LLM-QAT: Data-Free Quantization Aware Training for Large Language Models | Paper Citation Record

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A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 262

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Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security cites this paper.

Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 250

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A Survey on Knowledge Distillation of Large Language Models cites this paper.

A Survey on Knowledge Distillation of Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 21

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BitMoD: Bit-serial Mixture-of-Datatype LLM Acceleration cites this paper.

BitMoD: Bit-serial Mixture-of-Datatype LLM Acceleration LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 31

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FASTNav: Fine-tuned Adaptive Small-language-models Trained for Multi-point Robot Navigation cites this paper.

FASTNav: Fine-tuned Adaptive Small-language-models Trained for Multi-point Robot Navigation LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 19

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Anda: Unlocking Efficient LLM Inference with a Variable-Length Grouped Activation Data Format cites this paper.

Anda: Unlocking Efficient LLM Inference with a Variable-Length Grouped Activation Data Format LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 53

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Llama Guard 3-1B-INT4: Compact and Efficient Safeguard for Human-AI Conversations cites this paper.

Llama Guard 3-1B-INT4: Compact and Efficient Safeguard for Human-AI Conversations LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 11

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MiniKV: Pushing the Limits of LLM Inference via 2-Bit Layer-Discriminative KV Cache cites this paper.

MiniKV: Pushing the Limits of LLM Inference via 2-Bit Layer-Discriminative KV Cache LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 16

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SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization cites this paper.

SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 13

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Toward LLM-Agent-Based Modeling of Transportation Systems: A Conceptual Framework cites this paper.

Toward LLM-Agent-Based Modeling of Transportation Systems: A Conceptual Framework LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 71

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Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization cites this paper.

Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 17

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QPruner: Probabilistic Decision Quantization for Structured Pruning in Large Language Models cites this paper.

QPruner: Probabilistic Decision Quantization for Structured Pruning in Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 18

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Deploying Foundation Model Powered Agent Services: A Survey cites this paper.

Deploying Foundation Model Powered Agent Services: A Survey LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 209

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Extracting Interpretable Task-Specific Circuits from Large Language Models for Faster Inference cites this paper.

Extracting Interpretable Task-Specific Circuits from Large Language Models for Faster Inference LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 12

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1.58-bit FLUX cites this paper.

1.58-bit FLUX LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 39

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Observation 481751bf-a3bd-4deb-b46c-a7f9016bfe4a · inbound

SWSC: Shared Weight for Similar Channel in LLM cites this paper.

SWSC: Shared Weight for Similar Channel in LLM LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 6

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Observation 8f7e307b-7fdf-42e2-b184-d7e979a2c9bf · inbound

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach cites this paper.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 25

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Irrational Complex Rotations Empower Low-bit Optimizers cites this paper.

Irrational Complex Rotations Empower Low-bit Optimizers LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 20

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Observation 91f0dd9f-91b1-4b16-9f83-74bc34240102 · inbound

Qrazor: Reliable and Effortless 4-bit LLM Quantization by Significant Data Razoring cites this paper.

Qrazor: Reliable and Effortless 4-bit LLM Quantization by Significant Data Razoring LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 26

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FBQuant: FeedBack Quantization for Large Language Models cites this paper.

FBQuant: FeedBack Quantization for Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 22

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HadamRNN: Binary and Sparse Ternary Orthogonal RNNs cites this paper.

HadamRNN: Binary and Sparse Ternary Orthogonal RNNs LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 2022

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SHARP: Accelerating Language Model Inference by SHaring Adjacent layers with Recovery Parameters cites this paper.

SHARP: Accelerating Language Model Inference by SHaring Adjacent layers with Recovery Parameters LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 54

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RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models cites this paper.

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 21

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Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights cites this paper.

Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 17

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Sampling-Aware Quantization for Diffusion Models cites this paper.

Sampling-Aware Quantization for Diffusion Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 23

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Dual Precision Quantization for Efficient and Accurate Deep Neural Networks Inference cites this paper.

