Paper Citation Record · LEDGER

Low-Rank Quantization-Aware Training for LLMs

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2406.06385.

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

pith.paper-citation-record.v1
2406.06385 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:59:47.692975Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T23:14:01.452007Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d150909c-3950-405c-8c12-b12358e4a58a · inbound

FineGates: LLMs Finetuning with Compression using Stochastic Gates cites this paper.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Low-Rank Quantization-Aware Training for LLMs

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:38.968326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b702a118-15d6-4df0-a959-82e74271d743 · 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 Low-Rank Quantization-Aware Training for LLMs

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T23:03:44.553156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9df94a9e-ee01-4cf2-b66a-919db0ec728f · inbound

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models cites this paper.

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models Low-Rank Quantization-Aware Training for LLMs

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T11:59:47.692975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1768de1f-a55d-48c9-be05-903aee41c92e · inbound

FPTQuant: Function-Preserving Transforms for LLM Quantization cites this paper.

FPTQuant: Function-Preserving Transforms for LLM Quantization Low-Rank Quantization-Aware Training for LLMs

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T10:43:45.907542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95c57692-4605-4118-8f34-aaaddd32e8b6 · inbound

Fine-tuning on simulated data outperforms prompting for agent tone of voice cites this paper.

Fine-tuning on simulated data outperforms prompting for agent tone of voice Low-Rank Quantization-Aware Training for LLMs

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T19:42:00.899573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 866efa00-67b3-4e79-9ef7-4b994c45f1be · 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 Low-Rank Quantization-Aware Training for LLMs

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T12:50:59.043745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87dc17b7-445b-46a2-b2a7-c7bf588eae24 · inbound

Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization's Impact on VLMs Beyond Accuracy cites this paper.

Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization's Impact on VLMs Beyond Accuracy Low-Rank Quantization-Aware Training for LLMs

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:56:26.509064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 92241619-0582-43c3-bb64-555f45638541 · inbound

Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization's Impact on VLMs Beyond Accuracy cites this paper.

Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization's Impact on VLMs Beyond Accuracy Low-Rank Quantization-Aware Training for LLMs

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:30:44.119454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 989058f6-8f66-45a9-b492-b020fc034f65 · inbound

AutoNeural: Co-Designing Vision-Language Models for NPU Inference cites this paper.

AutoNeural: Co-Designing Vision-Language Models for NPU Inference Low-Rank Quantization-Aware Training for LLMs

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T18:56:57.732475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d5c7a40-b5ae-4da2-a035-cc3c28fa5eac · inbound

Efficient Reasoning on the Edge cites this paper.

Efficient Reasoning on the Edge Low-Rank Quantization-Aware Training for LLMs

Reference 116

Resolution: unresolved; no resolver link, observed 2026-07-13T23:28:12.790404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3275157-da9c-4874-8c30-a54b3b5b9f2c · inbound

Cool-chic 5.0: Faster Encoding and Inter-Feature Entropy Modeling for Overfitted Image Compression cites this paper.

Cool-chic 5.0: Faster Encoding and Inter-Feature Entropy Modeling for Overfitted Image Compression Low-Rank Quantization-Aware Training for LLMs

Reference 47

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T22:51:22.985151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8d55fdac-b78e-4512-8a21-2b2d8bad1f53 · inbound

Cool-chic 5.0: Faster Encoding and Inter-Feature Entropy Modeling for Overfitted Image Compression cites this paper.

Cool-chic 5.0: Faster Encoding and Inter-Feature Entropy Modeling for Overfitted Image Compression Low-Rank Quantization-Aware Training for LLMs

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T02:24:01.283347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2648af3e-78bb-45e4-959a-fb91fd579b3e · inbound

Compander-Aligned Query Geometry for Quantized Zeroth-Order Optimization cites this paper.

Compander-Aligned Query Geometry for Quantized Zeroth-Order Optimization Low-Rank Quantization-Aware Training for LLMs

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:56:21.895254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fd7ca9fb-fbfc-4c16-971b-26c392e99c20 · inbound

Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models cites this paper.

Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models Low-Rank Quantization-Aware Training for LLMs

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T05:23:03.674858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 98e0c01e-a919-441c-8858-511681d5e62c · inbound

Quant.npu: Enabling Efficient Mobile NPU Inference for on-device LLMs via Fully Static Quantization cites this paper.

Quant.npu: Enabling Efficient Mobile NPU Inference for on-device LLMs via Fully Static Quantization Low-Rank Quantization-Aware Training for LLMs

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T07:54:02.623919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a010152d-c889-4d9e-b4dc-aef662402b25 · inbound

Mapping the Schedule x Bit-Width Boundary in Sub-100M Quantisation-Aware Training cites this paper.

Mapping the Schedule x Bit-Width Boundary in Sub-100M Quantisation-Aware Training Low-Rank Quantization-Aware Training for LLMs

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T23:14:01.454198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4d1da84d-5601-4736-9bf5-6c465c7f900d · 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 Low-Rank Quantization-Aware Training for LLMs

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:42:36.026504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.