure 4 shows the result of two different frequencies over the EfQAT-CWPN in the BERTbase and ResNet-50

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:06:18.560325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bb5b081d-313b-45a0-b094-1630d4424dd7 · outbound

This paper cites Following (Jain et al., 2020), we apply the activation functions only over the scales and train the zero points without any activation function.

EfQAT: An Efficient Framework for Quantization-Aware Training Following (Jain et al., 2020), we apply the activation functions only over the scales and train the zero points without any activation function

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:06:18.552279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7cd5f7be-0a3d-4368-9fe4-003da7ce7386 · outbound

This paper cites SQuAT: Sharpness- and Quantization-Aware Training for BERT.

EfQAT: An Efficient Framework for Quantization-Aware Training SQuAT: Sharpness- and Quantization-Aware Training for BERT

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.384092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 859608bf-5a03-4ca8-b2e0-76f0d2347722 · outbound

This paper cites Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks.

EfQAT: An Efficient Framework for Quantization-Aware Training Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.373901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0513012-b79a-406c-a485-5313f3fd0288 · outbound

This paper cites Learned Step Size Quantization.

EfQAT: An Efficient Framework for Quantization-Aware Training Learned Step Size Quantization

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.363058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ea6aa24-401f-4b6e-abe4-502d5ded98e5 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

EfQAT: An Efficient Framework for Quantization-Aware Training Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.346608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f965f167-730e-4ba6-ab2d-2afc36304b78 · outbound

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

EfQAT: An Efficient Framework for Quantization-Aware Training PACT: Parameterized Clipping Activation for Quantized Neural Networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.349322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7947f0d-0581-45de-b3f3-4be907cd5de0 · outbound

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

EfQAT: An Efficient Framework for Quantization-Aware Training LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.354852Z

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Unavailable: canonical work link unavailable.

Observation c00768ac-3bd7-49c2-80ad-523f689202fd · outbound

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

EfQAT: An Efficient Framework for Quantization-Aware Training QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-12T19:06:18.343994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9ccf9268-b262-4640-92ad-41ce913d4410 · inbound

Automatic mixed precision for optimizing gained time with constrained loss mean-squared-error based on model partition to sequential sub-graphs cites this paper.

Automatic mixed precision for optimizing gained time with constrained loss mean-squared-error based on model partition to sequential sub-graphs EfQAT: An Efficient Framework for Quantization-Aware Training

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T20:26:47.095465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ee2f8ee-5d9a-4f9b-81fb-163df8b26359 · inbound

Layer-wise Quantization for Quantized Optimistic Dual Averaging cites this paper.

Layer-wise Quantization for Quantized Optimistic Dual Averaging EfQAT: An Efficient Framework for Quantization-Aware Training

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:02.930476Z

Source-reported events for the cited work

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Observation dfcd2b72-9b58-4ea1-9a4e-41cfe20b3d14 · inbound

A Vision Toward Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents cites this paper.

A Vision Toward Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents EfQAT: An Efficient Framework for Quantization-Aware Training

Reference 144

Resolution: unresolved; no resolver link, observed 2026-08-04T08:12:23.454385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ae5ccbc-9109-4986-aa43-7734560a851a · inbound

The Thermodynamic Costs of Simple Linear Regression cites this paper.

The Thermodynamic Costs of Simple Linear Regression EfQAT: An Efficient Framework for Quantization-Aware Training

Reference 80

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:03:23.187625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0a4753d7-4c9b-4158-9627-0f7706d06ee5 · inbound

GNMR: Runtime Stability Control for Low-Precision Large Language Model Training cites this paper.

GNMR: Runtime Stability Control for Low-Precision Large Language Model Training EfQAT: An Efficient Framework for Quantization-Aware Training

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:42:36.040255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.