Dual Precision Quantization for Efficient and Accurate Deep Neural Networks Inference LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 4

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LLM-Powered AI Agent Systems and Their Applications in Industry cites this paper.

LLM-Powered AI Agent Systems and Their Applications in Industry LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 83

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NQKV: A KV Cache Quantization Scheme Based on Normal Distribution Characteristics cites this paper.

NQKV: A KV Cache Quantization Scheme Based on Normal Distribution Characteristics LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 28

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Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks cites this paper.

Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 10

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Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs cites this paper.

Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 5

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Large Language models for Time Series Analysis: Techniques, Applications, and Challenges cites this paper.

Large Language models for Time Series Analysis: Techniques, Applications, and Challenges LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 66

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LCD: Advancing Extreme Low-Bit Clustering for Large Language Models via Knowledge Distillation cites this paper.

LCD: Advancing Extreme Low-Bit Clustering for Large Language Models via Knowledge Distillation LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 2023

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RLRC: Reinforcement Learning-based Recovery for Compressed Vision-Language-Action Models cites this paper.

RLRC: Reinforcement Learning-based Recovery for Compressed Vision-Language-Action Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 12

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Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 224

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CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs cites this paper.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 22

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Is Quantization a Deal-breaker? Empirical Insights from Large Code Models cites this paper.

Is Quantization a Deal-breaker? Empirical Insights from Large Code Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 9

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GeLaCo: An Evolutionary Approach to Layer Compression cites this paper.

GeLaCo: An Evolutionary Approach to Layer Compression LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 29

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P-CoT: A Pedagogically-motivated Participatory Chain-of-Thought Prompting for Phonological Reasoning in LLMs cites this paper.

P-CoT: A Pedagogically-motivated Participatory Chain-of-Thought Prompting for Phonological Reasoning in LLMs LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 33

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SiLQ: Simple Large Language Model Quantization-Aware Training cites this paper.

SiLQ: Simple Large Language Model Quantization-Aware Training LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 17

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Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models cites this paper.

Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 19

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Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs cites this paper.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 33

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LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving cites this paper.

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 17

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MoPEQ: Mixture of Mixed Precision Quantized Experts cites this paper.

MoPEQ: Mixture of Mixed Precision Quantized Experts LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 30

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LUQ: Layerwise Ultra-Low Bit Quantization for Multimodal Large Language Models cites this paper.

LUQ: Layerwise Ultra-Low Bit Quantization for Multimodal Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 24

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Observation 5aa9d5ee-59f6-4577-a69f-6dc488c1ad3f · inbound

BPDQ: Bit-Plane Decomposition Quantization on a Variable Grid for Large Language Models cites this paper.

BPDQ: Bit-Plane Decomposition Quantization on a Variable Grid for Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 14

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Observation 99a03ff7-decc-4925-a042-982722ce978a · inbound

Efficient Reasoning on the Edge cites this paper.

Efficient Reasoning on the Edge LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 107

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Network Edge Inference for Large Language Models: Principles, Techniques, and Opportunities cites this paper.

Network Edge Inference for Large Language Models: Principles, Techniques, and Opportunities LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 102

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:16:10.233740Z

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Observation 2b7bf740-18a7-4fc2-ada3-ce9aacb42f57 · inbound

TACO: Efficient Communication Compression of Intermediate Tensors for Scalable Tensor-Parallel LLM Training cites this paper.

TACO: Efficient Communication Compression of Intermediate Tensors for Scalable Tensor-Parallel LLM Training LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:06:20.891028Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6fd73307-f20b-441f-965b-172e3d7715b0 · inbound

EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation cites this paper.

EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:35:56.887863Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 266fad7a-5546-4724-bb32-a6709a8833ea · inbound

EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation cites this paper.

EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-22T10:11:23.356051Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 28ce22ae-d57c-40da-ad06-40416af41d00 · inbound

HCInfer: An Efficient Inference System via Error Compensation for Resource-Constrained Devices cites this paper.

