Paper Citation Record · LEDGER

RPTQ: Reorder-based Post-training Quantization for Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 29 inbound Pith citation observations for arXiv:2304.01089.

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

pith.paper-citation-record.v1
2304.01089 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 29 of 29 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T22:37:02.587052Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:00:08.944266Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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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 89cc0276-8bc5-403c-921b-2fcc2860711c · inbound

ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models cites this paper.

ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:49:33.787420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 85e27ffc-a300-4148-af5a-c63f955a1acb · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 207

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:39:33.244077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f4de0dba-4110-4ca8-9826-474856e95ec3 · inbound

MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design cites this paper.

MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:57:40.243433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d00b8fea-f7c7-4142-a4fa-5805dbb79238 · inbound

Exploring Model Invariance with Discrete Search for Ultra-Low-Bit Quantization cites this paper.

Exploring Model Invariance with Discrete Search for Ultra-Low-Bit Quantization RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-08T22:37:02.587052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2073583e-f852-4897-886e-2964a26e4b1b · inbound

AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization cites this paper.

AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:52:23.062751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fbf5668c-8cac-4748-a6fc-822c4398d3aa · 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 RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:25.793744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc21011f-198d-4ce5-9c00-4842c0696f96 · inbound

TuneComp: Joint Fine-tuning and Compression for Large Foundation Models cites this paper.

TuneComp: Joint Fine-tuning and Compression for Large Foundation Models RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T13:27:10.956921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c95b49e-d931-464c-98ec-bb89f3495c16 · inbound

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models cites this paper.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.624008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13490d82-3ed5-4eda-b554-a31cda926761 · inbound

Squeeze10-LLM: Squeezing LLMs' Weights by 10 Times via a Staged Mixed-Precision Quantization Method cites this paper.

Squeeze10-LLM: Squeezing LLMs' Weights by 10 Times via a Staged Mixed-Precision Quantization Method RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T14:45:38.639462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6644c61f-3f2d-4246-872a-185b49f7c556 · 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 RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-05T15:52:45.093167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03aa1266-58e4-4cc7-8560-b6e8ed5ba1da · inbound

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations cites this paper.

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-21T18:50:30.311609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5ac0f39a-a64c-4e12-9e53-881bb58db631 · inbound

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations cites this paper.

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-03T23:21:42.161586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6150133e-1454-4909-b6ec-bcf7fa526510 · inbound

QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models cites this paper.

QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-15T20:20:17.374756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3da5324d-3b7e-44ae-8e2c-9e2cb07b62b5 · inbound

Efficient Reasoning on the Edge cites this paper.

Efficient Reasoning on the Edge RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 136

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 a9b442a1-ba3f-4408-993a-67f5ede655aa · inbound

Rethinking Residual Errors in Compensation-based LLM Quantization cites this paper.

Rethinking Residual Errors in Compensation-based LLM Quantization RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:21:01.312642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 96c44a8a-e9b6-4a33-ba10-f4f6da1b5d05 · inbound

SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models cites this paper.

SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:30:58.368957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8e3f20cc-97f4-453c-b71e-ecb11294b2fd · inbound

Robust Ultra Low-Bit Post-Training Quantization via Stable Diagonal Curvature Estimate cites this paper.

Robust Ultra Low-Bit Post-Training Quantization via Stable Diagonal Curvature Estimate RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:15:28.863706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9ec8468d-0d9a-4872-9295-d7531edd22f1 · inbound

LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation cites this paper.

LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T12:46:04.778377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d7e86a4d-29aa-48df-abd7-8a11172dfb6b · inbound

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization cites this paper.

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:30:44.117085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3a500291-32c2-4680-9473-776ffd37d6dc · inbound

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization cites this paper.

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:01:18.170290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 12841d55-2b35-40df-ad8b-13b5fa4e4569 · inbound

An Empirical Study of OpenPangu Quantization on Ascend NPUs cites this paper.

An Empirical Study of OpenPangu Quantization on Ascend NPUs RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T06:09:36.913745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bbf59f15-bb4f-4cbf-be9d-9aee9fdd0906 · inbound

An Empirical Study of OpenPangu Quantization on Ascend NPUs cites this paper.

An Empirical Study of OpenPangu Quantization on Ascend NPUs RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T19:43:55.205571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d8ed24ce-ee72-455a-b734-cb6f284d30b0 · inbound

An Empirical Study of OpenPangu Quantization on Ascend NPUs cites this paper.

An Empirical Study of OpenPangu Quantization on Ascend NPUs RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T10:43:33.017954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed5ccabd-6b68-4bc8-b566-8684cf917e7b · inbound

BitNet Text Embeddings cites this paper.

BitNet Text Embeddings RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:00:08.946068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation be4909c9-1ac6-4e44-8e94-20dbf0afa05f · inbound

BitNet Text Embeddings cites this paper.

BitNet Text Embeddings RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.901412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d357f259-4126-4b35-b23e-e876a82b86cb · inbound

SAB-LVLM: Significance-Aware Binarization for Large Vision-Language Models cites this paper.

SAB-LVLM: Significance-Aware Binarization for Large Vision-Language Models RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:18:37.370737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f0dd7933-3e00-456a-97b0-f7ae3b6a76cf · 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 RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-02T03:32:54.396982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30d49bec-e832-49a0-a3b8-ffb2052a5bd6 · inbound

PolyQ: Codesigning End-to-End Quantization Framework for Scalable Edge CPU LLM Inference cites this paper.

PolyQ: Codesigning End-to-End Quantization Framework for Scalable Edge CPU LLM Inference RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T01:39:09.041444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccad053f-d63a-4a6a-8328-29b06be6eacc · inbound

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference cites this paper.

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 129

Resolution: unresolved; no resolver link, observed 2026-08-01T17:12:39.721365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.