Paper Citation Record · LEDGER

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models

As of 21 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2501.18154.

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

pith.paper-citation-record.v1
2501.18154 v1

Coverage vector

measured 41 of 41 reference resolution

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

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Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation acb9be1f-2fe1-45fd-8d0d-2068e121ab57 · outbound

This paper cites GPT-4 Technical Report.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models GPT-4 Technical Report

Reference 1

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Observation 0e7b122b-58eb-4841-9a9d-f968a9dcbaf9 · outbound

This paper cites Open and ef- ficient foundation language models,.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Open and ef- ficient foundation language models,

Reference 2

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This paper cites The Application of Large Language Models in Recommendation Systems.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models The Application of Large Language Models in Recommendation Systems

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This paper cites MT-Bench-101: A Fine-Grained Benchmark for Evaluating Large Language Models in Multi-Turn Dialogues.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models MT-Bench-101: A Fine-Grained Benchmark for Evaluating Large Language Models in Multi-Turn Dialogues

Reference 4

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This paper cites GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models

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This paper cites A Hybrid Attention Framework for Fake News Detection with Large Language Models.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models A Hybrid Attention Framework for Fake News Detection with Large Language Models

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Unresolved cited work

Reference 7

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Observation 7cfd952e-a759-4629-b72f-f627a5b5fa49 · outbound

This paper cites Measuring massive multitask language understanding,.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Measuring massive multitask language understanding,

Reference 8

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Observation bd76a265-24e2-480c-bef1-de1bddc44f09 · outbound

This paper cites ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models

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This paper cites Optimization of Transformer heart disease prediction model based on particle swarm optimization algorithm.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Optimization of Transformer heart disease prediction model based on particle swarm optimization algorithm

Reference 10

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This paper cites Enhancing User Intent for Recommendation Systems via Large Language Models.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Enhancing User Intent for Recommendation Systems via Large Language Models

Reference 11

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Observation 90283f29-66c3-44f4-a200-ab0eb405b06c · outbound

This paper cites An empirical study of LLaMA3 quantization: from LLMs to MLLMs.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models An empirical study of LLaMA3 quantization: from LLMs to MLLMs

Reference 12

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This paper cites Spqr: A sparse- quantized representation for near-lossless LLM weight compression,.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Spqr: A sparse- quantized representation for near-lossless LLM weight compression,

Reference 13

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This paper cites Degree-quant: Quantization-aware training for graph neural networks,.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Degree-quant: Quantization-aware training for graph neural networks,

Reference 14

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This paper cites Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach

Reference 15

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Observation 04c364e9-8a8b-4dac-b64f-0a754ec5e16e · outbound

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

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 16

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Observation f2b2f3ba-0a87-4452-91bc-7e231d123e2a · outbound

This paper cites Billm: Pushing the limit of post-training quantization for llms,.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Billm: Pushing the limit of post-training quantization for llms,

Reference 17

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Observation 7cc529cb-c5a9-48c5-8de3-618528649aba · outbound

This paper cites PB-LLM: partially binarized large language models,.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models PB-LLM: partially binarized large language models,

Reference 18

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Observation fb26b0bd-29ea-486f-962c-08cb68a98fe6 · outbound

This paper cites SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models

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This paper cites Analysis of the cholesky decomposition of a semi- definite matrix,.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Analysis of the cholesky decomposition of a semi- definite matrix,

Reference 20

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Pointer sentinel mixture models,

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Observation 66f4aabe-d65e-48cc-904c-8e32a4f383f7 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 22

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models LLM-QAT: data-free quantization aware training for large language models,

Reference 23

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Observation c6f02741-6a47-41f0-be9f-9b9742d20e33 · outbound

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Qlora: Efficient finetuning of quantized llms,

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models BRECQ: pushing the limit of post-training quantization by block reconstruction,

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Zeroquant: Efficient and affordable post-training quantization for large- scale transformers,

Reference 26

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Awq: Activation-aware weight quanti- zation for on-device llm compression and acceleration,

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Supervised neural networks for the clas- sification of structures,

Reference 28

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Observation 7c7a2766-a21e-47ab-a779-3441a97346b0 · outbound

This paper cites Substructure aware graph neural networks,.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Substructure aware graph neural networks,

Reference 29

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Observation f9ac68ba-8f22-48c8-b3ab-f5fa57c6eb95 · outbound

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models A new model for learning in graph domains,

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models The graph neural network model,

Reference 31

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models A simple graph neural network via layer sniffer,

Reference 32

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Rethinking random walk in graph representation learning,

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Deep graph clustering via dual correlation reduction,

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Observation 41984acf-84d1-4a43-b4d8-7f602e240b6d · outbound

This paper cites A Survey of Deep Graph Clustering: Taxonomy, Challenge, Application, and Open Resource.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models A Survey of Deep Graph Clustering: Taxonomy, Challenge, Application, and Open Resource

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Simple Contrastive Graph Clustering

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Hard sample aware network for contrastive deep graph clustering,

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Attribute and structure preserving graph con- trastive learning,

Reference 39

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Observation 443a6186-8467-4df7-9307-9034bd3747ef · outbound

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Semi-supervised classification with graph convolutional networks,

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Observation 91b91bcc-ae0b-48b7-b46c-ef1f978d08f9 · outbound

This paper cites AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration.

Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

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Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models Categorical reparameterization with gumbel-softmax,

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Pith citing papers

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