HCInfer: An Efficient Inference System via Error Compensation for Resource-Constrained Devices LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:41:10.681776Z

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Observation e3843bdb-a752-48ff-9ca0-fffe80ead469 · inbound

XPERT: Expert Knowledge Transfer for Effective Training of Language Models cites this paper.

XPERT: Expert Knowledge Transfer for Effective Training of Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T02:46:18.799055Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9ad7c572-8576-4b14-8845-366755fe2af3 · inbound

BCJR-QAT: A Differentiable Relaxation of Trellis-Coded Weight Quantization cites this paper.

BCJR-QAT: A Differentiable Relaxation of Trellis-Coded Weight Quantization LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:26:25.727040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 38f4a9b2-7c09-4795-a7ef-acd6cbbae7f0 · 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 LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:42:36.014542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aaee0fdb-94f6-4ace-afe8-cbe02ab12f38 · inbound

Recover-LoRA for Aggressive Quantization: Reclaiming Accuracy in 2-Bit Language Models via Low-Rank Adaptation with Knowledge Distillation on Synthetic Data cites this paper.

Recover-LoRA for Aggressive Quantization: Reclaiming Accuracy in 2-Bit Language Models via Low-Rank Adaptation with Knowledge Distillation on Synthetic Data LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:46:28.224995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d8416cfb-f7f3-4e63-94e1-1b104d227f3d · inbound

STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models cites this paper.

STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 135

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T07:06:43.737459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 286b2fae-86ac-46f0-8c2b-dea804c6ea59 · inbound

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization cites this paper.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:57:38.374568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a5a612fb-9ba0-40d2-b5d0-995de1e16987 · inbound

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization cites this paper.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:47:25.227142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7c9714d8-5af6-46b3-8cb6-4e0d3cca6ce8 · inbound

On the Expressive Power of Weight Quantization in Large Language Models cites this paper.

On the Expressive Power of Weight Quantization in Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:19:44.249942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3ae913f0-da22-43de-a08e-792808a197f3 · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 149

Resolution: verified exact; arxiv_id, observed 2026-07-04T11:09:46.246173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bac2f086-923e-4241-b59c-aae7c865516d · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 138

Resolution: unresolved; no resolver link, observed 2026-08-02T10:27:18.290805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 839d221e-91aa-4df9-b8a0-6d5be99aabdd · inbound

Reliability Scaling Laws for Quantized Large Language Models cites this paper.

Reliability Scaling Laws for Quantized Large Language Models LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 90

Resolution: unresolved; no resolver link, observed 2026-07-14T08:45:52.855783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19cb1add-ad6b-41f6-ae63-a819d29e2108 · inbound

Constraint-Driven Model Optimization: An Industry Framework for Selecting Compression and Acceleration Techniques in Modern Machine Learning Systems cites this paper.

Constraint-Driven Model Optimization: An Industry Framework for Selecting Compression and Acceleration Techniques in Modern Machine Learning Systems LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:40.665371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b130432c-3936-4f38-9d1e-dd118626a477 · inbound

Quantize with Confidence? An Empirical Study of Quantization for Code Generation cites this paper.

Quantize with Confidence? An Empirical Study of Quantization for Code Generation LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T03:32:51.848447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9853d2b9-d422-4a99-a51a-3afc791542a9 · inbound

High-accuracy Low-Bit KV-Cache Quantization via Local Distribution Restoration cites this paper.

High-accuracy Low-Bit KV-Cache Quantization via Local Distribution Restoration LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T09:50:32.862421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4aa58001-ee2b-486f-ab5f-c93f5be466fe · inbound

Recurrent Residual Quantization: A Progressive Multi-Precision Representation for LLMs cites this paper.

Recurrent Residual Quantization: A Progressive Multi-Precision Representation for LLMs LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T00:50:44.544992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05ac9e87-1a78-4d22-855b-823d91bc8940 · inbound

Hidden Language Consistency Phenomena in Reasoning LLMs cites this paper.

Hidden Language Consistency Phenomena in Reasoning LLMs LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 224

Resolution: unresolved; no resolver link, observed 2026-08-14T04:40:10.085670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers