Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
RPTQ: Reorder-based Post-training Quantization for Large Language Models
As of 23 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2304.01089.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-07-23T06:31:01.910684+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-13T23:28:12.790404Z
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
- 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 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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+00:00.
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 2026-07-23T06:31:01.910684+00:00.
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 2026-07-23T06:31:01.910684+00:00.
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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+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 2026-07-23T06:31:01.910684+00:00.
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 2026-07-23T06:31:01.910684+00:00.
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 2026-07-23T06:31:01.910684+00:00.