Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 47 inbound Pith citation observations for arXiv:2305.17888.

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

pith.paper-citation-record.v1
2305.17888 v1

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measured 47 of 47 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 47 of 47 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:44:00.570594Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T11:09:46.244627Z

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Outbound references

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Pith citing papers

Observation 1c207117-7a1b-4e98-831a-23616c41c4d2 · inbound

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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Observation 6b0f978d-4f28-49b7-bb0a-4e9f5c9dfc7f · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-17T00:57:26.711473Z

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Observation 7121c958-3f02-4e9d-83a0-eea923e4a4b1 · inbound

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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Observation 9bbb9f5b-f553-4d78-9461-5702cce38c02 · inbound

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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Observation c06bde00-4f54-477a-8dbb-b25bd8c9a328 · inbound

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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Observation 81f0e293-f8b7-4e9a-b481-24719f66a559 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-22T20:25:05.451215Z

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Observation 583417e6-2d07-44e2-b63e-987611b1c3f9 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:01:45.919541Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1c5fd896-d33d-4a13-8799-4efc3d93369b · inbound

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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Observation caf7d4d2-56b2-44f8-b527-c5be0de26c88 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:06:37.842283Z

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Observation 5e902144-9c07-4180-814a-abc23a3d27a2 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:29.098589Z

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Observation 67488c36-47eb-4299-9576-bf38307e1c8c · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-07T14:01:55.320202Z

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Observation 87080d35-f0c3-421d-aa94-a84a33b5ce14 · inbound

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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Observation 0ba1c425-02c2-4533-b9fb-70d751a16708 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-07T15:26:56.140382Z

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Observation 090a4bb0-5d7c-4879-a42f-42dba738a588 · inbound

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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Observation ca8dafa3-68f8-4ed1-9907-6282d399f474 · inbound

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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Observation 8bbdf5b2-1fec-48e1-8abf-b6f612c7051e · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:39.922662Z

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Observation e4e182b3-3f62-43ad-a85b-9b4b60d23d5c · inbound

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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Observation c07aea92-73a5-43bf-82c5-40e55bf5a083 · inbound

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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Observation 726f3140-9b51-40c8-a4b6-70696cff27e1 · inbound

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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Observation 0ffd1ac8-21f6-4831-918e-aa7eb7a08017 · inbound

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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Observation b814e3ab-99ec-4300-aa5e-a2060109a7fe · inbound

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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Observation 6bac20f3-ce57-498f-bc25-413a448e58bd · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:44:26.498527Z

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Observation df962eed-6dcd-46ac-a387-c1fc943dcf18 · inbound

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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Observation bbe18e3d-6411-4361-856c-30c03ce71e59 · inbound

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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Observation e1221fe7-79bb-48e0-85a3-a87b018c6443 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-04T14:45:26.761488Z

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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

Resolution: verified exact; arxiv_id, observed 2026-05-21T14:14:12.407962Z

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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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Unavailable: canonical work link unavailable.

Observation 790ad2c6-76d0-4f87-a730-69c21fefbf6f · inbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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

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Source-reported events for the cited work

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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

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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

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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

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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

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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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.